literature review hydropower plant

• Open access
• Published: 15 February 2023

Design models for small run-of-river hydropower plants: a review

• David Tsuanyo   ORCID: orcid.org/0000-0001-7073-4980 1 ,
• Boris Amougou 1 , 2 ,
• Abdoul Aziz 1 ,
• Bernadette Nka Nnomo 3 ,
• Davide Fioriti 4 &
• Joseph Kenfack 2  

Sustainable Energy Research volume  10 , Article number:  3 ( 2023 ) Cite this article

14k Accesses

10 Citations

3 Altmetric

Metrics details

Hydropower plants are among the most efficient and reliable renewable energy systems in the world as far as electricity production is concerned. Run-of-river hydropower plants seem more attractive than conventional hydroelectric plants since they can be a cheaper and environmentally friendly alternative. However, their expected energy production pattern heavily depends on several construction variables that need an appropriate design using specific models. This paper analyzes several existing models used for the calculation of the diameter and thickness of a penstock, the optimal selection and implantation (admissible suction head) of a turbine, to estimate the energy produced and expected cost of small hydropower projects for grid-connected and off-grid/micro-grid applications. This review particularly brings out the specificities of each of the models to suggest the most appropriate model according to the context of study and proposes methods to use them more efficiently. This review can be used as a guide in the design and simulation of run-of-river hydropower plants, thus helping in the assessment of the economic feasibility of projects that usually requires a high level of experience and expertise.

A critical review focused particularly on run-of-river hydropower plant design models was carried out.

Several calculation models including diameter and thickness of a penstock, admissible suction head of a turbine, and cost and energy production estimation for grid-connected applications are collected and analyzed.

Hydropower models for design and generation profile prediction presented can be used to optimally come against the variability problem of run-of river plants.

The paper can be used as a guide in the design and simulation of run-of-river hydropower plants with appropriate models.

Introduction

Till date, more than 81% of the world's energy consumption comes from fossil sources despite the setbacks related, such as environmental impact and the gradual disappearance of the resource (Safarian et al., 2019 ). Global energy demand remains constantly growing, but the contribution of renewable energy sources is still estimated to be very low (13.7%) (Safarian et al., 2019 ; Yildiz & Vrugt, 2019 ). Renewable energy sources (wind, solar, geothermal, biomass and hydropower) are cleaner, sustainable and environmentally friendly sources, meaning they should be harnessed as much as possible.

Among all the renewable energy sources, hydropower, representing about 2.5% of the world energy resource and about 15.9% of the global electricity generation, is among the most efficient and reliable as far as electricity generation in the world is concerned (Bozorg Haddad et al., 2011 ; Hydropower status report, sector trends & insights, 2019 ; Jadoon et al., 2020 ; Safarian et al., 2019 ). A hydro-power plant harnesses the energy of moving water to drive a turbine, which in turn will run a generator for electricity production. This technology is well understood and has many advantages (Breeze, 2005 ), among which a relatively low-marginal-cost and low greenhouse gas emission (Stoll et al., 2017 ), with nearly constant prices over the years (Ghosh & Prelas, 2011 ; Sattouf, 2014 ).

Usually, a typical hydropower plant is made of a dam (which creates the reservoir), a trash rack (that prevents debris from entering the intake), a water tunnel, a penstock (to divert the water to the turbine), a speed governor (controlling wicket gates to permanently adapt water flow variations to the energy demand), a turbine and a generator (Fig.  1 a) (Acakpovi et al., 2014 ; Pagès et al., 2003 ; Singh & Chauhan, 2011 ). As for run-of-river hydropower plants, it is generally a weir which is responsible for diverting the water from the river toward the intake. The water usually gets to the turbine after crossing a desilting tank. Water can also be brought to a forebay by a canal, and then the penstock will convey it to the turbine (Vougioukli et al., 2017 ). Figure  1 b shows the components of run-of-river hydropower plants.

a Typical hydropower plant with reservoir; b Run-of-river hydropower plant

The main particularity of run-of-river projects is that they do not need large reservoirs, which leads to several benefits. First, their construction time is shorter and their overall cost is lower compared to storage plants projects of this same capacity (Ibrahim et al., 2019 ). Second, they pose less problems of inundation and sedimentation, have a less harmful impact on fish migration, and decrease the problem of high rehabilitation, the disorder at the level of navigation and the problem of people moving, aspects that usually go with large-scale hydropower projects (Kumar & Katoch, 2014 ). Another advantage of run-of-river hydropower projects is the fact that they drive generators with small turbines that can be easily manufactured locally, thus promoting job creation and economic development through local industry (Goodland, 1994 ). Because of these advantages mentioned above, it is easier to get public and government’s acceptance for run-of-river hydropower projects as compared to storage plant projects, which need large submergence areas (Kumar & Katoch, 2014 ).

In the work of Korkovelos et al. ( 2018 ), it was found that the small-scale (1–10 MW) hydropower potential in Sub-Saharan Africa is estimated at 21,800 MW, and run-of-river hydropower plants are generally categorized as small hydropower plants (Bozorg Haddad et al., 2011 ; Safdar et al., 2020 ; Vougioukli et al., 2017 ). An overview of the small hydropower potential of each of the 44 Sub-Saharan African countries can be seen in Appendix 1 (Korkovelos, et al., 2018 ). In view of this great potential, it emerges that the small-scale hydropower and consequently run-of-river systems can be a very suitable option for rural electrification in Africa (Okedu et al., 2020 ). Indeed, they have made a significant contribution to the sustainable development of rural and remote areas in various developing countries these last years (Malhan & Mittal, 2021 ). There is no internationally agreed definition of small hydropower plants. The level of development of a country makes it possible to classify hydropower plants as shown in the Appendix 2 (Bhat & Prakash, 2014 ; Elbatran et al., 2015 ; Mishra et al., 2012 ; Ohunakin et al., 2011 ).

Despite the fact that the use of run-of-river hydropower plants goes with many advantages (Casila et al., 2019 ; Yildiz & Vrugt, 2019 ), the intense variability of their resource can have a significant impact on the quality of electricity and on the balance of the grid. Many hydropower models for design and generation profile prediction are used to come against this variability problem. Each of the models has its singularity. It is for this reason that this review regroups them to present their particularities and to orientate their choices for more efficient use. Moreover, the prefeasibility study of small hydropower projects generally represents a significant proportion of overall project costs and requires a high level of experience and expertise (Punys et al., 2011 ). Hence, it is important to analyze existing models to provide the elements, which can facilitate optimal design and operation of run-of-river hydropower plants from the least possible data (average daily flow and gross head), and less expertise possible in a single document.

However, the recent literature is lacking extensive literature reviews on modeling run-of-river projects. In Kuriqi et al., ( 2021 ), the major ecological impacts of run-of-river projects were reviewed, yet modeling factors were not on major focus. The review in Sasthav and Oladosu ( 2022 ) focused on only low-head run-of-rivers in the United States with some yet limited modeling perspectives. Finally, the authors in Singh and Singal ( 2017 ) reviewed the system operation of several hydro plants, yet the specific detailed models were not in the focus. Therefore, it turns out that reviewing design methodologies for run-of-river projects is not only timely but also needed.

This paper aims at examining numerical models for the optimal design of run-of-river hydropower plants without pondage. This is done with a particular focus on the optimal design of a penstock (calculation of the diameter and thickness), the optimal selection and implantation (admissible suction head) of a turbine, the estimation of energy production for central-grid applications and the estimation of the cost of small hydropower projects. More in detail, the main novelties of this study lay in (a) identifying and reviewing all major technical and economic parameters needed for the optimal design of run-of-river project, based on relevant literature and in-field experience, and (b) proposing a classification of the reviewed models to be possibly used as a reference by scholars and practitioners in the field.

Overview of run-of-river hydropower plants

Run-of-river hydropower plants are characterized by the fact that they do not have a water reserve allowing a seasonal regulation (Bozorg Haddad et al., 2011 ; Goodland, 1994 ; Pagès et al., 2003 ; Yildiz & Vrugt, 2019 ). They use the natural flow on river of water from upstream. Therefore, these plants are less flexible than hydropower plants with large reservoirs because their electricity output depends on the availability of water in the river. This particularity makes the energy generated proportional to water inflow, which is why the amount of power produced by run-of-river hydropower plants varies considerably throughout the year. Multiple hydraulic turbines can be set up to have a better control on these flow variations (Bozorg Haddad et al., 2011 ) and vary depending on the run-of-river hydropower plant configurations.

These configurations, regrouped into the diversion type plants without dams, the weir type plants and the river current systems type plants (using kinetic energy devices), can involve penstock pipes, open channels, barrages and other diversion methods.

In the diversion type plants without dams, a portion of the water diverted from fast flowing rivers can be used directly to feed a penstock. This will move the water down to the turbine (Fig.  2 a), whereas in other cases, the intake system instead feeds a diversion channel first before reaching the penstock passing through a forebay tank (Fig.  2 b) (Aquaret, 2012 ; Publishers, 2015 ).

Run-of-river in diversion type plants a without forebay tank and b with forebay tank

In the weir type plants (Fig.  3 a, c), the capacity of the system is directly linked to the existing flow of water through the dam which maintains the river flow (Penche, 2004 ; Publishers, 2015 ). There is also a weir type plant where the water of the river damned with a weir is allowed to flow through low-head turbines housed in the weir to generate electricity (Fig.  3 b) (Aquaret, 2012 ; Publishers, 2015 ).

Run-of-river in weir type plants a directly linked to the existing flow of water with floating intake b with flow through low-head turbines housed and c directly linked to the existing flow of water with protected intake

The river current systems type plants are using kinetic energy devices (reaction turbines, small bulb turbines, underwater turbines, oscillating hydrofoils, and venturi devices) installed directly into flowing water to harness the kinetic energy of the water of the river; hence, these systems are generally small. This type can make use of existing structures such as bridges (Aquaret, 2012 ; Publishers, 2015 ) (Fig.  4 ).

Run-of-river in river current systems type

Generally, run-of-river hydropower projects deal with two main activities. One main activity includes civil works, such as diversion weir and intake, desilting chamber, power channel including headrace channel, forebay and spillway, penstock, powerhouse building, or tailrace channel. The other main activity includes electromechanical equipment, namely turbines with governing systems and generators with excitation systems, switch gears, control and protection equipment, among others, which are all sheltered by the powerhouse (Mishra et al., 2012 ; Vougioukli et al., 2017 ; Yildiz & Vrugt, 2019 ).

As introduced, there are several configurations and components to take into consideration while dealing with run-of-river hydropower projects, of which the penstock and the turbine turn out to be the most relevant, hence heavily discussed in this study. After discussing the models for the design of a penstock (diameter and thickness), then the choice of the appropriate selection and implementation of the turbine (admissible suction head) for a given run-of-river without pondage project will be detailed.

The models presented in this review are appropriate for the design of a run-of-river hydropower plant that has a penstock and no reservoir, independently of the configuration chosen. Changes can occur if there is a reservoir because its presence will make sure that the flow reaching the turbine is not always the direct flow of the stream available for the plant, but this case will not be discussed in this paper.

Penstock models

To make the right choice of a penstock for a project, materials, diameter, wall thickness, type of joint and relative cost must be taken into account (Fraenkel et al., 1999 ; Penche, 2004 ).

Several methods used to determine the diameter and the wall thickness of the penstock of a small hydropower plant are presented in this subsection (Fig.  5 ).

Calculation models of the penstock diameter

To calculate the diameter of a penstock, one of the equations presented in the Table 1 can be used considering its limits.

Selecting a diameter can also be an iterative process. It is even the best way of selecting the appropriate diameter of a penstock since all the formulae have their limits. This method involves starting with a first estimate of what might be a suitable diameter obtained via one of the formulae of Table 1 and then adjusting that estimate according to the calculated head losses and the price (Fraenkel et al., 1999 ).

For example, the objective can be the restriction of the total head loss between 2 and 10%. Usually, the head loss is less than 4% according to the ESHA standard (Obinna Ajala Chinyere & Emmanuel Osiewundo Ojo, 2017 ). While using this method, one of the formulae of the Table 1 can be used for a first estimation of the diameter, which will serve as a guide diameter; the first value for the iteration process to get the best penstock. Obinna et al. ( 2017 ) proceeded like that using the first empirical Eq. (5) of the Table 1 to calculate the first estimate of a diameter to design a penstock for Kuchigoro Small Hydro Project.

Calculation models of the penstock thickness

The thickness of the penstock must be able to guarantee sufficient rigidity to withstand the maximum possible overpressure, which occurs when the valve that links the penstock to the turbine is closed in a short time (Fraenkel et al., 1999 ). This means that the determination of the minimum thickness of a penstock depends on the expected surge pressure and the properties of the penstock (Fraenkel et al., 1999 ).

The surge pressure head is calculated by the Eqs. ( 1 ), ( 2 ), ( 3 ) and ( 4 ) below:

where h surge

h surge : Surge pressure head (m)

h max : Maximum possible pressure (m)

h gross : Gross head (m)

C : Velocity of the pressure wave through the water (m/s)

V : Flow velocity with valve fully open (m/s)

\(\rho\) : Density of water (kg/m 3 )

\(k\) : Bulk Modulus of water (N/mm 2 )

\(E\) : Young’s Modulus of Elasticity for penstock material (N/m 2 )

\(D\) : Penstock diameter (mm)

\(e\) : Penstock wall thickness (mm)

e min : Penstock minimum wall thickness (mm)

\(:\) Gravitational acceleration (m/s 2 )

\(\sigma\) : Ultimate tensile strength of penstock material (N/mm 2 )

\(F\) : Safety factor, typically 3.

It is worth noticing that the expressions of the minimum thickness \({e}_{\text{min}}\) and the expected surge pressure \({h}_{\text{surge}}\) are mutually dependent. Hence, an iterative approach is needed to estimate the value of the thickness (Fraenkel et al., 1999 ).

The algorithm allowing the calculation of the thickness of a penstock is presented as below (Fraenkel et al., 1999 ):

Initialize a first estimate of \({e}_{0}\)

Calculate c, \({h}_{\text{max}}\) and \({e}_{\text{min}}\) for the current iteration i

Compare \({e}_{i}\) and \({e}_{\text{min}}\) :

if \({e}_{i}<\)   \({e}_{\text{min}}\) , update \({e}_{i+1}={e}_{i}+\Delta {e}_{i}\) and go to 2

if \({e}_{i} \gg\)   \({e}_{\text{min}}\) , set \({e}_{i+1}={e}_{\text{min}}\) , and go to 2

if \({e}_{i} \cong {e}_{\text{min}}\) and \({e}_{i}\ge {e}_{\text{min}}\) , go to 4

\({e}_{i}\) should be increased by 1.5 mm while dealing with mild steel pipes to take into consideration corrosion effects.

According to Ramos et al. ( 2000 ), the most dangerous situation the penstock must withstand occurs when it is subjected to a great depression due to the appearance of the vacuum. Thus, the minimum thickness a steel penstock with a diameter D must have to withstand such condition is calculated through the inequation below:

While using this method, 1 mm must be added to the value of the penstock thickness calculated to take into account the effects of corrosion (Ramos et al., 2000 ). In the numerical model of Yildiz and Vrugt ( 2019 ), the minimum thickness of the penstock is calculated using this method.

ESHA (Penche, 2004 ) also proposed other equations for the estimation of the minimum wall thickness that will make the penstock rigid enough to be handled without danger of deformation in the field. The equations are presented below:

where D is the diameter in m

where D is the diameter in mm.

The Eq. ( 23 ) with an additional margin of 1.2 was also used for feasibility studies of micro-hydro-power plant projects in Cameroon (Kengne Signe et al., 2017 a; Kengne Signe et al., 2017 b).

In conclusion, for the calculation of the thickness of a penstock, Eqs. ( 1 ), ( 2 ), ( 3 ) and ( 4 ) seem to be better appropriate since they can be used for all types of penstock material compared to the other models used only for steel pipes. However, their iteration process makes them a relatively more complex model that needs higher computational time and resources to be used, yet modern computers are well capable of bearing the burden.

Equations ( 22 ) and ( 23 ) guarantee the survival of the penstock during its manipulation in the field. This is why it might be more cautious to calculate three minimum thicknesses using Eq. ( 3 ), ( 22 ) and ( 23 ) to ultimately choose the largest value.

Models for the selection of hydraulic turbines

Turbine is made of (1) a nozzle that directs the flow to the runner, (2) a runner that converts the hydraulic energy into mechanical work and (3) a shaft that transfers the mechanical work to the electrical generator (Sangal et al., 2013 ), components that altogether determine the flexibility options and total energy production from the water flow. Commonly, there are two principal categories of hydro-turbines: impulse turbines, such as Pelton, Cross-flow and Turgo, for sites with high head and reaction turbines, such as propeller, Kaplan, Francis, screw and hydro-kinetic turbines, for sites generally with lower head and higher flows (Okot, 2013 ; Sangal et al., 2013 )). Typically, the head and flow available on a site are the principal criteria that orientate the choice of a hydro turbine for a given project (Paish, 2002 ). Nevertheless, it is also important to use the efficiency curves of turbines (like the one of Fig.  6 ) to know how the turbines will react to variations in flow rates and therefore determine the one which is the most suitable for a given installation site and river system (Okot, 2013 ; Yildiz & Vrugt, 2019 ).

Typical small hydro-turbines efficiencies (Chapallaz et al., 1995 )

Determination models of the nominal discharge

The choice of the nominal flow is important since the height of a proposed site does not really vary meanwhile the available flow varies a lot (Bezabih, 2021 ). Based on the flow duration curve, it is possible to determine the nominal flow of a hydropower plant. It is the maximum flow rate that can pass through the penstock and the turbine without causing inadmissible energy losses (Dubas & Pigueron, 2009 ). The nominal flow must be chosen carefully to have a hydro-project profitable and efficient enough. A good choice should make sure the plant works all the time at its maximum capacity while exploiting efficiently the hydraulic energy of the water (Dubas & Pigueron, 2009 ).

There are different ways to choose the nominal flow of a hydropower plant. The simplest way is to fix the mean annual flow as the nominal flow. In the work of Adejumobi and Shobayo ( 2015 ) on the optimal choice of turbines for small hydropower plants, the average annual flow has been considered as the nominal flow. According to Heteu and Martin ( 2001 ), the choice of the nominal flow depends on the use of the plant. If the hydropower plant is the only source of supply to the consumer or the mini-grid, the nominal flow is the flow reached for at least 250 days a year. Otherwise, the production must be the most important factor and the optimum flow in that case will be around a flow reached for a period between 50 and 90 days a year. This methodology was used for feasibility studies of micro-hydro-power plant projects in Cameroon while assessing the fall river of Kemken and Bakassa (Kengne Signe et al., 2017 a; Kengne Signe et al., 2017 b). For those two projects, systems were decentralized, and the flow rate of equipment used was the one, which exceeded 250 days per year (Kengne Signe et al., 2017 a; Kengne Signe et al., 2017 b). In the same way, Hanggi and Weingartner ( 2012 ) also mentioned in their work that the choice of the nominal flow depends on the desired operation or purpose of the hydropower plant. They recommended that for hydropower plants operating in an isolated network, the approximate values of the nominal flow should be less or equal to the flow reached for at least 255.5 days a year while that for hydropower plants in parallel operation should be between the flow reached for at least 54.75 days to 91.25 days a year.

According to Alexander and Giddens ( 2008 ), the equation below can also be used to find the optimum discharge for any diameter.

where \(\lambda\)  is the friction factor determined by the surface roughness of the penstock material (–), \({H}_{\text{g}}\text{ is}\) the gross head (m), S  is the penstock slope = \({H}_{\text{g}}\)  / L (–), D is the diameter of the penstock (m) and h is the head loss (m).

As with the formula of the calculation of the diameter of a penstock relying on the cost and the slope of the penstock presented in Table 1 (Eq. (17)), the objective is to have the head loss h = \({H}_{\text{g}}\)  /3 to achieve maximum power.

Voros et al. ( 2000 ) worked on how to design small hydroelectric plants while maximizing the economic benefits of the investment and they proposed an empirical equation allowing determining the optimum nominal flow rate of the hydro-turbines and concluded that it can be used safely for short-cut design purposes. This empirical equation is presented below:

where \({q}_{*50}\) is flow rate duration curve parameter, defined as \(/\) , \(q_{*\min }\) is flow rate duration curve parameter, defined as \(Q_{*\min }\) \(/\) , \(q_{\max }\) is hydro turbine maximum working flow rate fraction, Q max is annual highest stream flow rate (m 3 /s) and \(\gamma\) is short-cut model parameter with the values 0.422 for Francis turbines, 0.369 for Pelton turbines and 0.364 for Axial turbines.

In the study of Munir et al. ( 2015 ), a new parameter, known as the inverse incremental energy was used to select the optimum flow of the hydropower plant at head of Upper Chenab Lower (UCC) at Bamanwala. The nominal flow was selected through comparison of increment of energy with respect to change in flow. A relationship between inverse incremental energy and flow was plotted for the selection of the appropriate flow.

In conclusion, as seen above, there are several methodologies for the determination of the nominal discharge of a small hydropower project. Each of these methods can be used in specific contexts and situations as a starting point for the assessment of the potential of hydropower sites. However, to determine the best nominal discharge for a better exploitation of the energy potential of a natural stream or for a more economical project, we recommend using of an optimization algorithm related to appropriate objectives functions.

Selection of the appropriate type of turbine

The net head is the first criterion to estimate a suitable turbine for a hydropower project (Pagès et al., 2003 ; Paish, 2002 ; Penche, 2004 ) and Table 2 gives the range of operating heads by type of turbine.

A first technique used in the selection of turbines makes use of charts like that in Fig.  7 that depict the expected suitable ranges of net head and water flow admissible by technology (Paish, 2002 ; Penche, 2004 ). However, it is important noticing that the specific curve is strictly manufacturer-specific; hence, that plot shall be used as a preliminary reference.

: Typical range chart of turbines (Chapallaz et al., 1995 )

Another criterion that can also orientate in the selection of the appropriate turbine type is the specific speed. The specific speed is the speed in rpm of a turbine with a unit head and a unit output power. Impulse turbines have low specific speeds; Francis turbines have medium specific speeds and propeller or Kaplan have high specific speeds (Ramos et al., 2000 ). The specific speed of a turbine can be calculated as follows:

where \(Q\) is the discharge in m 3 /s, \(n\) the rotational speed of the turbine in rpm, \(E\) the specific hydraulic energy of the machine in J/kg, \(f\) the frequence of the electric system in Hz, \(p\) the number of pairs of poles of the trubine’s generator, \(g\) the gravitational constant in m/s 2 and \({H}_{\text{net}}\) the net head in m.

Without a speed increaser, the rotational speed of the turbine has the same value than the rotational speed of its generator. The rotational speeds of asynchronous generators will be 1 to 2% higher than the value of rotational speeds of the corresponded synchronous generators, a slight over-speed being necessary to create the magnetic field in the machine (Chapallaz et al., 1995 ).

According to Chapallaz et al. ( 1995 ), the maximum speed of the generator must be limited to 1500 rpm to consider the over-speeding of the runaway. Over-speeding causes very significant mechanical stress, and the minimum speed limited to 600 rpm, as because below this speed, the volume of the generator, hence its price compared to the installed power, increases with a decline in yield due to increased losses. When the rotational speed of the turbine is less than 600 rpm, it usually drives a generator with a low number of poles (1000 or 1500 rpm) via a speed increaser.

Thus, after calculating the specific speed of a hydro-project, the appropriate type of turbine can be selected through the Table 3 , which describes the operating speed limits by turbine.

This way of characterizing turbines through the specific speed was even used in the numerical model of Yildiz and Vrugt ( 2019 ).

Generally, in the prefeasibility study phase, the head and the design flow rate are used to select the appropriate type of turbine for a project since usually there is no enough information to calculate the specific speed. The choice of the methodology for selecting the type of turbine requires this level of information.

Cavitation model

The cavitation phenomenon occurs when a high-enough negative pressure occurs at the exit of the wheel, such as when a reaction turbine is located well above the downstream plan. In those conditions, water vaporizes and the corresponding vapor bubbles first detach from the surface of the runner blade and then implode creating strong pressure waves as soon as they reach an area where pressure is higher. As these implosions cause fast erosion of the blades, they must be avoided by accurately design the turbine discharge to limit the depression at its exit. To do so, the so-called suction head H S , which measures the distance between the downstream plan of water and the axis of the wheel of the turbine, shall be limited.

To reduce the construction costs, a reaction turbine shall be placed as high as possible in reference to the downstream level, but this increases the value of H S and cavitation may occur. Therefore, to protect turbines, it is important to know the suction head threshold beyond which cavitation appears relevant enough to damage the wheel during the implantation of a turbine. In mathematical terms, H S is calculated as follows (Penche, 2004 ):

where \({H}_{\text{s}}\) (m) is the limited suction head, \({H}_{\text{a}}\) (m) is the water height equivalent to atmospheric pressure, H v (m) is the water height equivalent to the vaporization pressure, H (m) is the net head, V (m/s 2 ) is the outlet average velocity (as a first approach, one can consider 2 m/s according to ESHA (Penche, 2004 )) and σ is a dimensionless coefficient called the Thomas’s coefficient.

\({H}_{\text{a}}\) can be calculated with the formula below (Yildiz & Vrugt, 2019 ):

where \({P}_{0}\) is the atmospheric pressure in Pa at sea level and \(z\) is the altitude of the power house in m.

\(\sigma\) can be calculated with the equations below (Penche, 2004 ):

where V is the outlet average velocity in m/s 2 and H the net head in m.

In the techno-economical method for sizing the capacity of a small hydropower plant by Santolin et al. ( 2011 ), the limited suction head was also calculated with the equation above but with different equations for the calculation of the Thomas’s coefficient: \(\sigma\) was calculated with the equations below:

where \({\omega }_{\text{s}}\) is the dimensionless specific speed (with values lying in the intervals [0.04, 0.40] for Pelton turbines, [0.4, 1] for Slow Francis turbines, (Safarian et al., 2019 ; Yildiz & Vrugt, 2019 ) for Normal Francis turbines, [2.0, 2.5] for Quick Francis turbines and [2.5, 8.0] for Kaplan turbines) and \(\omega\) the rotation velocity in rad/s.

Turbine operation models

It is worth noticing that each turbine can only operate between a minimum and a maximum flow rate, reflecting its limit in exploiting the available hydraulic energy. Hence, in a hydropower plant where there is only one turbine, the power output of the turbine can be represented as follows (Anagnostopoulos & Papantonis, 2007 ; HOMER, 2019 ):

\({Q}_{\text{exploited}}\) : Exploited discharge (m 3 /s).

\({Q}_{\text{exploitable}}\) : Exploitable discharge (m 3 /s).

Q min : Minimal discharge (m 3 /s).

Q miax : Maximal discharge (m 3 /s).

The minimal discharge is usually given as a percentage of the rated discharge (Penche, 2004 ), whose values by turbine type are reviewed and summarized in Table 4 .

Hanggi and Weingartner ( 2012 ) proposed a new parameter \(Q_{{{\text{safety}}}}\) , which is the safety flow beyond which the turbine operation has to be to avoid damages. By taking into account this new security constraint, the new operating schedule below emerged: (Yildiz & Vrugt, 2019 ):

Hanggi and Weingartner ( 2012 ) recommended to set \(Q_{{{\text{safety}}}}\) equal to the river discharge with an exceedance probability of 2% and it was done by Yildiz and Vrugt ( 2019 ) in their work.

It is worth mentioning that in most hydro-projects, environmental regulation mandates a minimum non-usable to bypass the hydropower plant to limit damages to the ecosystem. There are several hydrological-based environmental flows methods, which allow estimating this minimum flow. According to Kuriqi et al. ( 2019 ), the choice of 10% or 15% daily flow as minimum flow, methods named 10% or 15% Daily Flow, is considered appropriate. One of the methods can be used as reference method and can be combined with other methods.

Accordingly, the exploitable flow is obtained by the equation:

where \(Q\) Exploitable : Exploitable flow (m 3 /s).

\(Q\) river : Flow of the river (m 3 /s).

Q f : Reserved flow (m 3 /s).

However, given the variability of the river flow across the year and the operating schedules above, the efficient exploitation of a hydraulic resource, particularly in run-of-river plants with one turbine, can be challenging. For this reason, multiple turbines of different size operated in parallel may be used to enhance overall exploitation of the potential energy, but project, operation and maintenance costs may rise. This financial constraint limits most models to two turbines in practical terms (Anagnostopoulos & Papantonis, 2004 , 2007 ).

While dealing with two turbines, the operating schedule is a bit more complex. Two examples of operating schedule in the case of two turbines of different size working in parallel have been seen in the literature.

The first example is the methodology of Anagnostopoulos and Papantonis ( 2007 ) that does not consider the parameter \({Q}_{\text{safety}}\) , conversely to the second example of Yildiz and Vrugt ( 2019 ).

Calculation model of the energy production

The electric power generated by each turbine can be calculated using the formula below (RETScreen International, 2001 ):

where D : diameter of the penstock (m), \(L\) \(:\) Penstock length (m), \(:\) friction factor from moody chart of Darcy’s equation (–), \(V\) \(:\) velocity of water at the time t (m/s), \(\Delta H_{{{\text{major}}}}\) : losses due to friction (m), \(\Delta H_{{{\text{minor}}}}\) : singular or local losses (m), \(\varepsilon\) : coefficient of singular loss (–), P elec \(:\) electric power the time t (kW), \(\rho\) : density of water (kg/m 3 ), \(g\) \(:\) gravitational acceleration (m/s 2 ), Q t , k : exploited discharge of the turbine number k at the time t (m 3 /s), \(h_{{{\text{net}}}}\) \(:\) Net head (m) \(,\) : gross head (m) \(,\) : efficiency of the turbine number k at the time t (%) \(, :\) efficiency of the generator (%), \(l_{{{\text{trans}}}}\) \(:\) the transformer losses (–) \(,:\) line losses (–).

The calculation of turbine efficiencies can be done with the efficiency equations presented in the Retscreen engineering and cases textbook (RETScreen International, 2001 ) which are derived from a large number of manufacture efficiency curves for different turbine types and head and flow conditions. Gagliano et al. ( 2014 ) to evaluate the technical feasibility of repowering an old Silican hydro-power plant also used this equation for the calculation of electric power by a turbine. The results of the simulation were sufficiently reliable.

The amount of energy E in kilowatt hours (kWh) produced by n turbines of a run-of-river hydropower plant over a time period \(\Delta\) t can be calculated using the formula below

Equation ( 43 ) is one of the most general energy calculation formulae identified in the literature since it takes into account not only the electrical losses of all equipment (turbine, alternator, transformer), but also all types of line losses, such as those due to a parasitic load or an inappropriate cable section. The efficiency of the increaser should also be considered when it is needed between the turbine and the generator. Although the evolution of the generator efficiency with load is not considered in this equation, it generally gives a good representation of the total energy production, when the average efficiency is considered (Yildiz & Vrugt, 2019 ).

It is important to note that in grid-connected applications, all the potential energy that the hydro-power plant can generate is usually sold, unless grid outages occur. Instead, in off-grid applications depending on the actual load, the hydro-power plant may not be exploited completely and renewable production may be curtailed. This article focuses on the generation system, which can then be connected to the grid or enable a mini-grid or off-grid system. However, the issue of distribution of the generated energy is not discussed in this article.

There are also three indices, namely the energy production index \({E}_{f}\) , the load index \({L}_{f}\) and the water exploitation index \({W}_{f}\) , which can be useful for the assessment of the efficiency of a hydropower plant. \({W}_{f}\) denotes the fraction of the stream flow that passes through the operating turbines, \({E}_{f}\) is the sum of the generated energy divided by the energy potential of the natural stream at a gross head during a year period and \({L}_{f}\) is the ratio of the mean (annually) produced power to the installed nominal power (Anagnostopoulos & Papantonis, 2004 , 2007 ).

Cost estimation models of small hydropower projects

While dealing with a small hydropower project, it is important to evaluate its financial viability along with technical feasibility before taking any investment decision. That is the reason why several researchers developed multiple models for the estimation of the cost of a small hydropower project defining different cost-influencing parameters, which represent the variables of the equations. The most common cost-influencing parameters are the power and the net head.

Singal and Saini ( 2007 ) made an analysis for the cost of canal-based small hydropower schemes in the plains and other regions of the country in which water is used also for other purposes, like irrigation/drinking through canals, small dams, etc., and developed the correlation in Eq. ( 43 ) for estimating the cost of such schemes. The results of the correlation showed a maximum deviation of ± 12%, so the correlation can be used to predict the cost of a small hydropower plant at the planning stage.

Another study carried out by Singal et al. ( 2008 ) on the cost optimization based on electromechanical equipment of canal-based low-head (3–20 m) small hydropower scheme proposed correlations for the cost in Indian Rupees per kilowatt of the main components. These main components include civil works (diversion channel, spillway and power house building) and electromechanical equipment (turbine with governing system, generator with excitation system, control and protection equipment, electrical and mechanical auxiliaries, and main transformer and switchyard equipment). The correlations are presented below:

\(\text{Cost of diversion channel}\) : \(C_{1} = a_{1} P^{{x_{1} }} H^{{y_{1} }}\) (45)

\(\text{Cost of spillway}\) : \(C_{2} = a_{2} P^{{x_{2} }} H^{{y_{2} }}\) (46)

\(\text{Cost of power house building}\) : \(C_{3} = a_{3} P^{{x_{3} }} H^{{y_{3} }}\) (47)

\(\text{Cost of turbines with governing system}\) : \(C_{4} = a_{4} P^{{x_{4} }} H^{{y_{4} }}\) (48)

\(\text{Cost of generator with excitation system}\) : \(C_{5} = a_{5} P^{{x_{5} }} H^{{y_{5} }}\) (49)

\(\text{Cost of electrical }\&\text{ mechanical auxiliaries}\) : \(C_{6} = a_{6} P^{{x_{6} }} H^{{y_{6} }}\) (50)

\(\text{Cost of transformer }\&\text{ switchyard equipment}\) : \(C_{7} = a_{7} P^{{x_{7} }} H^{{y_{7} }}\) (51)

with \({a}_{1}=9904, {x}_{1}=-0.2295, {y}_{1}=-0.0623\)

\({a}_{3}\) , \({x}_{3}\) , and \({y}_{3}\) can be obtained via Table 5 and the other coefficients via Table 6 .

The total project cost includes the cost of civil works, the direct cost of electromechanical equipment and various items, and other indirect costs. This miscellaneous and indirect cost (that includes the costs of designs, indirect costs, tools and plants, communication, preliminary charge of preparing the report, survey and investigation, environmental impact assessment and cost of land) represents 13% of the sum of the cost of civil works and electromechanical equipment. Thus, the total cost of the project in this case can be calculated through the equation below:

In the work of Singal et al. ( 2010 ) on the analysis for cost estimation of low-head (3–20 m) run-of-river small hydropower schemes, other correlations were proposed for estimating the costs of several subcomponents of civil works. This includes diversion weir and intake, desilting chamber, power channel including head race channel, forebay and spillway, penstock, powerhouse building and tail race channel and electromechanical equipment (turbine with governing system, generator with excitation system, control and protection equipment, electrical and mechanical auxiliaries, main transformer and switchyard equipment). The correlations are presented below:

\(\text{Cost of power house building}\) : \(C_{1} = 92615P^{ - 0.2351} H^{ - 0.0585}\) (55)

\(\text{Cost of diversion weir and intake}\) : \(C_{2} = 12415P^{ - 0.2368} H^{ - 0.0597}\) (56)

\(\text{Cost of power channel}\) : \(C_{3} = 85383P^{ - 0.3811} H^{ - 0.0307}\) (57)

\(\text{Cost of desilting chamber}\) : \(C_{4} = 20700P^{ - 0.2385} H^{ - 0.0611}\) (58)

\(\text{Cost of forebay and spillway}\) : \(C_{5} = 25402P^{ - 0.2356} H^{ - 0.0589}\) (59)

\(\text{Cost of penstock}\) : \(C_{6} = 7875P^{ - 0.3806} H^{ - 0.3804}\) (60)

\(\text{Cost of tail race channel}\) : \(C_{7} = 28164P^{ - 0.376} H^{ - 0.624}\) (61)

Finally, the cost in Indian Rupees per kilowatt of civil works is

\(\text{Cost of turbines with governing system}\) :

\(\text{Cost of generator with excitation system}\) :

\(\text{Cost of electrical }\&\text{ mechanical auxiliaries}:\)

\(\text{Cost of transformer }\&\text{ switchyard equipment}\) :

Finally, the cost in Indian Rupees per kilowatt of electromechanical equipment is

For the same reasons mentioned in the work of Singal et al. ( 2008 ), the total cost of the project in this case too will be calculated through the Eq. ( 53 ).

Ogayar and Vidal ( 2009 ) developed correlations to estimate the cost of the electromechanical equipment (turbine, alternator and regulator) based on the head and the power. Here, we have an equation for each type of turbine: Pelton, Francis, Kaplan and semi-Kaplan for a power range below 2 MW. The results of these equations can be used to determine the initial investment at a previous study level when planning refurbishment or new construction of small hydropower plants without developing a complete project. These equations had been validated with real installations in different countries of the world (Spain, France, Italy, Belgium, Portugal, and Morocco) with committed errors lower than 20%. Santolin et al. ( 2011 ) used these equations in their techno-economical method for capacity sizing of a small hydropower plant to determine the machine cost. They were even updated by Gallagher et al. ( 2015 ) in his four-step methodology for assessing potential energy recovery sites in water and wastewater infrastructure in the UK and Ireland.

The correlations obtained were:

\(COST = 17.693P^{( - 0.3644725)} H^{( - 0.281735)}\) (68) in €/kW for Pelton turbine with errors ranged between − 23.83% and 20.015% ( R 2  = 93.16%);

\(COST = 25.698P^{( - 0.560135)} H^{( - 0.127243)}\) (69) in €/kW for Francis turbine with errors ranged between − 15.83% and 22.27% ( R 2  = 72.26%);

\(COST = 33.236P^{( - 0.58338)} H^{( - 0.113901)}\) (70) in €/kW for Kaplan turbine with errors ranged between − 18.53% and 23.5% ( R 2  = 91.7%);

\(COST = 19.498P^{( - 0.58338)} H^{( - 0.113901)}\) (71) in €/kW for Semi-Kaplan turbine with errors ranged between − 18.53% and 23.5% ( R 2  = 91.72%).

Mishra et al. ( 2011a ) also developed correlations for the estimation of the cost of the electromechanical equipment (turbine-alternator) in run-of-river small hydropower projects based on the head and the power. They used three different methods: sigma plot method, linest method and logest method. The results obtained from these correlations were verified from the data of electro-mechanical equipment of installed small hydropower projects. The results of the sigma plot software had a maximum error of ± 10%, the ones of the linest method had a maximum error of ± 5% and the ones of the logest method had a maximum error of ± 18%. Therefore, they are regarded as suitable for the preliminary cost estimation of the electromechanical equipment in small run-of-river hydropower projects.

(Sigma plot method)

(Linest method)

(Logest method)

In the review of Mishra et al. ( 2012 ) on electromechanical equipment applicable to small hydropower plants, other correlations developed for the cost of run-of-river small hydropower projects under low head (3–20 m) considering the head and the power were presented. Here, there is an equation for the cost estimation of turbines with governing system \(( {C}_{\text{t}}\) ), an equation for the cost estimation of generators with excitation system \(( {C}_{\text{g}}\) ), an equation for the cost estimation of electrical and mechanical auxiliaries \(( {C}_{\text{e}}\) ) and another one for the estimation of the cost of transformers and switchyard equipment \(( {C}_{\text{tr}}\) ). The equations are presented below:

where \({C}_{\text{e}\&\text{m}}\) is the cost per kilowatt of electromechanical equipment, H the net head in m and P the power in kW.

Mishra et al. ( 2011b ) proposed other correlations for the estimation of the investment cost of an entire small hydropower scheme under low head plants. There were formulas for civil works and formulas for electromechanical equipment.

For civil works, we have:

Intake (C 1 ): \(14382P^{( - 0.2368)} H^{( - 0.0596)}\) (76) with one unit, \(17940P^{( - 0.2366)} H^{( - 0.0596)}\) (77) with two units, \(21191P^{( - 0.2367)} H^{( - 0.0597)}\) (78) with three units and \(24164P^{( - 0.2371)} H^{( - 0.06)}\) (79) with four units;

Penstock (C 2 ): \(4906P^{( - 0.3722)} H^{( - 0.3866)}\) (80) with one unit, \(7875P^{( - 0.3806)} H^{( - 0.3804)}\) (81) with two units, \(9001P^{( - 0.369)} H^{( - 0.389)}\) (82) with three units and \(10649P^{( - 0.3669)} H^{( - 0.3905)}\) (83) with four units;

Power house building (C 3 ): \(62246P^{( - 0.2354)} H^{( - 0.0587)}\) (84) with one unit, \(92615P^{( - 0.2351)} H^{( - 0.0585)}\) (85) with two units, \(121027P^{( - 0.2354)} H^{( - 0.0587)}\) (86) with three units and \(146311P^{( - 0.2357)} H^{( - 0.0589)}\) (87) with four units;

Tailrace channel (C 4 ): \(28164P^{( - 0.376)} H^{( - 0.624)}\) (88) with one unit, \(28164P^{( - 0.376)} H^{( - 0.624)}\) (89) with two units, \(28164P^{( - 0.376)} H^{( - 0.624)}\) (90) with three units and \(28164P^{( - 0.376)} H^{( - 0.624)}\) (91) with four units.

For electromechanical equipment, we have:

Turbine with governing system (C 5 ): \(39485P^{( - 0.1902)} H^{( - 0.2167)}\) (92) with one unit, \(63346P^{( - 0.1913)} H^{( - 0.217)}\) (92) with two units, \(83464P^{( - 0.1922)} H^{( - 0.2178)}\) (93) with three units and \(101464P^{( - 0.1920)} H^{( - 0.2177)}\) (94) with four units;

Generator with excitation system (C 6 ): \(48568P^{( - 0.1867)} H^{( - 0.2090)}\) (95) with one unit, \(78661P^{( - 0.1855)} H^{( - 0.2090)}\) (96) with two units, \(105046P^{( - 0.1859)} H^{( - 0.2085)}\) (97) with three units and \(127038P^{( - 0.1858)} H^{( - 0.2085)}\) (98) with four units;

Mechanical and electrical auxiliaries (C 7 ): \(31712P^{( - 0.1900)} H^{( - 0.2122)}\) (99) with one unit, \(40860P^{( - 0.1892)} H^{( - 0.2118)}\) (100) with two units, \(49338P^{( - 0.1898)} H^{( - 0.2080)}\) (101) with three units and \(56625P^{( - 0.1896)} H^{( - 0.2121)}\) (102) with four units;

Main transformer and switchyard equipment (C 8 ): \(14062P^{( - 0.1817)} H^{( - 0.2082)}\) (103) with one unit, \(18739P^{( - 0.1803)} H^{( - 0.2075)}\) (104) with two units, \(23051P^{( - 0.1811)} H^{( - 0.2080)}\) (105) with three units and \(26398P^{( - 0.1809)} H^{( - 0.2079)}\) (106) with four units.

Thus, the formula to calculate the total cost per kW (Rs) is \({\mathbf{1}}.{\mathbf{13}}(C_{1} + \, C_{2} + \, C_{3} + \, C_{4} + C_{5} + \, C_{6} + \, C_{7} + \, C_{8} )\) (107).

Yildiz and Vrugt ( 2019 ) computed the cost of electromechanical equipment (turbine, generator and power transformer) using the equation of Ogayar and Vidal ( 2009 ):

where j is the exchange rate of euro to US dollar, P is the installed capacity of the plant in MW, a , b and c are coefficients of calculation depending on the type of turbine used. The multiplication factor 1/1000 converts the units of P from MW to kW. The cost of the penstock was calculated with the equation below:

where \(D\) , \(k\) and \(L\) are the diameter, the thickness and the length of the penstock in units of meters, \({d}_{s}\) in ton/m 3 denotes the steel density and \({c}_{\text{ton}}\) in $/ton is the penstock cost per ton weight.

The total cost of civil works was calculated with the Eq.  110 below:

where \(\alpha\) is a unitless coefficient called site factor (it can take on values between 0 and 1.5). The yearly maintenance and operation cost \({C}_{\text{om}}\) are estimated using the expression \({C}_{\text{om}}={\beta C}_{\text{em}}\) with \(\beta\) a unitless coefficient whose value ranges between 0.01 and 0.04. It was considered here that the electromechanical equipment has a life-span of about 25 years and the plant has a lifespan of 50 years. Hence, the total monetary investment in this numerical model is estimated using Eq.  111 below:

Dubas and Pigueron ( 2009 ) established a formula given the price, dated September 2009, of electromechanical equipment (the guard valve, the turbine, the generator as well as control-command, safety devices and cabinets) based on series of invoices and offers for this equipment. The formula relies on the maximum hydraulic power as presented in Eq. ( 112 ):

While using this formula, if the price obtained is lower than 20′000 CHF, then 20′000 CHF should be considered as the price. However, this price may vary from single to double depending on the supplier. In addition, this price was related to the specific economic and market situation of that time: when mini-turbines are in great demand, or when the prices of steel or copper prices are high, such as in recent periods, prices increase, making it difficult to be precise.

More recently, Mishra et al. ( 2018 ) developed a methodology for cost assessment of high head (beyond 100 m) run-of-river small hydropower plant projects to determine their techno-economic viability before undergoing detailed investigation. In this work, it is still the capacity and the head that have been considered as cost-influencing parameters. The correlations for cost proposed in this study were based on different types of head race conduit, penstock materials, types of turbine and types of generator for various layouts. It was concluded that these correlations could be used for reasonable cost estimation of hydropower projects for planning of such projects. The costs obtained through these correlations are in Indian Rupees. The correlations of costs are presented in Eqs.  113 and 114 :

Cost per kilowatt of civil works

The equations for the calculation of costs of civil works components presented above are used with Table 7 and considering the prices as per schedule of rates prevailing for the year 2012 in India (Penche, 2004 ). Thus, the prices used are as follows:

The price for earthwork in excavation with all leads and lifts in ordinary soil is 265 Indian Rupee/m 3 ;

The price for earthwork in excavation with all leads and lifts in soft rock, where blasting is not required is 330 Indian Rupee/m 3 ;

The price for earthwork in excavation with all leads and lifts in hard rock, including blasting is 550 Indian Rupee/m 3 ;

The price for M20 grade concrete work in plain cement concrete as well as in reinforced cement concrete, including shuttering, mixing, placing in position, compacting, and curing is 3640 Indian Rupee/m 3 ;

The price for reinforcement steel bars of iron 500 grade, including cutting, bending, binding, and placing in position is 55,000 Indian Rupee/MT;

The price for structural steel, including fabrication, transportation to site, and erection is 75,000 Indian Rupee/MT.

Cost per kilowatt of electromechanical equipment

The electromechanical equipment considered and the value of the constants \({a}_{1}\) , \({x}_{1}\) and \({x}_{2}\) are presented in Table 8 .

For the same reasons mentioned in the work of Singal et al. ( 2008 ), the total cost of a high head run-of-river small hydropower plant project can be calculated through Eq. ( 53 ).

These equations for the estimation of the cost of small hydropower projects presented in this part should be used carefully because they give a rough estimation of the costs of specific markets at specific times.

Conclusion and future scope

This paper presents a detailed review of models for the techno-economic design of a run-of-river hydropower plants. In particular, the technical modeling of the diameter and thickness of a penstock, the optimal selection and implantation (admissible suction head) of the turbine, the estimation of energy production systems and the estimation of the cost of small hydropower projects were extensively reviewed and discussed. These modeling approaches provide a powerful tool for the technical, economical, and financial feasibility study of run-of-river hydropower sites, to feed Artificial Intelligence and optimization algorithms. The limitation and validity of each have been clarified to inform readers on the generalizability of the study, as technology and market conditions evolve.

Therefore, this study can be of interest for scholars and developers interested in developing run-of-river feasibility studies and further research activity, especially in the context of Sub-Saharan Africa. The results of this review could also be used to develop a tool for the preliminary studies of run-of-river hydropower projects.

Availability of data and materials

All data analyzed during this study are included in this published article.

Acakpovi, A., Ben Hagan, E., & Xavier Fifatin, F. (2014). Review of hydropower plant models. International Journal of Computer Applications, 108 (18), 33–38. https://doi.org/10.5120/19014-0541

Article   Google Scholar  

Adejumobi, I., & Shobayo, D. (2015). Optimal selection of hydraulic turbines for small hydro electric power generation—A case study of Opeki River, South Western Nigeria. Nigerian Journal of Technology, 34 (3), 530. https://doi.org/10.4314/njt.v34i3.15

Alexander, K. V., & Giddens, E. P. (2008). Optimum penstocks for low head microhydro schemes. Renewable Energy, 33 (3), 507–519. https://doi.org/10.1016/j.renene.2007.01.009

Anagnostopoulos, J., & Papantonis, D. E. (2004). Application of evolutionary algorithms for the optimal design of a small hydroelectric power plant. Conference HYDRO 2004: A new era for hydropower.

Anagnostopoulos, J. S., & Papantonis, D. E. (2007). Optimal sizing of a run-of-river small hydropower plant. Energy Convers. Manag., 48 (10), 2663–2670. https://doi.org/10.1016/j.enconman.2007.04.016

Aquaret, Run-of-River. (2012). http://www.aquaret.com/indexa224.html?option=com_content&view=article&id=88&Itemid=233&lang=en . Accessed 13 Feb 2020.

Bezabih, A. W. (2021). Evaluation of small hydropower plant at Ribb irrigation dam in Amhara regional state, Ethiopia. Environmental Systems Research . https://doi.org/10.1186/s40068-020-00196-z

Bhat, V. I. K., & Prakash, R. (2014). Life cycle analysis of run-of river small hydro power plants in India. Open Renewable Energy Journal, 1 (1), 11–16. https://doi.org/10.2174/1876387100901010011

Bozorg Haddad, O., Moradi-Jalal, M., & Marino, M. A. (2011). Design-operation optimisation of run-of-river power plants. Water Management, 164 (9), 463–475.

Google Scholar  

Breeze, P. A. (2005). Power generation technologies. Elsevier; Newnes.

Casila, J. C., Duka, M., De Los Reyes, R., & Ureta, J. C. (2019). Potential of the Molawin creek for micro hydro power generation: An assessment. Sustainable Energy Technologies and Assessments., 32 , 111–120. https://doi.org/10.1016/j.seta.2019.02.005

Chapallaz, J. M., Mombelli, H. P., & Renaud, A. (1995). Turbines hydrauliques journées de formation pour ingénieurs : petites centrales hydrauliques. Brochure of Journées de formation pour ingénieurs, Programme d’action PACER–Energies renouvelables. Office fédéral des questions conjoncturelles, Lausanne, p. 130.

Dubas, M., & Pigueron, Y. (2009). Guide pour l’étude sommaire de petites centrales hydrauliques, manuel de cours. Haute Ecole Spécialisée de Suisse Occidentale (HES-SO), ed 1.

Edeoja, A., Ibrahim, J., & Kucha, E. (2016). Investigation of the effect of Penstock configuration on the performance of a simplified pico-hydro system. British Journal of Applied Science and Technology, 14 (5), 1–11. https://doi.org/10.9734/bjast/2016/23996

Elbatran, A. H., Abdel-Hamed, M. W., Yaakob, O. B., Ahmed, Y. M., & Arif Ismail, M. (2015). Hydro power and turbine systems reviews. Jurnal Teknologi, 74 (5), 83–90. https://doi.org/10.11113/jt.v74.4646

Fraenkel, P., Paish, O., Harvey, A., Brown, R., Edwards, A., & Bokalders V. (1999). Micro-hydro power: A guide for development workers. Intermed. Technol. Publ., no. June, p. 150.

Gagliano, A., Tina, G. M., Nocera, F., & Patania, F. (2014). Technical and economic perspective for repowering of micro hydro power plants: A case study of an early XX century power plant. Energy Procedia, 62 , 512–521. https://doi.org/10.1016/j.egypro.2014.12.413

Gallagher, J., Harris, I. M., Packwood, A. J., McNabola, A., & Williams, A. P. (2015). A strategic assessment of micro-hydropower in the UK and Irish water industry: Identifying technical and economic constraints. Renewable Energy, 81 , 808–815. https://doi.org/10.1016/j.renene.2015.03.078

Ghosh, T. K., & Prelas, M. A. (2011). Energy resources and systems: Volume 2: Renewable resources . Springer Netherlands. https://doi.org/10.1007/978-94-007-1402-1

Book   Google Scholar  

Goodland, R. (1994). Environmental sustainability and the power sector. Impact Assessment, 12 (4), 409–470. https://doi.org/10.1080/07349165.1994.9725877

Hänggi, P., & Weingartner, R. (2012). Variations in discharge volumes for hydropower generation in Switzerland. Water Resources Management, 26 (5), 1231–1252. https://doi.org/10.1007/s11269-011-9956-1

Héteu, P. T., & Martin, J. (2003). La filière hydroélectrique : Aspects technologiques et environnementaux. UCL-GEB, Louvain, Prix Tractebel 2001, working paper n°5.

Hoesein, A. A., & Montarcih, L. (2011). Design of micro hydro electrical power at Brang Rea River in West Sumbawa of Indonesia. Journal of Applied Technology in Environmental Sanitation., 1 (2), 177–183.

HOMER, Hydro Turbine Flow Rate; https://www.homerenergy.com/products/pro/docs/latest . Accessed 02 Oct 2019.

Hydropower status report, sector trends and insights. (2019). www.hydropower.org . Accessed 15 Mar 2020.

Ibrahim, M., Imam, Y., & Ghanem, A. (2019). Optimal planning and design of run-of-river hydroelectric power projects. Renewable Energy, 141 , 858–873. https://doi.org/10.1016/j.renene.2019.04.009

Jadoon, T. R., Khurram Ali, M., Hussain, S., Wasim, A., & Jahanzaib, M. (2020). Sustaining power production in hydropower stations of developing countries. Sustainable Energy Technologies and Assessments, 37 , 1–16. https://doi.org/10.1016/j.seta.2020.100637

Kengne Signe, E. B., Hamandjoda, O., & Nganhou, J. (2017a). Methodology of feasibility studies of micro-hydro power plants in Cameroon: Case of the micro-hydro of KEMKEN. Energy Procedia, 119 , 17–28. https://doi.org/10.1016/j.egypro.2017.07.042

Kengne Signe, E. B., Hamandjoda, O., Nganhou, J., & Wegang, L. (2017b). Technical and economic feasibility studies of a micro hydropower plant in Cameroon for a sustainable development. Journal of Power Energy Engineering, 05 (09), 64–73. https://doi.org/10.4236/jpee.2017.59006

Kishore, T. S., Patro, E. R., Harish, V. S. K. V., & Haghighi, A. T. (2021). A comprehensive study on the recent progress and trends in development of small hydropower projects. Energies, 14 (10), 2882. https://doi.org/10.3390/en14102882

Korkovelos, A., Mentis, D., Siyal, S. H., Arderne R. H., Bazilian, M., Howells, M., Beck, H., & Roo, A. D. (2018). A geospatial assessment of small-scale hydropower potential in sub-Saharan Africa. Energies . https://doi.org/10.3390/en11113100

Kumar, D., & Katoch, S. S. (2014). Sustainability indicators for run of the river (RoR) hydropower projects in hydro rich regions of India. Renewable and Sustainable Energy Reviews, 35 , 101–108. https://doi.org/10.1016/j.rser.2014.03.048

Kuriqi, A., Pinheiro, A. N., Sordo-Ward, A., Bejarano, M. D., & Garrote, L. (2021). Ecological impacts of run-of-river hydropower plants—Current status and future prospects on the brink of energy transition. Renewable and Sustainable Energy Reviews. https://doi.org/10.1016/j.rser.2021.110833

Kuriqi, A., Pinheiro, A. N., Sordo-Ward, A., & Garrote, L. (2019). Influence of hydrologically based environmental flow methods on flow alteration and energy production in a run-of-river hydropower plant. Journal of Cleaner Production, 232 , 1028–1042. https://doi.org/10.1016/j.jclepro.2019.05.358

Malhan, P., & Mittal, M. (2021). Evaluation of different statistical techniques for developing cost correlations of micro hydro power plants. Sustainable Energy Technologies and Assessments, 43 , 1–9. https://doi.org/10.1016/j.seta.2020.100904

Mishra, S., Singal, S. K., & Khatod, D. K. (2011a). Approach for cost determination of electro-mechanical equipment in Ror projects. Smart Grid and Renewable Energy, 02 (2), 63–67. https://doi.org/10.4236/sgre.2011.22008

Mishra, S., Singal, S. K., & Khatod, D. K. (2011b). Optimal installation of small hydropower plant—A review. Renewable and Sustainable Energy Reviews, 15 (8), 3862–3869. https://doi.org/10.1016/j.rser.2011.07.008

Mishra, S., Singal, S. K., & Khatod, D. K. (2012). A review on electromechanical equipment applicable to small hydropower plants. International Journal of Energy Research, 36 (5), 553–571. https://doi.org/10.1002/er.1955

Mishra, S., Singal, S. K., & Khatod, D. K. (2018). Cost optimization of high head run of river small hydropower projects. In M. Majumder (Ed.), Application of geographical information systems and soft computation techniques in water and water based renewable energy problems (pp. 141–166). Springer. https://doi.org/10.1007/978-981-10-6205-6_7

Chapter   Google Scholar  

Mohsin Munir, M., Shakir, A. S., & Khan, N. M. (2015). Optimal sizing of low head hydropower plant—A case study of hydropower project at head of UCC (Lower) at Bambanwala. Journal of Engineering and Applied Science, 16 , 73–83.

Nasir, B. A. (2014). Design considerations of micro-hydro-electric power plant. Energy Procedia, 50 , 19–29. https://doi.org/10.1016/j.egypro.2014.06.003

Obinna Ajala Chinyere, N. R. O., & Emmanuel Osiewundo Ojo Chidozie Okonkwo, E. U. M. (2017). Technical details for the design of a Penstock for Kuchigoro small hydro project. American Journal of Renewable Sustainable Energy, 3 (4), 27–35.

Ogayar, B., & Vidal, P. G. (2009). Cost determination of the electro-mechanical equipment of a small hydro-power plant. Renewable Energy, 34 (1), 6–13. https://doi.org/10.1016/j.renene.2008.04.039

Ohunakin, O. S., Ojolo, S. J., & Ajayi, O. O. (2011). Small hydropower (SHP) development in Nigeria: An assessment. Renewable and Sustainable Energy Reviews, 15 (4), 2006–2013. https://doi.org/10.1016/j.rser.2011.01.003

Okedu, K. E., Uhunmwangho, R., & Odje, M. (2020). Harnessing the potential of small hydro power in Cross River state of Southern Nigeria. Sustainable Energy Technologies and Assessments, 37 , 1–11. https://doi.org/10.1016/j.seta.2019.100617

Okibe Edeoja, A., Ibrahim, S. J., & Kucha, E. I. (2015). Conceptual design of a simplified decentralized pico hydropower with provision for recycling water. Journal of Multidisciplinary Engineering Science and Technology, 2 (2), 3159–3199.

Okot, D. K. (2013). Review of small hydropower technology. Renewable and Sustainable Energy Reviews, 26 , 515–520. https://doi.org/10.1016/j.rser.2013.05.006

Pagès, J. M., Supparo, E., Lafage, B., Etienne, J., & Valet, T. (2003). Guide pour le montage de projets de petite hydroélectricité—CONNAÎTRE POUR AGIR—Guides et cahier s techniques. Agence de l’Environnement et de la Maitrise de l’Energie (ADEME), p. 159, Ed. Rouland.

Paish, O. (2002). Small hydro power: Technology and current status. Renewable and Sustainable Energy Reviews, 6 (6), 537–556. https://doi.org/10.1016/S1364-0321(02)00006-0

Penche, C. (2004). Guide on how to develop a small hydropower plant. European Small Hydropower Association—ESHA, p. 296.

Publishers, E. (2015). Run-of-river hydropower systems. www.ee.co.za/article/run-of-river-hydropower-systems.html . Accessed 9 Feb 2020.

Punys, P., Dumbrauskas, A., Kvaraciejus, A., & Vyciene, G. (2011). Tools for small hydropower plant resource planning and development: A review of technology and applications. Energies, 4 (9), 1258–1277. https://doi.org/10.3390/en4091258

Ramos, H., Betâmio De Almeida, A., Manuela Portela, M., & Pires De Almeida, H. (2000). Guideline for design of small hydropower plants, Western Regional Energy Agency & Network, 2000.

RETScreen International. (2001). Engineering-Cases-Textbook, Clean Energy Project Analysis, 2001–2004.

Safarian, S., Unnthorsson, R., & Ritcher, C. (2019). A review of biomass gasifcation modelling. Renewable and Sustainable Energy Reviews, 110 , 378–391. https://doi.org/10.1016/j.rser.2019.05.003

Safdar, I., Sultan, S., Raza, H. A., Umer, M., & Ali, M. (2020). Empirical analysis of turbine and generator efficiency of a Pico hydro system. Sustainable Energy Technologies and Assessments, 37 , 1–7. https://doi.org/10.1016/j.seta.2019.100605

Sangal, S., Garg, A., & Kumar, D. (2013). Review of optimal selection of turbines for hydroelectric projects. International Journal of Emerging Technolology and Advanced Engineering, 3 (3), 424–430.

Santolin, A., Cavazzini, G., Pavesi, G., Ardizzon, G., & Rossetti, A. (2011). Techno-economical method for the capacity sizing of a small hydropower plant. Energy Conversion Management., 52 (7), 2533–2541. https://doi.org/10.1016/j.enconman.2011.01.001

Sasthav, C., & Oladosu, G. (2022). Environmental design of low-head run-of-river hydropower in the United States: A review of facility design models. Renewable and Sustainable Energy Reviews . https://doi.org/10.1016/j.rser.2022.112312

Sattouf, M. (2014). Simulation model of hydro power plant using Matlab/Simulink. International Journal of Engineering Research and Applications, 4 (1), 295–301.

Singal, S. K., & Saini, R. P. (2007). Analytical approach for cost estimation of low head small hydro power schemes. International Conference on Small Hydropower—Hydro Sri Lanka, p. 4.

Singal, S. K., Saini, R. P., & Raghuvanshi, C. S. (2008). Cost optimisation based on electro-mechanical equipment of canal based low head small hydropower scheme. The Open Renewable. Energy Journal, 1 , 26–35. https://doi.org/10.2174/1876387100901010026

Singal, S. K., Saini, R. P., & Raghuvanshi, C. S. (2010). Analysis for cost estimation of low head run-of-river small hydropower schemes. Energy for Sustainable Development, 14 (2), 117–126. https://doi.org/10.1016/j.esd.2010.04.001

Singh, G., & Chauhan, D. (2011). Development and simulation of mathematical modelling of hydraulic turbine. International Journal on Control System and Instrumentation., 02 (2), 55–59.

Singh, V. K., & Singal, S. K. (2017). Operation of hydro power plants—A review. Renewable and Sustainable Energy Reviews, 69 , 610–619. https://doi.org/10.1016/j.rser.2016.11.169

Singhal, M. K., & Kumar, A. (2015). Optimum design of penstock for hydro projects. International Journal of Energy and Power Engineering., 4 (4), 216–226. https://doi.org/10.11648/j.ijepe.20150404.14

Stoll, B., et al. (2017). Hydropower modeling challenges hydropower modeling challenges. National Renewable Energy Laboratory (NREL), United States. https://doi.org/10.2172/1353003 .

Voros, N. G., Kiranoudis, C. T., & Maroulis, Z. B. (2000). Short-cut design of small hydroelectric plants. Renewable Energy, 19 (4), 545–563. https://doi.org/10.1016/S0960-1481(99)00083-X

Vougioukli, A. Z., Didaskalou, E., & Georgakellos, D. (2017). Financial appraisal of small hydro-power considering the cradle-to-grave environmental cost: A case from Greece. Energies, 10 (4), 430. https://doi.org/10.3390/en10040430

Yildiz, V., & Vrugt, J. A. (2019). A toolbox for the optimal design of run-of-river hydropower plants. Environmental Modelling & Software, 111 , 134–152. https://doi.org/10.1016/j.envsoft.2018.08.018

Download references

Acknowledgements

The Cameroon Ministry of Scientific Research and Innovation supported this work under the SETaDiSMA project. The SETaDiSMA project is part of the LEAP-RE programme. LEAP-RE has received funding from the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement 963530.

European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement 963530 through LEAP-RE project.

Author information

Authors and affiliations.

National Center for Development of Technologies-Ministry of Scientific Research and Innovation, PO Box 1457, Yaoundé, Cameroon

David Tsuanyo, Boris Amougou & Abdoul Aziz

National Advanced School of Engineering/ L3E, University of Yaoundé I, PO Box 8390, Yaoundé, Cameroon

Boris Amougou & Joseph Kenfack

Institute of Geological and Mining Research- Hydrological Research Centre (IRGM-CRH)-Ministry of Scientific Research and Innovation, PO Box 1457, Yaoundé, Cameroon

Bernadette Nka Nnomo

Department of Energy, Systems, Territory and Construction Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56122, Pisa, Italy

Davide Fioriti

You can also search for this author in PubMed   Google Scholar

Contributions

Conceptualization, D.T and B.A.; methodology, D.T. and B.A.; validation, J.K. and D.F.; formal analysis, D.T., B.A. and A.A.; investigation, B.A. and A.A.; writing—original draft preparation, B.A and D.T.; writing—review and editing, all authors; visualization, D.T.; supervision, D.T.; project administration, D.T.; funding acquisition, D.T. All authors have read and approved the final manuscript.

Corresponding author

Correspondence to David Tsuanyo .

Ethics declarations

Ethics approval and consent to participate.

Not applicable.

Consent for publication

Competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Small hydropower technical potential per country for 44 Sub-Saharan African countries (Korkovelos et al., 2018 )

Small hydropower definition and classification in some selected countries and organizations (Bhat & Prakash, 2014 ; Elbatran et al., 2015 ; Mishra et al., 2012 ; Ohunakin et al., 2011 )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Tsuanyo, D., Amougou, B., Aziz, A. et al. Design models for small run-of-river hydropower plants: a review. Sustainable Energy res. 10 , 3 (2023). https://doi.org/10.1186/s40807-023-00072-1

Download citation

Received : 11 June 2022

Accepted : 05 January 2023

Published : 15 February 2023

DOI : https://doi.org/10.1186/s40807-023-00072-1

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Run-of-river
• Hydropower plant
• Optimal design
• Energy system modeling

• Search Menu
• Sign in through your institution
• Advance Articles
• Author Guidelines
• Open Access Options
• Self-Archiving Policy
• About International Journal of Low-Carbon Technologies
• Editorial Board
• Advertising and Corporate Services
• Journals Career Network
• Dispatch Dates
• Journals on Oxford Academic
• Books on Oxford Academic

Article Contents

1 introduction, 2 methodology, 3 data observation and data analysis, 4 results and discussion, 5 conclusion and recommendation, acknowledgements.

• < Previous

Problems identification and performance analysis in small hydropower plants in Nepal

• Article contents
• Figures & tables
• Supplementary Data

Roshan Pandey, Rajendra Shrestha, Nawraj Bhattarai, Rabin Dhakal, Problems identification and performance analysis in small hydropower plants in Nepal, International Journal of Low-Carbon Technologies , Volume 18, 2023, Pages 561–569, https://doi.org/10.1093/ijlct/ctad043

• Permissions Icon Permissions

Hydropower is powered by water, making it a clean source of energy. It contributes about 17% of worldwide annual energy generation and 90% of national energy generation, out of which 25% of its generation is contributed by small hydropower plants (SHPs). Thus, Nepal is predominantly dependent on a clean source of energy for power generation. In quantitative terms, approximately 70% of hydropower plants in Nepal are SHPs. Unfortunately, there are several bottlenecks to the smooth operation of these plants, viz. run-off-river hydropower with low water flow in dry season, insufficiency of proper guidance monitoring, regularization and inadequate and unfriendly policies. The study is based on primary and secondary data considering the SHPs spreading from eastern to western Nepal. Furthermore, the study follows the multicriteria decision analysis method to generalize the major issues at the sites. Inadequate water flow in the dry season is not the only issue for reduction in power generation; mechanical failure due to lack of monitoring and periodical maintenance is the predominant reason for the reduction in power output. This study discusses the role of reduction in water flow, unavailability of a trained workforce in rural hydropower areas, absence of appropriate equipment monitoring guidelines and inconsistent maintenance in the equipment failure and power production of hydropower plants. Every one in three SHPs has issues with smooth operation in terms of generation capacity, and overall, 50% of SHPs have mechanical issues as the major problem, which concludes the findings of the research.

Global installed hydropower capacity rose by 1.6% to 1330 GW in 2020, generating a record of 4370 TWh of clean electricity in 2020—higher than the previous record of 4306 TWh in 2019 [ 1 ]. Although most of the developed nations' electricity is mainly generated by coal, natural gas and even nuclear energy, hydropower is still the primary source of electricity for many countries. In 2020, hydropower supplied 17% of global electricity generation, the third largest source after coal and natural gas, and over the last 20 years, hydropower's total capacity rose 70% globally [ 2 ]. Being the largest low-emission source of electricity in the world, the hydropower installation rate is modest compared with solar and other renewable energy. Hydropower as one of the clean sources of energy has various options like run-off-river (ROR), reservoirs and pump storage methods of generation. Among these reservoir methods, high dams can contribute a huge energy supply, followed by pump storage systems producing 160 GW of supply in the world by 2019 [ 2 ].

Although small hydropower plants (SHPs) contribute only 1.5% of the world's installed electricity capacity and 7.5% of hydropower capacity, the role of SHP in developing countries is crucial. The world's SHP potential is estimated to be 78 GW, considering less than 10 MW as the standard size of which more than 66% have not been exploited yet. More than 65% of installed SHPs lie in the Asian region. Likewise, the South Asian region has an estimated SHP potential of 48.5 GW, and among which only 12% of it has been exploited in the region so far. The electrification rate in South Asia has increased to 75% in the last 6 years on average [ 3 ].

Hydropower is a clean and affordable commercial energy source, having a huge possibility as an electricity commodity for South Asia, including Nepal. Currently, hydropower structure has reached 86% in Nepal, and technical losses have declined to less than 15% in the national grid [ 4 ]. Even so, the South Asian average electrification rate is only 75%. Hydroelectric power plants with a smaller than 1-MW installed capacity are categorized as mini-/micro-hydropower plants, and those with an installed capacity larger than 1 MW and smaller than 10 MW are categorized as small hydroelectric power plants as per the Department of Electricity Development of Nepal [ 5 ]. But still, the definition of Nepal's SHP is not clear. At present, there are 17 micro-hydroelectric plants and 80 small hydroelectric power plants connected to the national grid [ 5 ]. The total installed hydroelectric power plants of Nepal stand at 2088 MW, out of which nearly 20% of its generation is contributed by SHPs. Unlike other renewable energy sources, an SHP can be considered one of the mature and reliable means of renewable energy generation that can be constructed with less investment and fewer administrative procedures than medium and large hydropower plants [ 6 ].

Although hydroelectric power is one of the main and low-cost sources of electricity generation for South Asian developing countries, it has a rapid rate of industrialization, urbanization and local level needs; however, international donor investments and abroad technologies and experiences still have to be managed [ 7 ]. Similarly, the role of SHPs in one of the neighboring countries, China, is also huge; it contributes to China's social, economic and environmental sectors. The country's electrification rate of 99.9% was mainly achieved through more than 47 000 hydropower stations in rural regions [ 8 ].

Despite the huge potential of hydroelectric power generation in Nepal, It is unfortunate that only 5% of the total generation capacity has been achieved yet [ 9 ]. However, in recent years, the hydropower generation rate has been increasing much more speedily than in earlier years. Many government policies, rules and regulations have been placed forward, and required amendments to the existing laws have been made to promote the expansion of hydroelectric power plants by the government of Nepal. There are many difficulties and challenges in electricity generation and even more in SHPs. Despite these challenges and difficulties, SHPs in Nepal are growing at a higher pace at both government and private levels. Although low investment costs, less administrative hassle and fewer gesture periods make the SHP develop at a faster rate, the problems regarding the reliability of the system, operation and maintenance issues along with problematic shutting down due to large machinery difficulties make investors think about the performance evaluation in such systems.

Even learning the practices from many developing countries, evaluating the performance of mechanical components and design consideration for SHP systems is a matter of high priority for various reasons like energy security, subsidy delivery and so on [ 10 ].

The equipment like real-time monitoring, automatic flaw detector, supervisory control and data acquisition system, oil refinery units and other necessary maintenance appliances could make the system reliable and run for long periods without any problematic shutdown. However, testing of components in hydropower plants can yield very useful information to the plant operators for future evaluation, and it is not even expensive or cumbersome [ 11 ].

There are still a few documents based on standard engineering practices that aim for procedural guidance to agencies responsible for the simple operation and maintenance of hydropower plants in Nepal to all government, public and private sector agencies [ 12 ]. However, the documents are not enough to give all the information and the details. The question is also regarding the quality and number of the implementing skilled workforce and investment that will be used in such operation maintenance methods.

As a consequence of low investment and less technical expertise requirements, SHP plants have attained a lot of popularity [ 13 ]. But the problems like routine maintenance, maintenance procedure; real-time monitoring, testing and calibration of the components are major in the SHPs of Nepal. The previous study also shows that the condition of hydroelectric plants below 1 MW is satisfactory regarding installed major components like a turbine, a generator and other electrical appliances and even poor in regard to components like bearings, shaft and couplings [ 14 ]. Hydromechanical, electromechanical and electrical components are the major problematic area of concern for old SHPs in Nepal in terms of reliability, safe operation and proper maintenance [ 15 ]. These previous studies also give the necessity for the study of SHPs above 1 MW of capacity having more or less similar components installed under similar circumstances. Maintenance is just limited to regular routine repair and periodic overhaul, which in the long run affect the performance of power plants [ 16 ].

Although it has been found that the plants above 10-MW installed capacity in Nepal have good performance in terms of efficiency and their performance has been enhanced in the latter year by increasing the efficiency of the components installed [ 17 ], the conditions of SHPs below 10 MW are still lower, and performance measures and upgrading inefficient technologies have not been practiced by either the public or the private sector.

Thus, the study mainly concentrates on problem identification and performance evaluation in SHPs of Nepal, focusing mainly on mechanical issues and the reliability of components installed in such plants. The study also gives a clear picture of electromechanical, mechanical and electrical issues along with their impact and the possible problematic shutdown in plants and their causes, along with the consequences on generation output.

The methodology followed for this research work consisted of a literature review and desk study of similar works and national and international practices, along with the development of mechanisms/protocols for current activities. The protocols started with the sampling of data with a preliminary survey and detailed field study. After the completion of primary data collection, data validation and comparison were done using various secondary data from sources like articles, reports, books and so on. Then, a detailed analysis of hydropower plants using parameters like power generation, power losses and overall functional condition of the plant had been done. The methods and steps taken for the study are explained in Figure 1 .

Schematic representation of the study methodology.

As shown in Figure 1 , preliminary data regarding hydropower generation and its status have been collected following the clustering method with 10% random sampling from the eastern to the western part of Nepal. The sampling data from eastern to western Nepal lie between 2.4 MW of the Panauti hydropower plant to 30 MW of the Chameliya hydropower plant. The reason behind the selection of hydropower plants up to 30 MW is only because of the International Organization for Standardization definition of SHPs. And the sampling plants are all ROR schemes since only one plant is reservoir type and no pump storage plant has been installed. After the sampling of plants, the questionnaires were developed and a protocol for the study was defined. The protocols comprised the site visit of plants, observing the plants and their components, interviewing, secondary data from the data log book and finally filling out the questionnaire. The questionnaire was developed in such a way that it would help survey plants of any size below 50 MW. The sample survey was done in Panauti hydropower plants at first, wherein the pros and cons were collected, and it was applied to the other plants. The survey questionnaires consist of general information (such as plant name, construction date, location, owner, etc.) and technical parameters (such as head, flow rate, types; components type, viz. generator, turbine, shaft, governor, bearings, etc.; and the condition of the components, mainly mechanical parts and the failure rate). They also consist of data regarding the times of failure, problem of the shutdown, maintenance period, maintenance persons, etc. Finally, the observation data were based on detailed problems and status. These bulk data were then checked and compared with the secondary data taken from the Dispatch Center, Nepal Electricity Authority (NEA), the sole organization that looks after the generation, production and transmission in the country. Thus, both the observed preliminary data from the questionnaire surveys revealed the current situations of these hydropower plants through compilation and preliminary analysis. The data collection was accomplished through a developed questionnaire by examining and interviewing the technicians and plant managers during the power plant visit.

The observed data along with the secondary data after validation were analyzed in two phases. Preliminary analysis was done at first with a simple compilation and surface study. The final and detailed analysis was completed after analyzing the data in more depth, considering the secondary data and results from such a similar study. The detailed analysis of data followed the standard guidelines and performance indices for the evaluation of plants. The performance indices were as follows: availability factor, plant factor, capacity factor, performance factor, annual energy generation per installed capacity, percentage loss and so on. Here, availability hours were defined as the ratio of net available hours to total hours of running; the plant factor was the ratio of annual energy generation by maximum possible generation and the capacity factor was defined as the ratio of actual energy generation to design generation, performance generation as a targeted generation to actual generation. Furthermore, plotting the graph of each value gave the results in each plant for analysis. Then, these performance indices were analyzed and compared with the actual data available on the site to find the actual result.

Furthermore, a detailed analysis sheet was deployed in the stations having more problematic components to get a clear picture of the plants. The comparative performance analysis was done using three indicators, viz. good, satisfactory and poor operation of components, along with detailed reasons for the problems. The validation of the analyzed study was done again to draw up the results and findings. Finally, the conclusion was drawn using a simple multicriteria decision analysis (MCDA) method with the help of analyzing the primary surveyed data, observing the information results and comparing them with the secondary data findings in the study.

Technical parameters and basic information of the surveyed power plants.

Status of electromechanical, mechanical and electrical components of the plants.

G indicates good; S, satisfactory; P, poor.

3.1 Data observation

First, the primary survey data and observed information from the site were examined. The data from 12 hydropower plants that were considered for the study gave primary information about their installed capacity, head, discharge rate, the turbine used and site location of the power plant. The basic and technical information in the questionnaire survey consists of hundreds of data. Some important technical parameters of the 12 surveyed plants are presented in Table 1 .

List of reasons for problematic shutdown in various hydropower plants.

Similarly, the questionnaire survey along with the technical observation of the status of major electromechanical, mechanical and electrical components was observed. The major problems with those components and the servicing of the components with skilled manpower were also observed. The main problem in the sites and skilled manpower supporting the issue were also observed in the survey. The observed data were filled out in the questionnaire in such a way that they gave the qualitative data of good, satisfactory and poor of three classes or ranks for the components. The rank defined for some components and equipment during the survey is illustrated in Table 2 .

Similarly, the problems of various equipment and components were observed and surveyed in detail during the study, with necessary breakdown maintenance. However, the reason for the problematic shutdown of various plants in the last few years is illustrated in Table 3 .

Even the period of all 12 plants for major maintenance was noted down, which showed time the problematic issues accumulated” and its solution timeline. Components detail problems for each machinery failure and their further consequences were also observed. Figure 2 illustrates the timeline for any major maintenance in each plant. The major maintenance in Panauti hydropower was observed to be 5 years with long duration time compared with other power plants. And the reasons behind the long duration for major maintenance were found to be insignificant low generation from the site and difficulty to repair and maintain the old system of that design.

Period of major maintenance for 12 plants.

The comparison of installed capacity versus the output power of various 12 plants in annual average and during a particular wet season is mentioned in Figure 3 , which gives information regarding the effectiveness of plants in terms of output. In Figure 3 , the annual average output of plants collected from the plant's logbook with the annual average and the output average for the months of (Bhadra) August and September was observed during the questionnaire survey.

Installed capacity versus annual average output and average output in August/September of various plants [ 18 [ .

3.2 Data analysis

Various performance indices are used to analyze the data in the plants. The annual average power output plotted along with the observation output in particular months can be observed in Figure 3a and b . It was found that the actual annual average power output and power output of the surveyed months differed in some of the hydropower plants. The generation output in the surveyed month seems to be lower than the annual average generation and power output although it is not the month of the dry season.

The output power and generation marginally differ in Chameliya, Modi Khola, Trishuli and Panauti hydropower plants than others. Thus, to investigate the reasons for this phenomenon in power plants, we have gone for various secondary and primary survey data.

Then, we assigned 1 for poor performance, 3 for satisfactory performance and 5 for good performance of installed components in these five plants. Thus, the performance ratings of 1, 3 and 5 assigned for the major electromechanical, hydromechanical and electrical components for each of the hydropower sites having a difference in generation output are illustrated in Figure 4 .

Plot of equipment performance status for the respective hydroelectric plant.

From Figure 3 , we have observed that there are great discrepancies between installed capacity and output obtained in four hydropower plants—Trishuli, Chameliya, Panauti and Modi Khola, which have been analyzed by performance rating in electromechanical, hydromechanical and electrical components of five plants.

For performance evaluation, we selected five plants, four abovementioned plants and the other one is the Puwa Khola plant. Based on the performance plots of various hydroelectric equipment in the selected four plants, we observed that the performance of electromechanical equipment is relatively poor as indicated by the deeps in the graph as shown in Figure 4 . The condition of the bearing, mechanical governor, turbine and some generators has a poor performance rating in the plants having detailed study. The graph of the performance ratings for this plant shows that the sites having a poor rating in mechanical components have much less generation in the months than the sites having a satisfactory and good rating. Thus, to be clearer and more reliable in our results, we further plotted the annual energy generation along with the target/design energy of each power plant. The annual energy generation data for all the sites except the Puwa Khola plants are less than the target/design energy data, having an overall satisfactory performance rating of the electromechanical, mechanical and electrical components.

The annual energy generation versus target/design energy graph, months for all five plants, is illustrated in Figures 5a–e .

(a) Annual generated energy and design/target energy of the Trishuli hydropower plant [ 18 [ , . (b) Annual generated energy and design/target energy of the Chameliya hydropower plant [ 18 [ , . (c) Annual generated energy and design/target energy of the Modi Khola hydropower plant [ 18 [ , . (d) Annual generated energy and design/target energy of the Panauti hydropower plant [ 18 [ , . (e) Annual generated energy and design/target energy of the Puwa Khola hydropower plant [ 18 [ .

The three fiscal years' (FY) data of design generation versus actual energy generation have also been analyzed for the plants and have similar patterns of low actual generation consistently. The three FYs' data are illustrated in Figure 6 .

Actual generation in three FY data versus design generation of the plants [ 18 [ .

Similarly, for further analysis of the plant's status, graphs have been plotted from the available data of annual loss percentages, generation percentage with respect to the target and plant factor. The plotted data for the five plants give additional support to the previous results, with less percentage loss in the Puwa Khola site and higher one in the Trishuli site. The annual generation with respect to the target value and plant factor is high for the Puwa Khola site and low for the Panauti site. The plotted graphs of percentage loss and annual generation with respect to target and plant factors are illustrated in Figure 7 .

Power plants losses, generation to target and plant factor [ 18 [ .

The study based on a questionnaire survey and observed data along with secondary information presents the status of SHPs in Nepal. The data of the 12 plants surveyed show that 33.33% of them have regular issues, and these issues are basically from solving through preventive maintenance to major maintenance types. The major problems found in four plants in addition to one good-condition plant have been studied in detail for the representation of the problems. It is clear from the generation to the targeted and plant factor curve of five plants taken for a detailed study that there are also other factors for the decrease in annual generation besides annual flow. The plant station losses clear the difference in design/targeted and generated value, but the loss curve does not clear the weightage of losses either due to component damages or annual flow.

From Figures 5a–e , it is observed that there is more deviation in generated energy from target/design energy in Trishuli, Chameliya, Panauti and Modi Khola hydroelectric power plants compared with the Puwa Khola hydropower plant. Obviously, the months of dry seasons are responsible for low generation due to low water flow, which is even clear from the existing literature [ 19 ]. But still, there are other factors responsible for low annual generation other than the low flow as observed from primary data. It has been drawn from findings that irregular maintenance, high cost for skilled manpower and poor operation strategies leading to mechanical wear are the major leading factors of losses. Figure 2 further supports the findings that the plant delays in major maintenance would be reflected in their performance than those in a few months. Delayed in major maintenance of Chameliya and Panauti, accumulation of a large number of issues, and thus decreases in a generation have been observed than the other plants. They ultimately cause huge losses throughout the years. Figure 6 shows the consistently lower actual energy generation in three FY than design generation in the four plants, further representing continued reflecting and recurring problems every year.

Figure 7 shows the results that the performance indices are good for the Puwa Khola plant and below satisfactory in Panauti, Trishuli and Chameliya plants. The percentage loss, plant factor, capacity factor and performance factor results conclude the findings in them.

Chameliya plant of 30 MW, which has frequent problems in the shaft and bearing wear, causing the vibration in the system, causes an annual average generation of 10 MW from the operation date. Panauti plant, which is the oldest power plant, has been designed for three units of 2.4 MW, but the design flow is for two units that only have an annual average power of 1.5 MW. It has problems in some design aspects, mainly in the mechanical parts. Similarly, the Trishuli plant, which is also one of the oldest plants of 24 MW in the northern part of Nepal, is suffering from continuous debris and sediment making and lowering power output, and the components installed in it are older, thus having frequent problems with turbine and the governor system. The previous studies also support the operational issue in plants either due to sediment erosion in the turbine and its parts or mechanical losses like leakages, vibration, and cavitations, which are the major problems in the hydropower of Nepal [ 20 ]. The reduction in efficiency and increase in operational and maintenance cost for the hydropower are mainly associated with degradation of turbines and their components due to sediment erosion [ 21 ]. Although the problems of sediment erosion on turbines and their components are found to be challenging, the latest development of coating technique has mitigated frequent maintenance issues in them. However, thermal spray technique is considered to be one of the latest advanced methods that mitigate the erosion issue, but it also decreases the efficiency due to surface roughness on them according to IEC 62364. Hence, real-time monitoring in the hydropower system before and after overhauls is always the major factor that results in enhancing the efficiency in hydropower machinery and proper operation of hydraulic systems [ 22 ].

Similarly, findings reading the effectiveness of plants having Pelton unit over Francis, one can be observed from the study. Skilled manpower from various countries has also been deployed for serious issues in some of the sites, clearing the insufficient skilled labor and skill knowledge regarding the operation and maintenance of the system. Import of skilled manpower, import of knowledge and low generation are connected with financial loss and high payback periods. Even SHPs are challenging source of energy for developing countries like Central Asia in terms of improving the levelized cost of energy, enhancing equipment efficiency and lifetime and increasing yearly power output [ 23 ].

Many hydropower plants in the developing and developed countries of Europe and North America have planned to rehabilitate by replacing old runners and other mechanical components to enhance the efficiency, durability and reliability of the system [ 24 ]. Even countries that mainly depend on hydropower as the primary electricity generation are generally South Asian and Central Asian countries, and the main issues in these countries are technical for its development. The issue in technical parts makes the generation and operation cost of electricity higher than in other parts of world.

Hence, both the least developed and developing countries other than South Asia and Central Asia can also have future benefits with the study, focusing on preventive and scheduled maintenance strategy, periodical major maintenance and the use of enhanced, efficient hydraulic technologies to address similar issues in mechanical, electromechanical and electrical components of hydropower plants.

The research study of 2.4–30 MW plants in Nepal with primary and secondary data gives the finding that most of the plants that are comparably lower in size have lower generation than the design, and that is not only due to the lower flow in the dry season but also due to the fact that the actual problems are in the maintenance and operation strategies in these plants. The surveyed and observed data of all 12 plants give interesting figures for performance ratings of electromechanical, mechanical and electrical components based on MCDA methods. Among all 12 plants, it is observed from the data that the performance of the Trishuli, Chameliya, Panauti and Modi Khola is comparatively low with respect to that of Puwa Khola, which has a good annual generation above the targeted value. Though, the design generation for each month is different for various plants and so is the generation, but the main reason for losses in these plants is not only due to the design parameters and design flow but also the major mechanical problems in them, which are due to debris, sediments, or lack of operation and maintenance. The major problematic shutdown in these plants is the issue of mechanical component failure, and the plants that have delayed major maintenance show a lower generation throughout the years.

Besides this, the article also focuses on the issue of insufficient knowledge and skilled manpower within the country for such systems' operation and maintenance. The huge loss in revenue through the low generation and high cost of foreign manpower caused the plant costs to be high, and even the payback periods for investors are high.

Hence, it is concluded in this article that the ROR-type scheme in Nepal is not only the reason for low generation in the dry season. The mechanical components (turbine, governor, breaker and bearings) are the critical factors in the hydroelectric performance of these plants, and the equipment needs detailed investigation and analysis. In addition, these hydropower plants are situated from eastern Nepal to western Nepal. Thus, observation and analysis of these hydropower plants certainly give the representation of the hydropower plants' condition in Nepal. Regular preventive maintenance and regular major maintenance are the prime necessity in the power plants of a country like ours where there is huge sediment flow and a chance of large debris in the wet season affecting the moving components. The study also shows the problem found in the plants having Francis unit rather than the Pelton one. Although there are only two Pelton systems, Radhe and Puwa Khola plants have good generation value and performance indices than the others in the survey, which also verifies and supports the common practices. Obviously, for the reliability of the system, energy security and safe running of plant maintenance strategy, technical audit, real-time monitoring, national standards and guidelines development could be the suggestions for the developers of Nepal.

Furthermore, a detailed study of the plants is necessary for the performance analysis of mechanical components, which seem to be the main cause of annual loss in generation and major problematic shutdown. Each plant needs a real-time monitoring system for further investigation to have more information on the cause and consequences.

Innovation and digitalization in the modern world have made much improvement in preventive measures and the effective operation of SHP. The artificial intelligence-based monitoring system, automatic flaw detection, remote operation and cyber security in the system are some of the examples applied in modern SHP. These types of systems induce effective operation and automation in SHP as existing in developed countries. Even the rehabilitation of old plants with such mechanization and innovative systems in those countries could be a learning lesson and future recommendation for developing countries like ours.

The authors would like to thank University Grants Commission, Nepal, for providing financial support as a fellowship for the research. Similarly, the authors would also like to thank the Nepal Academy of Science and Technology for providing laboratory and equipment facilities for the study. The authors also acknowledge various power stations of the Independent Power Producer (IPP) and Nepal Electricity Authority (NEA) for providing the necessary information during the survey. Finally, sincere gratitude is given to the Department of Mechanical and Aerospace Engineering, Pulchowk Campus, for providing workspace.

International Hydropower Association (IHA) . 2021 Hydropower Status Report . IHA , 2021 .

Google Scholar

Google Preview

IEA , World Energy Outlook 2019 , International Energy Agency (IEA) , November 2019 . https://www.iea.org/reports/world-energy-outlook-2020 (12 August 2021, date last accessed).

Heng L , Xianlai W , Xiaobo H , Krēmere E . World Small Hydropower Development Report 2019 . United Nations Industrial Development Organization , 2019 .

NEA . A Year in Review—Fiscal Year-2019/2020 . Nepal Electricity Authority , 2020 .

Department of Electricity Development (DOED) . Power Plants: Hydro . 11 August 2021 . http://doed.gov.np/license/54 (21 August 2021, date last accessed).

MNRE . Evaluation of Small Hydro Power (SHP) Programme of MNRE . Ministry of New & Renewable Energy (MNRE) , 2017 .

Bhuttoa AW , Bazmib AA , Zahedib G . Greener energy: issues and challenges for Pakistan-hydel power prospective . Renew Sustain Energ Rev 2012 ; 16 : 2732 – 46 .

Ministry of Water Resources (MoWR) . Small Hydropower Development and Management in China . MoWR , 2016 .

Shrestha HM . Exploitable potential, theoretical potential, technical potential . J Water Energy Environ 2016 ; 19 : 1 – 5 .

Verma HK , Kumar A . 2007 . Performance testing and evaluation of small hydropower plants. In International Conference on Small Hydropower . Sri Lanka .

IEC 61116 . International Standard: Electromechanical Equipment Guide for Small Hydroelectric Installations . International Electromechanical Commission , 1992 .

Department of Electricity Development (DOED) , Guidelines for Operation and Maintenance for Hydropower Stations, Substations and Transmission Lines , Department of Electricity Development, Ministry of Energy, Government of Nepal , 2017 .

Adhikari D . Hydropower development in Nepal . Econ Rev 2023 ; 18 : 70 – 94 .

Agrawal S , Pandey R . Current status of small/micro hydropower in Nepal: a case study of Giringdi SHP . J Inst Engineering 2020 ; 15 : 21 – 7 .

Bashyal M , Poudel L . Performance analysis and rehabilitation prospective of aged Small Hydropower Plant – A Case Study of Fewa Hydropower Plant (1 MW). In Bashyal M, Poudel L (ed.) Proceedings of 10th IOE Graduate Conference . Pulchowk Campus, Institute of Engineering , Lalitpur, Nepal , 2021 , 161 – 69 .

Joshi S , Shrestha R . Performance evaluation of Runoff River type hydropower plants operating in Nepal: a case study of Nepal electricity authority . J Inst Engineering 2014 ; 10 : 104 – 20 .

Bohara S , Shrestha R . Performance Evaluation of Hydro Power Plants of Nepal Greater Than 10 MW Using Data Envelopment Analysis. In Bohara S, Shrestha R (ed.) Proceedings of IOE Graduate Conference . Pulchowk Campus, Institute of Engineering , Lalitpur, Nepal , 2017 .

NEA . Dispatch Centre Data Record 2020 . NEA , 2020 .

Singh R , Bhattarai N , Prajapati A , Shakya SRS . July 2022 . Impact of variation in climatic parameters on hydropower generation: a case of hydropower project in Nepal. In Heliyon , Vol. 8 , pp. 4 – 13 .

Sapkota P , Chitrakar S , Neopane HP , Thapa B . Problem identification and condition monitoring status of Nepalese power plants . Earth Environ Sci 2022 ; 1079 : 3 – 5 .

Gantawa R , Tamrakar NK . Analysis of sediment abrasion potential in hydro turbines by studying fine sediments from the Budhi Gandaki-Trishuli River of Nepal . J Nepal Geol Soc 2019 ; 58 : 29 – 38 .

Feng D , Wang Z , Ma P , Wang W . Analysis and application of hydropower real-time performance calculation . Energy Power Eng July 2013 ; 05 : 63 – 7 .

Ulugbek A , Nilufar A . Sustainable small-scale hydropower solutions in Central Asian countries for local and cross-border energy/water supply . Renew Sust Energ Rev 2022 ; 167 : 3 – 12 .

GmbH AH . Modernization and Renovation of Hydro Power Plants—New Life for Hydro Assets . ANDRITZ GROUP , 2019 .

Email alerts

Citing articles via, affiliations.

• Online ISSN 1748-1325
• Print ISSN 1748-1317
• Copyright © 2024 Oxford University Press
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Download Free PDF

Harnessing hydropower: Literature Review

Free related PDFs Related papers

This study overviews the status of the power supply; implications of the inadequate power supply; and the significance of hydropower in the socioeconomic wellbeing of Sub-Saharan Africa (SSA). This study noted that despite the large presence of energy potentials across the entire region, the power supply is grossly inadequate. Currently, the world's highest population without access to electricity live in SSA and the number, which was 585 million in 2009 is expected to increase to 645 million in 2030. The supply of clean, affordable and adequate power in the region is compounded by the global energy trends, described as energy trilemma by the world energy council. These attributes are anchored in three pillars-energy equity, energy security and environmental sustainability. This article sees hydropower technology, which has been revolutionised over the years into different categories, as a vital modern energy source for clean power generation. The hydropower technologies discussed are large hydropower, small hydropower (SHP) and pumped storage hydropower. Hydropower provides clean, relatively cheap electricity, reliable and sustainable power supply. The study identifies SHP as a system that satisfies the modern energy attributes of low CO 2 emissions and environmentally friendly scheme, suitable for standalone and rural electrification.

Energy &amp; Environment, 2017

Flowing water has hydraulic energy that can be transformed into electrical energy, sub-Saharan Africa has an abundance of hydro resources that are untapped. In this study, various barriers limiting the use of small hydropower to tap the abundant hydro potentials for power generation are discussed. These barriers include insufficient fund; lack of adequate manufacturing infrastructure; lack of adequate power generation and distribution policies; inaccurate hydrological data; insufficient human and power infrastructure capacities; and inadequate domestic and regional participation in design and manufacture of small hydropower component devices and systems. This study sees hydro as a cleaner energy source and small hydropower as the best power system for rural and remote areas and for stand-alone electrification. For power sustainability in the region, public–private partnership, domestication of small hydropower technologies and less reliance on foreign technologies and international ...

Climatic Change

Scholarly Research Journal for Humanity Science & English Language, , 2023

The concept of living in harmony with nature is as old as humankind. However, a modern conception emerged in the term 'sustainable development' with the rise of green movements in the late 1960s and early 1970s. Sustainable development can be defined as an approach to the economic development of a country without compromising with the quality of the environment for future generations. This definition captured the spirit of the times whereby government, business, and civil society have strived to make development sustainable. Hydropower accounts for 16% of all global electricity production and it is one of the world's most widely used renewable, low-carbon energy resources. It plays an important role in enabling communities around the world to meet their power and water needs. In some regions the pace of hydropower growth has been rapid but with little guidance to ensure development is sustainable. However, some of the most promising and influential initiatives to improve development, such as the Hydropower Sustainability Assessment Protocol, have been driven by the hydropower sector itself. This paper addresses the progress that hydropower has made in the context of sustainable development over the past 15 years. The concept of sustainable development does imply limits, not absolute limits but limitations imposed by the present state of technology and social organizations on environmental resources and by the ability of the biosphere to absorb the effects of human activities. But technology and social organization can both be managed and improved to make way for a new era of economic growth.

IOP Conference Series: Earth and Environmental Science, 2018

Sub-Saharan Africa lags behind all other regions of the world in terms of people’s access to electricity. The World Bank has asserted that promoting the development of hydropower would lower the generation costs of electricity, reduce carbon emissions and help to insulate countries in sub-Saharan Africa from increases in the price of fossil fuels. However, hydropower makes up just under 20% of the installed generating capacity. Despite a considerable exploitable hydropower potential of about 1,750 TWh/year, and the opportunity to ensure energy security through hydropower generation, only 5% of the potential is currently tapped. Based on planned schemes, the hydropower generating capacity in Africa could almost quadruple over the next 20–30 years. This policy brief focuses on large hydropower infrastructure in sub-Saharan Africa. It investigates the climate change risks and the use of climate services in decision-making and makes recommendations for actions to enhance the resilience of hydropower schemes. It summarises a more comprehensive paper prepared to support the scoping phase of the Future Climate for Africa (FCFA) programme for the hydropower sector.

Zanzibar Water Conference, 2022

Tanzania is hugely dependent on hydro power generation (HPG), despite the ever introduction of new technologies, changing climate, increasing demand, and technological advances. This dependency is more than 30% of all current grid power, and as a result, occurrence of drought jeopardizes the electricity supply to consumers, with very negative consequences. The power utility, Tanzania Electric Supply Company (TANESCO) is striving to explore newer power sources, which are clean energy (HPG, solar, biomass, etc.), and others the conventional fossil energy (diesel, natural gas, heavy fuel oil, etc.) to attain an appreciable energy mix. However, this energy mix still leaves the national grid hugely dependent on HPG. Therefore, this paper undertakes to study current trends towards increasing exploitation of HPG, the impacts of dependency on HPG, the challenges facing this implementation, and many other factors. The study will employ extensive literature review of current documentation that deals with power sector in Tanzania, develop a hypothetical bestcase scenario, collection of secondary data, statistical analysis of the data, and comparisons to that hypothetical best-case scenario. The study will elucidate how to leverage recent technological advances, to efficiently exploit the HPG and thus bring about an optimum energy mix for the national grid. The results from this study could inform energy researchers, policy makers, power sector practitioners, and other stakeholders to make informed decisions on water sources utilizations for sustainability and efficiency.

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

Energy Policy, 2002

International Journal of Water Resources Development, 2015

International Journal of Water Resources Development, 2019

Hydro Nepal: Journal of Water, Energy and Environment, 2015

INTERNATIONAL JOURNAL OF WATER RESOURCES DEVELOPMENT, 2019

Journal of Renewable Energy, 2018

International Journal of Water Resoruces Development, 2021

International Journal of Renewable Energy Technology, 2011

Rwanda Journal, 2012

International Journal of Energy Economics and Policy, 2017

Resources, 2017

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

• < Previous

Home > Student Works > 74

Student Works

Literature review: hydropower and iceland's environment.

Olivia Villamagna , Embry-Riddle Aeronautical University Follow

Submitting Campus

Daytona Beach

Student Status

Undergraduate

Study Abroad

Advisor Name

Dr. Kelly Whealan George

Second Advisor Name

Wesley Lewis

Abstract/Description

This paper seeks to answer the question: To what extent do hydropower plants affect the surrounding environment? Through a literature review and personal accounts found on blogs and website articles, there were many conclusions that came from this research. A review of the literature indicated that use of hydropower influences the ecology around the plant. The power plant’s redirection of the river's water flow and reservoir submergence cause many problems for the surrounding environments. Hydropower plants can change the landscape due to the fact that the water they use is no longer providing the right nutrients to the previously flourishing landscape as a result of the rerouting of rivers. Specifically, the hydroelectric power plants affect soil sediment around the plants, destroys habitats, impacts certain fish migration patterns, and ruins water quality. The plants were also found to uproot flora, change the sediment content and cause erosion, disrupt nesting grounds, and change whole migration patterns of some birds. These factors all contribute to the negative effects of hydropower on the nearby ecosystems. Research has identified that the change caused by the redirected and distributed water flow affects animals and vegetation in the adjacent areas and, eventually, leads to the destruction of habitats. The researcher briefly researched how this could affect eco-tourism, which was found to be quickly growing and a huge part of Iceland's economy. These effects also play a negative role in Iceland's nature tourism industry, as it is changing much of the wildlife sought out by these tourists.

It must be stated above all that plants do have a great negative effect on the environment and surrounding ecology.

How can this problem be mitigated? A few suggestions made were to move the plants to more isolated countries or implement nature preservation programs directly correlated to the plants. There have been few speculations on how to mitigate the effects of the power plants on the animals that reside in the water areas around the plant. One of the suggestion is to make “small adjustments to river flow regimes might help to restore river ecosystems” (Poff & Schmidt, 2016).

Further research also suggested since not many studies were conducted on this topic, especially ones that were originally written in English.

Document Type

Undergraduate Research

Scholarly Commons Citation

Villamagna, O. (2018). Literature Review: Hydropower and Iceland's Environment. , (). Retrieved from https://commons.erau.edu/student-works/74

Since June 14, 2018

Included in

Environmental Studies Commons

Advanced Search

• Notify me via email or RSS
• Collections
• Disciplines

Author Corner

• Submission Guidelines
• Conference/Event Hosting
• Journal or Event Request Form
• Scholarly Commons Help

Home | About | FAQ | My Account | Accessibility Statement

Privacy Copyright

Advertisement

A study on solutions and problems of hydroelectric power plants in the operation

• Original Article
• Published: 29 May 2022
• Volume 8 , article number  90 , ( 2022 )

Cite this article

• Cengiz Koç   ORCID: orcid.org/0000-0001-7310-073X 1  

489 Accesses

4 Citations

Explore all metrics

Hydroelectricity, which is defined as green energy, is a type of renewable energy. Despite the advantages of hydroelectric power plants, there are also negative effects caused by them. While power plants do provide advantages such as flood reduction, disaster management, mitigation of the effects of global warming and climate change; they can also lead to some unwanted environmental effects at the local and regional levels. In this study, the generation capacities of hydroelectric power plants that were built and commissioned by a Public Institution or by the Private Sector in the Büyük Menderes and Western Mediterranean basins were evaluated, for the years of 2010–2019. In the years examined, the project energy production value was compared with the maximum and minimum energy production levels of the power plants. The average maximum and average minimum production rates, which were calculated by proportioning the maximum and minimum energy production values to the project production value, was 93.33% and 56.04% for the West Mediterranean basin, respectively; and it was 92.97% and 43.09% for the Büyük Menderes basin. The average production rate for the Western Mediterranean basin was 69.8%, and for the Büyük Menderes basin it was 68%. It has been shown that there were significant differences between the annual energy production of the power plants and the amount of production realized due to the changes in the water resources of the studied basins, as well as due to insufficient data and careless planning. In addition, the production and environmental problems encountered during the operation phase have been revealed and suggestions have been recommended for the resolution of these problems in this study.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Hydropower potentials in Bangladesh in context of current exploitation of energy sources: a comprehensive review

Hydropower Potential in India: A Review

Hydropower Plants

Abbasi T, Abbasi SA (2011a) Small hydro and the environmental implications of its extensive utilization. Renew Sust Energ Rev 15(4):2134–2143

Article   Google Scholar  

Abbasi T, Abbasi SA (2011b) Small hydro and the environmental implications of its extensive utilization. Renew Sustain Energy Rev 15:2134–2143

Anderson D, Moggridge H, Warren P, Shucksmith J (2015) The impacts of ‘run-of-river’ hydropower on the physical and ecological condition of rivers. Water Environ J 29:268–276

Avcı I (2008) Goals, expectations and realities in the practice. New global perspectives in the assessment and management of hydroelectric potential and water, a strategic resource in Turkey. Union of Chambers of Turkish Engineers and Architects, Journal of Measure, January 42–42. (in Turkish)

Bayazıt Y, Bakış R, Koç C (2017) An investigation of small scale hydropower plants using the geographic information system. Renew Sustain Energy Rev 67:289–294

Bayazıt Y, Bakış R, Koç C (2021) A study on transformation of multi-purpose dams into pumped storage hydroelectric power plants by using GIS model. Int J Green Energy 18(3):308–318

Bunn SE, Arthington AH (2002) Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environ Manag 30:492–507

Cejka T, Beracko P, Matecny I (2019) The impact of the Gabcikovo hydroelectric power barrier on the Danube floodplain environment-the results of long-term monitoring of land snail fauna. Environ Monit Assess 192:30

Couto TBA, Olden JD (2018) Global proliferation of small hydropower plants—science and policy. Front Ecol Environ 16:91–100

Dogmus ÖC, Nielsen JO (2020) The on-paper hydropower boom: a case study of corruption in the hydropower sector in Bosnia and Herzegovina. Ecol Econ 172:106630

DSI (2019) Büyük Menderes ve Batı Akdeniz Havzalarında İşletilen Hidroelektrik Santral Kayıtları, Tarım ve Orman Bakanlığı, DSİ Genel Müdürlüğü, DSİ 21. Bölge Müdürlüğü, İşletme ve Bakım Şube Müdürlüğü, Aydın

DSI (2020) http://www.dsi.gov.tr/english/service/enerjie.htm . Accessed 20 Apr 2020

EC (European Commission) (2000) Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the field of water policy. Off J Eur Communities L 327:1–73

Google Scholar  

EC (European Commission) (2018) Commission E. Guidance document on the requirements for hydropower in relation to EU nature legislation. In: Environment, editor. Brussels, Belgium, p 1–83

Erlewein A (2013) Disappearing rivers—the limits of environmental assessment for hydropower in India. Environ Impact Assess Rev 43:135–143

ESHA (2010) Hydropower and environment, technical and operational procedures to better integrate small hydropower plants in the environment. http://www.esha.be . Accessed Oct 2010

EÜAŞ (2008) Özel Sektörün Hidrolik Santral Yapma A¸samaları. Elektrik Üretim Anonim Sirketi. http://www.euas.gov.tr/ . Accessed 12 May 2020

EUROSTAT (2019) Energy statistics introduced. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Energy_statistics_introduced#Introduction . Accessed 1 May 2020

ICOLD (2000) Open letter to WCD Chair, 30 November 2000. International Commission on Large Dams

IHA (International Hydropower Association) (2019) Hydropower downstream flow regimes. International Hydropower Association, London, p 73

Kallis G, Butler D (2001) The EU water framework directive: measures and implications. Water Policy 3:125–142

Kelly S (2019) Megawatts mask impacts: small hydropower and knowledge politics in the Puelwillimapu, Southern Chile. Energy Res Soc Sci 54:224–235

Kelly-Richards S, Silber-Coats N, Crootof A, Tecklin D, Bauer C (2017) Governing the transition to renewable energy: a review of impacts and policy issues in the small hydropower boom. Energy Policy 101:251–264

Kentel E, Alp E (2013) Hydropower in Turkey: economical, social and environmental aspects and legal challenges. Environ Sci Policy 31:34–43

Koç C (2012) Problems and solutions related to hydroelectric power plants constructed on the Buyuk Menderes and the West Mediterranean basin. Energy Sources Part A Recov Util Environ Effects 34(15):1416–1425

Koç C (2014) A study on the development of hydropower potential in Turkey. Renew Sustain Energy Rev 39:498–508

Koç C (2017) A study on importance and role of irrigation and hydropower plant operation in integrated river basin management. Comput Water Energy Environ Eng 6:1–10

Koç C (2018) A study on operation problems of hydropower plants integrated with irrigation schemes operated in Turkey. Int J Green Energy 15(2):129–135

Koç C (2020a) A study on environmental and social impacts of mini hydro power plants. Eu J Sci Technol 20:35–41

Koç C (2020b) A study on operation of hydroelectric power plants constructed on irrigation canal. Eur J Sci Technol 19:138–144

Koç C, Kosif K, Kızıltepe S, Özdemir K (2010) Büyük Menderes ve Batı Akdeniz Havzalarında İşletmede olan Taşkın Tesislerine Yapılan Müdahaleler Üzerine Bir Çalışma. II. Ulusal Taşkın Sempozyumu 22–24 Mart, Afyonkarahisar, 71–79

Koralay N, Kara O, Kezik U (2018) Effects of run-of-the-river hydropower plants on the surface water quality in the Solakli stream watershed, Northeastern Turkey. Water Environ J 32:412–421

Laguna M, Upadhyay D, Taylor S (2006) Flowing to the East: Small Hydro in developing countries, Renewable Energy World, pp 126–131

Lange K, Meier P, Trautwein C, Schmid M, Robinson CT, Weber C et al (2018) Basin-scale effects of small hydropower on biodiversity dynamics. Front Ecol Environ 16:397–404

Larinier M (2008) Fish passage experience at small-scale hydro-electric power plants in France. Hydrobiologia 609:97–108

Mbaka JG, Wanjiru M (2015) A global review of the downstream effects of small impoundments on stream habitat conditions and macroinvertebrates. Environ Rev 23:257–262

McManamay RA, Samu N, Kao SC, Bevelhimer MS, Hetrick SC (2015) A multi-scale spatial approach to address environmental effects of small hydropower development. Environ Manag 55:217–243

Nautiyal H, Goel V (2020) Sustainability assessment of hydropower projects. J Clean Prod 265:121661

Pascale G, Connors BM, Palen WJ (2017) Run-of-River hydropower and salmonids: potential effects and perspective on future research. Can J Fish Aquat Sci 74:1135–1149

Poff NL, Zimmerman JKH (2010) Ecological responses to altered flow regimes: a literature review to inform the science and management of environmental flows. Freshw Biol 55:194–205

Popescu VD, Munshaw RG, Shackelford N, Montesino Pouzols F, Dubman E, Gibeau P et al (2020) Quantifying biodiversity trade-offs in the face of widespread renewable and unconventional energy development. Sci Rep 10:7603

Premalatha M, Tabassum A, Abbasi T, Abbasi SA (2014) A critical view on the eco-friendliness of small hydroelectric installations. Sci Total Environ 481:638–643

Ptak T (2019) Towards an ethnography of small hydropower in China: rural electrification, socioeconomic development and furtive hydroscapes. Energy Res Soc Sci 48:116–130

Rex W, Foster V, Lyon K, Bucknall J, Liden R (2014) Supporting hydropower: an overview of the World Bank Group’s engagement. World Bank Group, Washington, DC

SPD (2019). Hidroenerji Raporu Yekdem’e Kayıtlı HES’lerin Üretim Verimliliği, Su Politikaları Derneği, Hidropolitik Akademi, Rapor No: 2019-2, Kavaklıdere-Ankara, s.28

Valero E (2012) Characterization of the water quality status on a stretch of River Lérez around a small hydroelectric power station. Water 4:815–834

Yuksel I (2010) As a renewable energy hydropower for sustainable development in Turkey. Renew Sustain Energy Rev 14:3213–3219

Zarfl C, Lumsdon AE, Berlekamp J, Tydecks L, Tockner K (2014) A global boom in hydropower dam construction. Aquat Sci 77:161–170

Download references

Acknowledgements

In this study, data on the hydroelectric power plants operated and constructed in the Büyük Menderes and Western Mediterranean basins were obtained from the General Directorate of State Hydraulic Works. Therefore, I would like to thank the relevant institution for its contribution and assistance to this study.

Author information

Authors and affiliations.

Department of City and Regional Planning, Muğla Sıtkı Koçman University, Muğla, Turkey

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Cengiz Koç .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Koç, C. A study on solutions and problems of hydroelectric power plants in the operation. Sustain. Water Resour. Manag. 8 , 90 (2022). https://doi.org/10.1007/s40899-022-00677-2

Download citation

Received : 30 July 2021

Accepted : 10 May 2022

Published : 29 May 2022

DOI : https://doi.org/10.1007/s40899-022-00677-2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Büyük Menderes
• Energy production rate
• Hydroelectric power plant
• Operational and environmental problems
• Western Mediterranean
• Find a journal
• Publish with us
• Track your research

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Journal Proposal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• Author Biographies
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

Floating photovoltaic plant monitoring: a review of requirements and feasible technologies.

1. Introduction

• Better average PV system efficiency due to the mitigating thermal effect resulting from the thermal capacity of the water [ 9 ];
• Indirect effect of water evaporation minimization [ 10 ];
• Shorter installation times compared to ground-based systems [ 11 ];
• Higher power density as compared to ground-based systems [ 12 ].

2. PV Floating Plants

• A large number of mooring lines (especially in the case of pure float designs).
• Site constraints.
• Varying water levels.
• Unequal load distribution.
• Array shape and size.

3. PV Floating Monitoring Issues

3.1. monitoring fpv systems for evaluating the water environment impact on energy production.

• Positioning of the PV Modules: The position of the photovoltaic (PV) modules can be affected by wave movements, which vary significantly depending on whether the system is located offshore or in freshwater basins, as well as the type and design of the anchoring system. Consequently, the modules exhibit variable positioning.
• Temperature of the PV Modules: The temperature of the PV modules is affected by their surrounding microclimate, in turn depending on the water temperature and the thermo-hygrometric conditions induced by the presence of water.
• Efficiency Degradation of the PV Modules over time. The hygrometric conditions in which the PV modules operate can impact their efficiency over time, potentially leading to a loss of performance.

3.1.1. Variable Module Positioning

3.1.2. pv module temperature, 3.1.3. loss of efficiency of pv modules over time, 3.1.4. effects of soiling on fpv, 3.1.5. monitoring via uav, 3.2. monitoring fpv systems for evaluating their impact on water ecosystem, 4. sensors for water quality monitoring, 5. technologies for autonomous water basin mapping and monitoring, 5.1. state of the art of surface and underwater robotic systems.

• ASVs (autonomous surface vehicles), also called USVs (unmanned surface vehicles), are boats controlled by an autopilot, commonly linked to a ground station through at least one radio trans-receiver (for sending telemetry data) and to a radio-controller through a radio receiver module aboard the vessel, enabling manual recovery of the ASV or failsafe functions at any time. Positions, trajectories, and all on-board data acquired aboard the vessel are available on the ground station (or directly in a control room), making it possible to set waypoints of interest and let the robot follow them automatically.
• ROVs (Remotely Operating Vehicles), due to their cost-effectiveness, excellent maneuverability and on-line acquisition capability, represent the current commercial tool for widespread use in underwater exploration. Some ROVs configurations can be equipped with an extension module, enabling the tethered cable to supply the energy required for an indefinite time due to the availability of an electrical socket on the surface.
• AUVs (Autonomous Underwater Vehicles), unlike ROVs, are characterized by the absence of a tethering cable, relying on a battery pack for power supply and off-line data acquisition capabilities. Indefinite operation requires permanent electrical recharge/docking/recovery stations. The cost of these vehicles increases with the number of sensors fitted on-board. The more automated and powerful the vehicle, the more complex the missions it can perform.

5.2. Issues Related to Robotic Systems

5.2.1. localization issues, 5.2.2. data transmission, 5.2.3. energy autonomy and environmental impact, 5.2.4. operation and maintenance, 6. a case study for an fpv autonomous monitoring system.

Click here to enlarge figure

7. Discussion

8. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

• Nijsse, F.J.M.M.; Mercure, J.F.; Ameli, N.; Larosa, F.; Kothari, S.; Rickman, J.; Vercoulen, P.; Pollitt, H. The momentum of the solar energy transition. Nat. Commun. 2023 , 14 , 6542. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Nøland, J.K.; Auxepaules, J.; Rousset, A.; Perney, B.; Falletti, G. Spatial energy density of large-scale electricity generation from power sources worldwide. Sci. Rep. 2022 , 12 , 21280. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Bolinger, M.; Bolinger, G. Land Requirements for Utility-Scale PV: An Empirical Update on Power and Energy Density. IEEE J. Photovolt. 2022 , 12 , 589–594. [ Google Scholar ] [ CrossRef ]
• Capellán-Pérez, I.; Castro, C.; Arto, I. Assessing vulnerabilities and limits in the transition to renewable energies: Land requirements under 100% solar energy scenarios. Renew. Sustain. Energy Rev. 2017 , 77 , 760–782. [ Google Scholar ] [ CrossRef ]
• Sargentis, G.-F.; Siamparina, P.; Sakki, G.-K.; Efstratiadis, A.; Chiotinis, M.; Koutsoyiannis, D. Agricultural Land or Photovoltaic Parks? The Water–Energy–Food Nexus and Land Development Perspectives in the Thessaly Plain, Greece. Sustainability 2021 , 13 , 8935. [ Google Scholar ] [ CrossRef ]
• Cagle, A.E.; Armstrong, A.; Exley, G.; Grodsky, S.M.; Macknick, J.; Sherwin, J.; Hernandez, R.R. The Land Sparing, Water Surface Use Efficiency, and Water Surface Transformation of Floating Photovoltaic Solar Energy Installations. Sustainability 2020 , 12 , 8154. [ Google Scholar ] [ CrossRef ]
• Floating PV on a Quarry Lake in Southern Germany. Available online: https://www.pv-magazine.com/2020/11/16/floating-pv-on-a-quarry-lake-in-southern-germany/ (accessed on 19 September 2024).
• Trapani, K.; Redõn Santafé, M. A review of floating photovoltaic installations: 2007–2013. Prog. Photovolt. Res. Appl. 2015 , 23 , 524–532. [ Google Scholar ] [ CrossRef ]
• Amiot, B.; Le Berre, R.; Giroux-Julien, S. Evaluation of thermal boundary conditions in floating photovoltaic systems. Prog. Photovolt. Res. Appl. 2023 , 31 , 251–268. [ Google Scholar ] [ CrossRef ]
• Bontempo Scavo, F.; Tina, G.M.; Gagliano, A.; Nižetić, S. An assessment study of evaporation rate models on a water basin with floating photovoltaic plants. Int. J. Energy Res. 2021 , 45 , 167–188. [ Google Scholar ] [ CrossRef ]
• Prefab Floating Solar for Easy Installation. Available online: https://www.pv-magazine.com/2022/06/28/prefab-floating-solar-for-easy-installation/ (accessed on 19 September 2024).
• Rosa-Clot, M. (Pisa, Italy). Private communication. 2024. [ Google Scholar ]
• Hernández-Callejo, L.; Gallardo-Saavedra, S.; Alonso-Gómez, V. A Review of Photovoltaic Systems: Design, Operation and Maintenance. Sol. Energy 2019 , 188 , 426–440. [ Google Scholar ] [ CrossRef ]
• Chen, X.; Zhou, W. Performance Evaluation of Aquavoltaics in China: Retrospect and Prospect. Renew. Sustain. Energy Rev. 2023 , 173 , 113109. [ Google Scholar ] [ CrossRef ]
• Hu, J.; Teng, K.; Li, C.; Li, X.; Wang, J.; Lund, P.D. Review of Recent Water Photovoltaics Development. Oxf. Open Energy 2023 , 2 , oiad005. [ Google Scholar ] [ CrossRef ]
• Cazzaniga, R.; Cicu, M.; Rosa-Clot, M.; Rosa-Clot, P.; Tina, G.M.; Ventura, C. Floating Photovoltaic Plants: Performance Analysis and Design Solutions. Renew. Sustain. Energy Rev. 2018 , 81 , 1730–1741. [ Google Scholar ] [ CrossRef ]
• Rosa-Clot, M.; Marco Tina, G. Chapter 7—Tracking Systems. In Floating PV Plants ; Rosa-Clot, M., Marco Tina, G., Eds.; Academic Press: Cambridge, MA, USA, 2020; pp. 79–87. [ Google Scholar ] [ CrossRef ]
• Shi, W.; Yan, C.; Ren, Z.; Yuan, Z.; Liu, Y.; Zheng, S.; Li, X.; Han, X. Review on the Development of Marine Floating Photovoltaic Systems. Ocean Eng. 2023 , 286 , 115560. [ Google Scholar ] [ CrossRef ]
• Wu, S.; Jiang, N.; Zhang, S.; Zhang, P.; Zhao, P.; Liu, Y.; Wang, Y. Discussion on the Development of Offshore Floating Photovoltaic Plants, Emphasizing Marine Environmental Protection. Front. Mar. Sci. 2024 , 11 , 1336783. [ Google Scholar ] [ CrossRef ]
• Claus, R.; López, M. Key Issues in the Design of Floating Photovoltaic Structures for the Marine Environment. Renew. Sustain. Energy Rev. 2022 , 164 , 112502. [ Google Scholar ] [ CrossRef ]
• World Bank Group; ESMAP; SERIS. Where Sun Meets Water: Floating Solar Market Report ; World Bank: Washington, DC, USA, 2019. Available online: http://documents.worldbank.org/curated/en/670101560451219695/Floating-Solar-Market-Report (accessed on 19 September 2024).
• Sobolewski, K.; Sobieska, E. Lightning Protection of Floating Photovoltaic Power Plants—Simulation Analysis of Sample Solutions. Energies 2023 , 16 , 4222. [ Google Scholar ] [ CrossRef ]
• Ghosh, A. A Comprehensive Review of Water Based PV: Flotavoltaics, under Water, Offshore & Canal Top. Ocean Eng. 2023 , 281 , 115044. [ Google Scholar ] [ CrossRef ]
• Gorjian, S.; Sharon, H.; Ebadi, H.; Kant, K.; Scavo, F.B.; Tina, G.M. Recent Technical Advancements, Economics and Environmental Impacts of Floating Photovoltaic Solar Energy Conversion Systems. J. Clean. Prod. 2021 , 278 , 124285. [ Google Scholar ] [ CrossRef ]
• Acharya, M.; Devraj, S. Floating Solar Photovoltaic (FSPV): A Third Pillar to Solar PV Sector? TERI Discussion Paper; Output of the ETC India Project (The Energy and Resources Institute): New Delhi, India, 2019. [ Google Scholar ]
• Mayville, P.; Patil, N.V.; Pearce, J.M. Distributed Manufacturing of after Market Flexible Floating Photovoltaic Modules. Sustain. Energy Technol. Assess. 2020 , 42 , 100830. [ Google Scholar ] [ CrossRef ]
• Trapani, K.; Millar, D.L. The Thin Film Flexible Floating PV (T3F-PV) Array: The Concept and Development of the Prototype. Renew. Energy 2014 , 71 , 43–50. [ Google Scholar ] [ CrossRef ]
• Kanotra, R.; Shankar, R. Floating Solar Photovoltaic Mooring System Design and Analysis. In Proceedings of the OCEANS 2022—Chennai, Chennai, India, 21–24 February 2022; pp. 1–9. [ Google Scholar ] [ CrossRef ]
• Rosa-Clot, M.; Tina, G.M. Submerged and Floating Photovoltaic Systems. Rosa-Clot, M., Tina, G.M., Eds.; Academic Press: Cambridge, MA, USA, 2018; Chapter 8; pp. 185–212. [ Google Scholar ] [ CrossRef ]
• DNV. Design, Development and Operation of Floating Solar Photovoltaic Systems. DNV-RP-0584, March 2021; amended October 2021. Available online: https://brandcentral.dnv.com/fr/gallery/10651/others/0338546af264473e8481ba6ea78daf0f_hi.pdf (accessed on 19 September 2024).
• Alcañiz, A.; Monaco, N.; Isabella, O.; Ziar, H. Offshore Floating PV–DC and AC Yield Analysis Considering Wave Effects. Energy Convers. Manag. 2024 , 300 , 117897. [ Google Scholar ] [ CrossRef ]
• Bugeja, R.; Mule’ Stagno, L.; Dexarcis, L. An Offshore Solar Irradiance Calculator (OSIC) Applied to Photovoltaic Tracking Systems. Energies 2023 , 16 , 3735. [ Google Scholar ] [ CrossRef ]
• Nurhakim, A.; Effendi, M.R.; Saputra, H.M.; Mardiati, R.; Priatna, T.; Ismail, N. A Novel Approach to Calculating Yaw Angles Using an Accelerometer Sensor. In Proceedings of the 2019 IEEE 5th International Conference on Wireless and Telematics (ICWT), Yogyakarta, Indonesia, 25–26 July 2019; pp. 1–4. [ Google Scholar ] [ CrossRef ]
• Delacroix, S.; Bourdier, S.; Soulard, T.; Elzaabalawy, H.; Vasilenko, P. Experimental Modelling of a Floating Solar Power Plant Array under Wave Forcing. Energies 2023 , 16 , 5198. [ Google Scholar ] [ CrossRef ]
• Rossi, G.B.; Cannata, A.; Iengo, A.; Migliaccio, M.; Nardone, G.; Piscopo, V.; Zambianchi, E. Measurement of Sea Waves. Sensors 2021 , 22 , 78. [ Google Scholar ] [ CrossRef ]
• Choi, Y.-K.; Lee, N.-H.; Lee, A.-K.; Kim, K.-J. A Study on Major Design Elements of Tracking-Type Floating Photovoltaic Systems. SGCE 2014 , 3 , 70–74. [ Google Scholar ] [ CrossRef ]
• Micheli, L. The Temperature of Floating Photovoltaics: Case Studies, Models and Recent Findings. Sol. Energy 2022 , 242 , 234–245. [ Google Scholar ] [ CrossRef ]
• Santos, L.D.O.; De Carvalho, P.C.M.; Filho, C.D.O.C. Photovoltaic Cell Operating Temperature Models: A Review of Correlations and Parameters. IEEE J. Photovolt. 2022 , 12 , 179–190. [ Google Scholar ] [ CrossRef ]
• Peters, I.M.; Nobre, A.M. Deciphering the Thermal Behavior of Floating Photovoltaic Installations. Sol. Energy Adv. 2022 , 2 , 100007. [ Google Scholar ] [ CrossRef ]
• Tina, G.M.; Bontempo Scavo, F.; Merlo, L.; Bizzarri, F. Analysis of Water Environment on the Performances of Floating Photovoltaic Plants. Renew. Energy 2021 , 175 , 281–295. [ Google Scholar ] [ CrossRef ]
• Lindholm, D.; Selj, J.; Kjeldstad, T.; Fjær, H.; Nysted, V. CFD Modelling to Derive U-Values for Floating PV Technologies with Large Water Footprint. Sol. Energy 2022 , 238 , 238–247. [ Google Scholar ] [ CrossRef ]
• Hamdi, R.T.A.; Hafad, S.A.; Kazem, H.A.; Chaichan, M.T. Humidity Impact on Photovoltaic Cells Performance: A Review. Int. J. Recent Eng. Res. Dev. 2018 , 3 , 27–37. [ Google Scholar ]
• Luo, W.; Isukapalli, S.N.; Vinayagam, L.; Ting, S.A.; Pravettoni, M.; Reindl, T.; Kumar, A. Performance Loss Rates of Floating Photovoltaic Installations in the Tropics. Sol. Energy 2021 , 219 , 58–64. [ Google Scholar ] [ CrossRef ]
• Shaju, A.; Chacko, R. Soiling of Photovoltaic Modules—Review. IOP Conf. Ser. Mater. Sci. Eng. 2018 , 396 , 012050. [ Google Scholar ] [ CrossRef ]
• Francia, D.F.; De Vito, S.; Fattoruso, G.; Matano, A. Energy transition: An analysis of agrivoltaic utilities suitability in terms of Levelized Cost of Electric Energy. In Proceedings of the Global Energy Transition Toward Decarbonization: A Multi-Scalar Perspective and Transformation, Milan, Italy, 24–27 July 2023. [ Google Scholar ]
• Willers, G.; Naumann, V.; Holzlohner, R.; Gottschalg, R.; Ilse, K. Analysis of Threshold Conditions for Cementation of Soiling on PV Modules and Telescope Mirrors. IEEE J. Photovolt. 2024 , 14 , 330–336. [ Google Scholar ] [ CrossRef ]
• Dewi, T.; Taqwa, A.; Rusdianasari; Kusumanto, R.D.; Sitompul, C.R. The Investigation of Sea Salt Soiling on PV Panel. In Proceedings of the 4th Forum in Research, Science, and Technology (FIRST-T1-T2-2020), Palembang, Indonesia, 10-11 November 2020; Atlantis Press: Amsterdam, The Netherlands, 2021; pp. 141–147. [ Google Scholar ] [ CrossRef ]
• Boeing, A.; Neda, M.; Steinberg, S.; Batista, J. The Impact of Lower Quality Water on Soiling Removal from Photovoltaic Panels. Renew. Sustain. Energy Rev. 2022 , 169 , 112870. [ Google Scholar ] [ CrossRef ]
• Nordin, M.; Sharma, S.; Khan, A.; Gianni, M.; Rajendran, S.; Sutton, R. Collaborative Unmanned Vehicles for Inspection, Maintenance, and Repairs of Offshore Wind Turbines. Drones 2022 , 6 , 137. [ Google Scholar ] [ CrossRef ]
• NPR. Solar Energy Project Location Debate. NPR [Internet]. 18 June 2023. Available online: https://www.npr.org/2023/06/18/1177524841/solar-energy-project-location-debate (accessed on 10 July 2024).
• Mirletz, H.; Hieslmair, H.; Ovaitt, S.; Curtis, T.L.; Barnes, T.M. Unfounded Concerns about Photovoltaic Module Toxicity and Waste Are Slowing Decarbonization. Nat. Phys. 2023 , 19 , 1376–1378. [ Google Scholar ] [ CrossRef ]
• Gunerhan, H.; Hepbasli, A.; Giresunlu, U. Environmental Impacts from the Solar Energy Systems. Energy Sources Part A Recovery Util. Environ. Eff. 2008 , 31 , 131–138. [ Google Scholar ] [ CrossRef ]
• Exley, G.; Page, T.; Thackeray, S.J.; Folkard, A.M.; Couture, R.-M.; Hernandez, R.R.; Cagle, A.E.; Salk, K.R.; Clous, L.; Whittaker, P.; et al. Floating Solar Panels on Reservoirs Impact Phytoplankton Populations: A Modelling Experiment. J. Environ. Manag. 2022 , 324 , 116410. [ Google Scholar ] [ CrossRef ]
• Exley, G.; Hernandez, R.R.; Page, T.; Chipps, M.; Gambro, S.; Hersey, M.; Lake, R.; Zoannou, K.-S.; Armstrong, A. Scientific and Stakeholder Evidence-Based Assessment: Ecosystem Response to Floating Solar Photovoltaics and Implications for Sustainability. Renew. Sustain. Energy Rev. 2021 , 152 , 111639. [ Google Scholar ] [ CrossRef ]
• Haas, J.; Khalighi, J.; De La Fuente, A.; Gerbersdorf, S.U.; Nowak, W.; Chen, P.-J. Floating Photovoltaic Plants: Ecological Impacts versus Hydropower Operation Flexibility. Energy Convers. Manag. 2020 , 206 , 112414. [ Google Scholar ] [ CrossRef ]
• Stichting Toegepast Onderzoek Waterbeheer. Zonneparken Versie Maart 2019 ; STOWA: Amersfoort, The Netherlands, 2019; Available online: https://www.stowa.nl/sites/default/files/assets/PUBLICATIES/Publicaties%202018/STOWA%202018-73%20Zonneparken%20versie%20maart%202019.pdf (accessed on 19 September 2024).
• Ribeiro, H.V.; Acre, M.R.; Faulkner, J.D.; Da Cunha, L.R.; Lawson, K.M.; Wamboldt, J.J.; Brey, M.K.; Woodley, C.M.; Calfee, R.D. Effects of Shady Environments on Fish Collective Behavior. Sci. Rep. 2022 , 12 , 17873. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Misman, N.A.; Sharif, M.F.; Chowdhury, A.J.K.; Azizan, N.H. Water Pollution and the Assessment of Water Quality Parameters: A Review. Desalin. Water Treat. 2023 , 294 , 79–88. [ Google Scholar ] [ CrossRef ]
• Yang, P.; Chua, L.H.C.; Irvine, K.N.; Nguyen, M.T.; Low, E.-W. Impacts of a Floating Photovoltaic System on Temperature and Water Quality in a Shallow Tropical Reservoir. Limnology 2022 , 23 , 441–454. [ Google Scholar ] [ CrossRef ]
• Al-Widyan, M.; Khasawneh, M.; Abu-Dalo, M. Potential of Floating Photovoltaic Technology and Their Effects on Energy Output, Water Quality and Supply in Jordan. Energies 2021 , 14 , 8417. [ Google Scholar ] [ CrossRef ]
• Ilgen, K.; Schindler, D.; Wieland, S.; Lange, J. The Impact of Floating Photovoltaic Power Plants on Lake Water Temperature and Stratification. Sci. Rep. 2023 , 13 , 7932. [ Google Scholar ] [ CrossRef ]
• Bai, Q.; Li, R.; Li, Z.; Leppäranta, M.; Arvola, L.; Li, M. Time-Series Analyses of Water Temperature and Dissolved Oxygen Concentration in Lake Valkea-Kotinen (Finland) during Ice Season. Ecol. Inform. 2016 , 36 , 181–189. [ Google Scholar ] [ CrossRef ]
• Liu, Z.; Ma, C.; Li, X.; Deng, Z.; Tian, Z. Aquatic Environment Impacts of Floating Photovoltaic and Implications for Climate Change Challenges. J. Environ. Manag. 2023 , 346 , 118851. [ Google Scholar ] [ CrossRef ]
• Wang, T.; Chang, P.; Huang, Y.; Lin, T.; Yang, S.; Yeh, S.; Tung, C.; Kuo, S.; Lai, H.; Chen, C. Effects of Floating Photovoltaic Systems on Water Quality of Aquaculture Ponds. Aquac. Res. 2022 , 53 , 1304–1315. [ Google Scholar ] [ CrossRef ]
• Bhattacharya, M.; Kumar, A.; Nema, A.K.; Das, S.; Vijayanandan, A. Making a Case for Environmental Risk-Based Monitoring of Floating Solar Systems. Environ. Sci. Technol. 2024 , 58 , 2595–2597. [ Google Scholar ] [ CrossRef ]
• Atikah, R.H.; Wahyuningsih, N.P.S.; Suwartha, N.; Setiawan, E.A. Spatial Analysis of Water Quality Parameters Concentration around the Floating Solar Panel Installation in Lake Mahoni, Depok, Indonesia. E3S Web Conf. 2024 , 485 , 01010. [ Google Scholar ] [ CrossRef ]
• Song, F.; Lu, Z.; Guo, Z.; Wang, Y.; Ma, L. The Effects of a Fishery Complementary Photovoltaic Power Plant on the Near-Surface Meteorology and Water Quality of Coastal Aquaculture Ponds. Water 2024 , 16 , 526. [ Google Scholar ] [ CrossRef ]
• Vlaswinkel, B.; Roos, P.; Nelissen, M. Environmental Observations at the First Offshore Solar Farm in the North Sea. Sustainability 2023 , 15 , 6533. [ Google Scholar ] [ CrossRef ]
• De Lima, R.L.P.; Paxinou, K.; Boogaard, F.C.; Akkerman, O.; Lin, F.-Y. In-Situ Water Quality Observations under a Large-Scale Floating Solar Farm Using Sensors and Underwater Drones. Sustainability 2021 , 13 , 6421. [ Google Scholar ] [ CrossRef ]
• Ubina, N.A.; Cheng, S.-C. A Review of Unmanned System Technologies with Its Application to Aquaculture Farm Monitoring and Management. Drones 2022 , 6 , 12. [ Google Scholar ] [ CrossRef ]
• De Lima, R.L.P.; De Graaf-van Dinther, R.E.; Boogaard, F.C. Impacts of Floating Urbanization on Water Quality and Aquatic Ecosystems: A Study Based on In Situ Data and Observations. J. Water Clim. Chang. 2022 , 13 , 1185–1203. [ Google Scholar ] [ CrossRef ]
• Chatziantoniou, A.; Papandroulakis, N.; Stavrakidis-Zachou, O.; Spondylidis, S.; Taskaris, S.; Topouzelis, K. Aquasafe: A Remote Sensing, Web-Based Platform for the Support of Precision Fish Farming. Appl. Sci. 2023 , 13 , 6122. [ Google Scholar ] [ CrossRef ]
• Bao, H.; Zhang, Y.; Song, M.; Kong, Q.; Hu, X.; An, X. A Review of Underwater Vehicle Motion Stability. Ocean Eng. 2023 , 287 , 115735. [ Google Scholar ] [ CrossRef ]
• YSI Inc. YSI EXO Multiparameter Water Quality Sondes. Available online: https://www.ysi.com/file%20library/documents/brochures%20and%20catalogs/ysi-exo-brochure.pdf (accessed on 19 September 2024).
• YSI Inc. YSI 6920 V2-2 Multiparameter Water Quality Sondes. Available online: https://www.ysi.com/6920-v2-2 (accessed on 19 September 2024).
• Quadlink Tech. Aquadlink ® Smart Aquaculture Application System. Available online: https://www.quadlink-tech.com/en/a4-11108-14327/Aquadlink%C2%AESmart-Aquaculture-Application-System.html (accessed on 19 September 2024).
• Myron L. Ultrapen PT1 ; Myron L: Carlsbad, CA, USA, 2024. Available online: https://www.myronl.com/products/handheld-portable-instruments/ultrapen-pt1/?gad_source=1&gclid=Cj0KCQjw7ZO0BhDYARIsAFttkCjR7sQRJ3sgPw4j1wK9lzwPxDoptNmhcrqKIY5AyNtjv1LHsXB82KQaAijJEALw_wcB (accessed on 4 July 2024).
• De Lima, R.L.P.; Boogaard, F.C.; De Graaf-van Dinther, R.E. Innovative Water Quality and Ecology Monitoring Using Underwater Unmanned Vehicles: Field Applications, Challenges and Feedback from Water Managers. Water 2020 , 12 , 1196. [ Google Scholar ] [ CrossRef ]
• In-Situ Inc. TROLL ® 9500 Multiparameter Water Quality Monitoring Instrument. Available online: https://www.inmtn.com/docs/IEI_Troll9500_bro.pdf (accessed on 19 September 2024).
• Van Essen Instruments. CTD Diver—Downloads ; Van Essen Instruments: Delft, The Netherlands, 2024; Available online: https://www.vanessen.com/products/data-loggers/ctd-diver/#tab-downloads (accessed on 4 July 2024).
• AQUAREAD. AP-2000/2000-D Advanced Multiparameter Water Quality Probes. Available online: https://www.aquaread.com/products/water-quality/ap-2000 (accessed on 19 September 2024).
• PME. PME miniDOT Dissolved Oxygen Logger Specifications. Fondriest Environmental. Available online: https://www.fondriest.com/pme-minidot-dissolved-oxygen-logger.htm (accessed on 4 July 2024).
• Germ, M.; Tertinek, Ž.; Zelnik, I. Diversity of Macrophytes and Macroinvertebrates in Different Types of Standing Waters in the Drava Field. Water 2024 , 16 , 1130. [ Google Scholar ] [ CrossRef ]
• Aquaread. AP-7000 ; Aquaread: Broadstairs, UK, 2020; Available online: https://www.aquaread.com/products/water-quality/ap-7000 (accessed on 4 July 2024).
• Krohkaew, J.; Nilaphruek, P.; Witthayawiroj, N.; Uapipatanakul, S.; Thwe, Y.; Crisnapati, P.N. Thailand Raw Water Quality Dataset Analysis and Evaluation. Data 2023 , 8 , 141. [ Google Scholar ] [ CrossRef ]
• Eureka Water Probes. Sonde Multiparametriche per Operatori di Campo. Manta+. Available online: https://www.waterprobes.com/product-page/manta-35 (accessed on 19 September 2024).
• Liu, X.; Georgakakos, A.P. Chlorophyll a Estimation in Lakes Using Multi-Parameter Sonde Data. Water Res. 2021 , 205 , 117661. [ Google Scholar ] [ CrossRef ]
• Nazirova, K.; Alferyeva, Y.; Lavrova, O.; Shur, Y.; Soloviev, D.; Bocharova, T.; Strochkov, A. Comparison of In Situ and Remote-Sensing Methods to Determine Turbidity and Concentration of Suspended Matter in the Estuary Zone of the Mzymta River, Black Sea. Remote Sens. 2021 , 13 , 143. [ Google Scholar ] [ CrossRef ]
• RBR Global. RBRduo 3 & RBRconcerto 3 |C.T, C.T.D, C.T.D++ ; RBR Global: Ottawa, ON, Canada, 2024; Available online: https://rbr-global.com/products/standard-loggers (accessed on 4 July 2024).
• Salas-Cueva, N.F.; Mendoza, J.; Cutipa-Luque, J.C.; Yanyachi, P.R. An Open-Source Wireless Platform for Real-Time Water Quality Monitoring with Precise Global Positioning. Int. J. Adv. Comput. Sci. Appl. 2021 , 12 , 775–782. [ Google Scholar ] [ CrossRef ]
• In-Situ. Aqua TROLL 500-600-700-800 Spec Sheet. Available online: https://in-situ.com/pub/media/support/documents/Aqua-TROLL-500-600-700-800_Spec-Sheet_ltr_en.pdf (accessed on 4 July 2024).
• Boehrer, B.; Saiki, K.; Ohba, T.; Tanyileke, G.; Rouwet, D.; Kusakabe, M. Carbon Dioxide in Lake Nyos, Cameroon, Estimated Quantitatively from Sound Speed Measurements. Front. Earth Sci. 2021 , 9 , 645011. [ Google Scholar ] [ CrossRef ]
• Idronaut. IDRONAUT OCEAN SEVEN 316Plus CTD for Oceanography ; Idronaut: Brugherio, Italy, 2023; Available online: www.idronaut.it/wp-content/uploads/2021/10/oceanseven316plus-leaflet.pdf (accessed on 4 July 2024).
• Marsili-Libelli, S. Fuzzy Prediction of the Algal Blooms in the Orbetello Lagoon. Environ. Model. Softw. 2004 , 19 , 799–808. [ Google Scholar ] [ CrossRef ]
• Di Natale, C.; Davide, F.; D’Amico, A.; Legin, A.; Rudinitskaya, A.; Selezenev, B.; Vlasov, Y. Technical Digest of Eurosensors X ; Eurosensors Association: Leuven, Belgium, 1996; pp. 1345–1348. [ Google Scholar ]
• Yu, V.; Legin, A.; Rudnitskaya, A.; Di Natale, C.; D’Amico, A. Nonspecific Sensor Arrays (“Electronic Tongue”) for Chemical Analysis of Liquids. Pure Appl. Chem 2005 , 77 , 1965–1983. [ Google Scholar ]
• Tønning, E.; Sapelnikova, S.; Christensen, J.; Carlsson, C.; Winther-Nielsen, M.; Dock, E.; Solna, R.; Skladal, P.; Nørgaard, L.; Ruzgas, T.; et al. Chemometric Exploration of an Amperometric Biosensor Array for Fast Determination of Wastewater Quality. Biosens. Bioelectron. 2005 , 21 , 608–617. [ Google Scholar ] [ CrossRef ]
• Gabrieli, G.; Muszynski, M.; Ruch, P.W. Feature Importance Methods Unveiling the Cross-Sensitive Response of an Integrated Sensor Array to Quantify Major Cations in Drinking Water. In Proceedings of the 2022 IEEE Sensors, Dallas, TX, USA, 30 October 2022–2 November 2022; pp. 1–4. [ Google Scholar ] [ CrossRef ]
• Martınez-Máñez, R.; Soto, J.; Garcia-Breijo, E.; Gil, L.; Ibáñez, J.; Llobet, E. An “Electronic Tongue” Design for the Qualitative Analysis of Natural Waters. Sens. Actuators B Chem. 2005 , 104 , 302–307. [ Google Scholar ] [ CrossRef ]
• Mimendia, A.; Gutiérrez, J.M.; Leija, L.; Hernández, P.R.; Favari, L.; Muñoz, R.; Del Valle, M. A Review of the Use of the Potentiometric Electronic Tongue in the Monitoring of Environmental Systems. Environ. Model. Softw. 2010 , 25 , 1023–1030. [ Google Scholar ] [ CrossRef ]
• Cetó, X.; Valle, M.D. Electronic Tongue Applications for Wastewater and Soil Analysis. iScience 2022 , 25 , 104304. [ Google Scholar ] [ CrossRef ]
• Campos, I.; Alcañiz, M.; Aguado, D.; Barat, R.; Ferrer, J.; Gil, L.; Marrakchi, M.; Martínez-Mañez, R.; Soto, J.; Vivancos, J.L. A voltammetric electronic tongue as tool for water quality monitoring in wastewater treatment plants. Water Res. 2012 , 46 , 2605–2614. [ Google Scholar ] [ CrossRef ]
• Cruz, M.G.N.; Ferreira, N.S.; Gomes, M.T.S.R.; Botelho, M.J.; Costa, S.T.; Vale, C.; Rudnitskaya, A. Determination of Paralytic Shellfish Toxins Using Potentiometric Electronic Tongue. Sens. Actuators B Chem. 2018 , 263 , 550–556. [ Google Scholar ] [ CrossRef ]
• Ruch, P.W.; Hu, R.; Capua, L.; Temiz, Y.; Paredes, S.; Lopez, A.; Barroso, J.; Cox, A.; Nakamura, E.; Matsumoto, K. A Portable Potentiometric Electronic Tongue Leveraging Smartphone and Cloud Platforms. In Proceedings of the 2019 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN), Fukuoka, Japan, 26–29 May 2019; pp. 1–3. [ Google Scholar ] [ CrossRef ]
• Arzamendia, M.; Britez, D.; Recalde, G.; Gomez, V.; Santacruz, M.; Gregor, D.; Gutierrez, D.; Toral, S.; Cuellar, F. An Autonomous Surface Vehicle for Water Quality Measurements in a Lake Using MQTT Protocol. In Proceedings of the 2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON), Valparaíso, Chile, 6–9 December 2021; pp. 1–5. [ Google Scholar ] [ CrossRef ]
• Beshah, W.T.; Moorhead, J.; Dash, P.; Moorhead, R.J.; Herman, J.; Sankar, M.S.; Chesser, D.; Lowe, W.; Simmerman, J.; Turnage, G. IoT Based Real-Time Water Quality Monitoring and Visualization System Using an Autonomous Surface Vehicle. In Proceedings of the OCEANS 2021: San Diego—Porto, San Diego, CA, USA, 20–23 September 2021; pp. 1–4. [ Google Scholar ] [ CrossRef ]
• Kaushal, P.; Mudhalwadkar, R.P. Internet of Things Enabled Electronic Tongue for Remote Monitoring of Water Quality. In Smart Sensors Measurements and Instrumentation ; Santhosh, K.V., Guruprasad, R.K., Eds.; Springer: Singapore, 2021; pp. 71–79. [ Google Scholar ]
• Mayflower: World’s Cleverest Robotic Ship Gets Ready to Cross and Study the Atlantic. Available online: https://research.ibm.com/blog/mayflower-to-cross-the-atlantic (accessed on 11 July 2024).
• Rudnitskaya, A. Calibration Update and Drift Correction for Electronic Noses and Tongues. Front. Chem. 2018 , 6 , 433. [ Google Scholar ] [ CrossRef ]
• Simmerman, J.; Chesser, G.D.; Lowe, J.W.; Moorhead, J.; Beshah, W.; Turnage, G.; Dash, P.; Sankar, M.S.; Moorhead, R.; Herman, J. Evaluation of the Utility and Performance of an Autonomous Surface Vehicle for Mobile Monitoring of Waterborne Biochemical Agents. In Proceedings of the OCEANS 2021: San Diego—Porto, San Diego, CA, USA, 20–23 September 2021; pp. 1–10. [ Google Scholar ] [ CrossRef ]
• Gentemann, C.L.; Scott, J.P.; Mazzini, P.L.F.; Pianca, C.; Akella, S.; Minnett, P.J.; Cornillon, P.; Fox-Kemper, B.; Cetinić, I.; Chin, T.M.; et al. Saildrone: Adaptively Sampling the Marine Environment. Bull. Am. Meteorol. Soc. 2020 , 101 , E744–E762. [ Google Scholar ] [ CrossRef ]
• Steccanella, L.; Bloisi, D.D.; Castellini, A.; Farinelli, A. Waterline and Obstacle Detection in Images from Low-Cost Autonomous Boats for Environmental Monitoring. Robot. Auton. Syst. 2020 , 124 , 103346. [ Google Scholar ] [ CrossRef ]
• Manley, J.E. Unmanned Surface Vehicles, 15 Years of Development. In Proceedings of the OCEANS 2008, Quebec City, QC, Canada, 15–18 September 2008; pp. 1–4. [ Google Scholar ] [ CrossRef ]
• Christ, R.D.; Wernli, R.L. The ROV Manual: A User Guide for Observation-Class Remotely Operated Vehicles , 1st ed.; Elsevier: Amsterdam, The Netherlands, 2013. [ Google Scholar ]
• Enterprise Grade ROV Platform Powerful & Precise, Advanced Add-Ons, Exceptional Stability, Superior Battery. Available online: https://www.qysea.com/products/fifish-w6/ (accessed on 5 July 2024).
• Vedachalam, N.; Ramesh, R.; Jyothi, V.B.N.; Doss Prakash, V.; Ramadass, G.A. Autonomous Underwater Vehicles—Challenging Developments and Technological Maturity towards Strategic Swarm Robotics Systems. Mar. Georesour. Geotechnol. 2019 , 37 , 525–538. [ Google Scholar ] [ CrossRef ]
• Hydromea. EXRAY™ Leaflet 2024 ; Hydromea: Renens, Switzerland, 2024; Available online: https://files.hydromea.com/exray/EXRAY_leaflet_2024_Web.pdf (accessed on 19 September 2024).
• Katzschmann, R.K.; DelPreto, J.; MacCurdy, R.; Rus, D. Exploration of Underwater Life with an Acoustically Controlled Soft Robotic Fish. Sci. Robot. 2018 , 3 , eaar3449. [ Google Scholar ] [ CrossRef ]
• Moriconi, C.; Cupertino, G.; Betti, S.; Tabacchiera, M. Hybrid Acoustic/Optic Communications in Underwater Swarms. In Proceedings of the OCEANS 2015—Genova, Genova, Italy, 18–21 May 2015; pp. 1–9. [ Google Scholar ] [ CrossRef ]
• UNEXMIN Project. Underwater Explorer for Flooded Mines. Horizon 2020, European Union. Available online: https://www.unexmin.eu/ (accessed on 15 July 2024).
• Ridolfi, A.; Costanzi, R.; Fanelli, F.; Monni, N.; Allotta, B.; Bianchi, S.; Conti, R.; Gelli, J.; Gori, L.; Pugi, L.; et al. FeelHippo: A Low-Cost Autonomous Underwater Vehicle for Subsea Monitoring and Inspection. In Proceedings of the 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC), Florence, Italy, 7–10 June 2016; pp. 1–6. [ Google Scholar ] [ CrossRef ]
• Hydromea. Autonomous Underwater Swarm. Available online: https://www.hydromea.com/_files/ugd/474ccd_0bd150d8e2194648b37b80d3b947f626.pdf (accessed on 5 July 2024).
• Bellingham, J.G.; Rajan, K. Robotics in Remote and Hostile Environments. Science 2007 , 318 , 1098–1102. [ Google Scholar ] [ CrossRef ]
• Yoerger, D.R.; Jakuba, M.; Bradley, A.M.; Bingham, B. Techniques for Deep Sea Near Bottom Survey Using an Autonomous Underwater Vehicle. In Robotics Research: Results of the 12th International Symposium ISRR ; Springer: Berlin/Heidelberg, Germany, 2007. [ Google Scholar ]
• Hagen, P.E.; Midtgaard, O.; Hasvold, O. Making AUVs Truly Autonomous. In Proceedings of the OCEANS 2007, Vancouver, BC, Canada, 29 September–4 October 2007; pp. 1–4. [ Google Scholar ] [ CrossRef ]
• Walker, J.H.; Trembanis, A.C.; Miller, D.C. Assessing the Use of a Camera System within an Autonomous Underwater Vehicle for Monitoring the Distribution and Density of Sea Scallops ( Placopecten magellanicus ) in the Mid-Atlantic Bight. Fish. Bull. 2016 , 114 , 261–274. [ Google Scholar ] [ CrossRef ]
• Niccolai, A.; Grimaccia, F.; Lorenzo, G.D.; Araneo, R.; Ughi, F.; Polenghi, M. A Review of Floating PV Systems with a Techno-Economic Analysis. IEEE J. Photovolt. 2024 , 14 , 23–34. [ Google Scholar ] [ CrossRef ]
• Kinsey, J.C.; Eustice, R.M.; Whitcomb, L.L. A Survey of Underwater Vehicle Navigation: Recent Advances and New Challenges. In Proceedings of the 7th Conference on Maneuvering and Control of Marine Craft (MCMC’2006), Lisbon, Portugal, 20–22 September 2006; IFAC: Lisbon, Portugal, 2006; pp. 1–12. [ Google Scholar ]
• Heidemann, J.; Stojanovic, M.; Zorzi, M. Underwater Sensor Networks: Applications, Advances and Challenges. Phil. Trans. R. Soc. A 2012 , 370 , 158–175. [ Google Scholar ] [ CrossRef ]
• Pal, A.; Campagnaro, F.; Ashraf, K.; Rahman, M.R.; Ashok, A.; Guo, H. Communication for Underwater Sensor Networks: A Comprehensive Summary. ACM Trans. Sens. Netw. 2022 , 19 , 22. [ Google Scholar ] [ CrossRef ]
• Cai, W.; Liu, Z.; Zhang, M.; Wang, C. Cooperative Artificial Intelligence for Underwater Robotic Swarm. Robot. Auton. Syst. 2023 , 164 , 104410. [ Google Scholar ] [ CrossRef ]
• Campagnaro, F.; Calore, M.; Casari, P.; Calzado, V.S.; Cupertino, G.; Moriconi, C.; Zorzi, M. Measurement-Based Simulation of Underwater Optical Networks. In Proceedings of the OCEANS 2017—Aberdeen, Aberdeen, UK, 19–22 June 2017; pp. 1–7. [ Google Scholar ] [ CrossRef ]
• Glover, D.M.; Jenkins, W.J.; Doney, S.C. Modeling Methods for Marine Science. In Modeling Methods for Marine Science , 2nd ed.; Cambridge University Press: Cambridge, UK, 2016. [ Google Scholar ]
• Paul, D.; Devaprakasam, D.; Patil, S.; Agrawal, A. Floating Solar: A Review on the Comparison of Efficiency, Issues, and Projections with Ground-Mounted Solar Photovoltaics. Int. J. Sustain. Dev. Plan. 2023 , 18 , 3213–3228. [ Google Scholar ] [ CrossRef ]
• Ramanan, C.J.; Lim, K.H.; Kurnia, J.C.; Roy, S.; Bora, B.J.; Medhi, B.J. Towards Sustainable Power Generation: Recent Advancements in Floating Photovoltaic Technologies. Renew. Sustain. Energy Rev. 2024 , 194 , 114322. [ Google Scholar ] [ CrossRef ]
• dell’Erba, R. Determination of Spatial Configuration of an Underwater Swarm with Minimum Data. Int. J. Adv. Robot. Syst. 2015 , 12 , 97. [ Google Scholar ] [ CrossRef ]
• dell’Erba, R. Distance Estimations in Unknown Sea Underwater Conditions by Power LED for Robotics Swarms. Contin. Mech. Thermodyn. 2021 , 33 , 97–106. [ Google Scholar ] [ CrossRef ]
• dell’Erba, R. The Distances Measurement Problem for an Underwater Robotic Swarm: A Semi-Experimental Trial, Using Power LEDs, in Unknown Sea Water Conditions. Contin. Mech. Thermodyn. 2023 , 35 , 895–903. [ Google Scholar ] [ CrossRef ]
• Peng, Z.; Wang, J.; Wang, J. Constrained Control of Autonomous Underwater Vehicles Based on Command Optimization and Disturbance Estimation. IEEE Trans. Ind. Electron. 2019 , 66 , 3627–3635. [ Google Scholar ] [ CrossRef ]
• RBR. RBR CT-UV and CTD-UV Instruments ; RBR: Ottawa, Canada, 2023; Available online: https://rbr-global.com/wp-content/uploads/2023/12/RBR-CT-uv-and-CTD-uv-Instruments-RIG-0015699revA.pdf (accessed on 19 September 2024).
• RBR. Performance of Two RBRconcerto CTDs on OSNAP Mooring CF06 ; RBR: Ottawa, Canada, 2019; Available online: https://rbr-global.com/wp-content/uploads/2019/11/Performance-of-two-RBRconcerto-CTDs-on-OSNAP-mooring-CF06-20190409-1.pdf (accessed on 19 September 2024).
• RBR. Assessment of RBRcoda, T.ODO Performance on Long-Term Deployment and Profiling in Bedford Basin ; RBR: Ottawa, Canada, 2020; Available online: https://rbr-global.com/wp-content/uploads/2020/02/0008419revC-Assessment-of-RBRcoda-T.ODO-performance-on-long-term-deployment-and-profiling-in-Bedford-Basin.pdf (accessed on 19 September 2024).
• Oceanology International. Trusted for Argo: RBR Sensors Receive Highest Argo Data Quality Designation. Oceanology International. 17 February 2023. Available online: https://inside.oceanologyinternational.com/2023/02/17/trusted-for-argo-rbr-sensors-receive-highest-argo-data-quality-designation/ (accessed on 19 September 2024).
• Lundesgaard, Ø.; Sundfjord, A.; Lind, S.; Nilsen, F.; Renner, A.H.H. Import of Atlantic Water and Sea Ice Controls the Ocean Environment in the Northern Barents Sea. Ocean Sci. 2022 , 18 , 1389–1418. [ Google Scholar ] [ CrossRef ]
• Ziar, H.; Prudon, B.; Lin, F.; Roeffen, B.; Heijkoop, D.; Stark, T.; Teurlincx, S.; De Senerpont Domis, L.; Goma, E.G.; Extebarria, J.G.; et al. Innovative Floating Bifacial Photovoltaic Solutions for Inland Water Areas. Prog. Photovolt. 2021 , 29 , 725–743. [ Google Scholar ] [ CrossRef ]
• Dever, M.; Owens, B.; Richards, C.; Wijffels, S.; Wong, A.; Shkvorets, I.; Halverson, M.; Johnson, G. Static and Dynamic Performance of the RBRargo3 CTD. J. Atmos. Ocean. Technol. 2022 , 39 , 1525–1539. [ Google Scholar ] [ CrossRef ]
• Teece, M.A. An Inexpensive Remotely Operated Vehicle for Underwater Studies. Limnol. Ocean Methods 2009 , 7 , 206–215. [ Google Scholar ] [ CrossRef ]
• Meng, L.; Hirayama, T.; Oyanagi, S. Underwater-Drone with Panoramic Camera for Automatic Fish Recognition Based on Deep Learning. IEEE Access 2018 , 6 , 17880–17886. [ Google Scholar ] [ CrossRef ]
• Kimball, P.W.; Clark, E.B.; Scully, M.; Richmond, K.; Flesher, C.; Lindzey, L.E.; Harman, J.; Huffstutler, K.; Lawrence, J.; Lelievre, S.; et al. The ARTEMIS Under-ice AUV Docking System. J. Field Robot. 2018 , 35 , 299–308. [ Google Scholar ] [ CrossRef ]
• Yan, X.; Liang, X.; Ouyang, W.; Liu, Z.; Liu, B.; Lan, J. A Review of Progress and Applications of Ship Shaft-Less Rim-Driven Thrusters. Ocean Eng. 2017 , 144 , 142–156. [ Google Scholar ] [ CrossRef ]
• Hydromea. DiskDrive Thruster Technology ; Hydromea: Renens, Switzerland, 2024; Available online: https://www.hydromea.com/diskdrive-thruster-technology (accessed on 19 September 2024).
• Hydromea. Vertex Autonomous Underwater Swarm ; Hydromea: Renens, Switzerland, 2024; Available online: https://www.hydromea.com/vertex-autonomous-underwater-swarm (accessed on 19 September 2024).
• Markelov, I.; Couture, R.; Fischer, R.; Haande, S.; Van Cappellen, P. Coupling Water Column and Sediment Biogeochemical Dynamics: Modeling Internal Phosphorus Loading, Climate Change Responses, and Mitigation Measures in Lake Vansjø, Norway. JGR Biogeosci. 2019 , 124 , 3847–3866. [ Google Scholar ] [ CrossRef ]
• Saloranta, T.M.; Andersen, T. MyLake—A Multi-Year Lake Simulation Model Code Suitable for Uncertainty and Sensitivity Analysis Simulations. Ecol. Model. 2007 , 207 , 45–60. [ Google Scholar ] [ CrossRef ]

Share and Cite

Bossi, S.; Blasi, L.; Cupertino, G.; dell’Erba, R.; Cipollini, A.; De Vito, S.; Santoro, M.; Di Francia, G.; Tina, G.M. Floating Photovoltaic Plant Monitoring: A Review of Requirements and Feasible Technologies. Sustainability 2024 , 16 , 8367. https://doi.org/10.3390/su16198367

Bossi S, Blasi L, Cupertino G, dell’Erba R, Cipollini A, De Vito S, Santoro M, Di Francia G, Tina GM. Floating Photovoltaic Plant Monitoring: A Review of Requirements and Feasible Technologies. Sustainability . 2024; 16(19):8367. https://doi.org/10.3390/su16198367

Bossi, Silvia, Luciano Blasi, Giacomo Cupertino, Ramiro dell’Erba, Angelo Cipollini, Saverio De Vito, Marco Santoro, Girolamo Di Francia, and Giuseppe Marco Tina. 2024. "Floating Photovoltaic Plant Monitoring: A Review of Requirements and Feasible Technologies" Sustainability 16, no. 19: 8367. https://doi.org/10.3390/su16198367

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals