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This study investigates the feasibility of utilizing surplus hydropower from Ecuador’s major hydroelectric plants to produce green hydrogen, a clean energy source that can be used to meet a large percentage of energy needs. Given Ecuador’s significant hydropower infrastructure, this approach leverages untapped energy resources for hydrogen production, with potential impacts on decarbonization strategies. A Pareto analysis identified five key hydroelectric plants that contribute the most to the national surplus. Using historical data from 2019 to 2023, a stochastic model was applied to estimate future surplus availability through 2030. The findings indicate that although Ecuador’s surplus hydropower peaked in 2021, the general trend shows a decline, suggesting an urgent need to capitalize on these resources efficiently. The results indicate a projected annual surplus of hydroelectric energy in Ecuador, ranging from 7475 to 3445 GWh over the next five years, which could be utilized for green hydrogen production. Ecuador thus has promising potential to become a green hydrogen producer, enhancing both regional energy security and carbon reduction goals. The reduction in energy availability for hydrogen production is attributed to the increasing energy demand and variable climatic conditions.

The rising demand for clean energy production due to climate change emphasizes the importance of optimizing water resources, particularly in countries with significant hydropower potential. Existing models for the Operational Planning of Hydropower Systems (HPSOP) typically focus on the natural flows of rivers, often overlooking the potential of water transfers between rivers and basins. To address this gap, this article employs an improved mathematical model of hydropower production, considering the adjustment of the water transfer in the operation schedule as an additional optimization variable. A customized meta-heuristic, named the Evolutionary Socio-Bio Inspired Technique (ESBIT), has been tailored to integrate water transfer mechanisms into the operational planning model. The proposed model was validated through a case study at the Henry Borden Complex in São Paulo, Brazil, using real power plant parameters and inflow data from the Brazilian system. The results obtained from the test case, both with and without water transfer, demonstrate that the proposed methodology effectively captures the operational characteristics of a system that allows water transfers between rivers or basins to optimize the available water resources and system costs.

In light of challenges like climate change, pollution, and depletion of fossil fuel reserves, governments and businesses prioritize renewable energy sources such as solar, wind, and hydroelectric power. Renewable energy forecasting models play a crucial role for energy market operators and prosumers, aiding in planning, decision-making, optimization of energy sales, and evaluation of investments. This study aimed to develop machine learning models for hydropower forecasting in plants integrated into Water Distribution Systems, where energy is generated from water flow used for municipal water supply. The study involved developing and comparing monthly and two-week forecasting models, utilizing both one-step-ahead and two-step-ahead forecasting methodologies, along with different missing data imputation techniques. The tested algorithms—Seasonal Autoregressive Integrated Moving Average, Random Forest, Temporal Convolutional Network, and Neural Basis Expansion Analysis for Time Series—produced varying levels of performance. The Random Forest model proved to be the most effective for monthly forecasting, while the Temporal Convolutional Network delivered the best results for two-week forecasting. Across all scenarios, the seasonal–trend decomposition using the LOESS technique emerged as the most successful for missing data imputation. The accurate predictions obtained demonstrate the effectiveness of using these models for energy planning and decision-making.

Alkaline electrolysis systems are currently considered to be suitable for large-scale hydrogen production. Previous research has primarily focused on integrating renewable energy sources such as solar and wind into water electrolysis systems. However, intermittent issues stemming from the sporadic nature of renewable energy sources have led to the introduction of energy storage systems (ESSs) to address these intermittent challenges. Extensive research has been conducted on the efficiency and operational aspects of these systems. In contrast to other renewable energy sources, hydropower offers the advantages of stable output and high utilization, making it a promising solution for overcoming intermittent issues. In this study, we propose the design of an optimized alkaline electrolysis system tailored for small-scale hydropower generation. This approach allowed us to confirm the efficiency of a small-scale hydropower-based hydrogen production facility and the analysis of hydrogen production costs under diverse scenarios. Notably, the optimal selling price per kilogram of hydrogen was determined to be USD 15.6 when the operational time exceeded 20 h, albeit indicating a challenging market supply. Under the consideration of various scenarios and government subsidies, this study revealed that a USD 10/kgH2 subsidy or 24 h of continuous operation achieved break-even points in the sixth and eighth years, respectively. Ultimately, the findings underscore the necessity for essential measures, including government backing and technological advancements in small-scale hydropower facilities, to enhance the economic viability of the green hydrogen market in South Korea.

All long-term hydropower planning problems require a forecast of the inflow during the planning period. However, it is challenging to accurately forecast inflows for a year or more. Therefore, it is common to use stochastic models considering the uncertainties of the inflow. This paper compares deterministic and stochastic models in a weekly rolling horizon framework considering inflow uncertainty. The stochastic model is tested in both a risk-neutral and a risk-averse version. The rolling horizon framework helps make periodic decisions and update the information in each rolling week, which minimizes the errors in prolonged forecasts. The models aim to utilize the water stored in the rainy season throughout the year with minimum load shedding while storing as much water as possible at the end of the planning horizon. The Conditional Value at Risk (CVaR) risk measure is used to develop the risk-averse stochastic model. Three different risk measures are investigated to choose the risk measure that yields the best outcome in the risk-averse problem, and the two best measures are compared to a deterministic and risk-neutral model in a weekly rolling horizon framework. The results show that the risk-neutral and best risk-averse models perform almost equally and are better than the deterministic model. Hence, using a stochastic model would be an improvement to the actual planning performed in the Ethiopian and other African countries’ power systems.

Electrification using renewable energy sources represents a clear path toward solving the current global energy crisis. In Colombia, this challenge also involves the diversification of the electrical energy sources to overcome the historical dependence on hydropower. In this context, green hydrogen represents a key energy carrier enabling the storage of renewable energy as well as directly powering industrial and transportation sectors. This work explores the realistic potential of the main renewable energy sources, including solar photovoltaics (8172 GW), hydropower (56 GW), wind (68 GW), and biomass (14 GW). In addition, a case study from abroad is presented, demonstrating the feasibility of using each type of renewable energy to generate green hydrogen in the country. At the end, an analysis of the most likely regions in the country and paths to deploy green hydrogen projects are presented, favoring hydropower in the short term and solar in the long run. By 2050, this energy potential will enable reaching a levelized cost of hydrogen (LCOH) of 1.7, 1.5, 3.1 and 1.4 USD/kg-H2 for solar photovoltaic, wind, hydropower and biomass, respectively.

We developed a Parsimonious Multi-dimensional Moving Window (PMMW) algorithm that only requires Digital Elevation Model (DEM) data of a watershed to efficiently locate potentially optimal hydropower sites. The methodology requires only open source DEM data; therefore, it can be used even in remotest watersheds of the world where in situ measurements are scarce or not available at all. We used three parameters in this algorithm, and tested the method using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Shuttle Radar Topography Mission (SRTM) derived DEMs. Our case study on the Morony Watershed, Montana, USA shows that (1) along with 6 out of the 7 existing hydropower plants being successfully located, 12 new potential hydropower sites were also identified, using a clearance of 1 km, diversion of 90 m, and Hydropower Index (HI) threshold of 109 m as the criteria. For the 12 new potential hydropower sites, 737.86 Megawatts (MW) ± 84.56 MW untapped hydropower potential in the Morony Watershed was also derived; (2) SRTM DEM is more suitable for determining the potential hydropower sites; (3) although the ASTER and SRTM DEMs provide elevation data with high accuracy, micro-scale elevation differences between them at some locations may have a profound impact on the HI.

Part I of this series of publications addressed the background and fundamentals of the lifetime assessment of prototype Francis turbines. Part II concentrated on the developed methods of numerical calculation and assessment procedures. The present contribution (Part III) deals with the instrumentation and the metrological range of the assessment procedure. The most important sensors, measurement tools, and data acquisition units are presented (background). The instrumentation of the prototype Francis turbine is used, on the one hand, for machine unit monitoring and plant operating and, on the other hand, for generating measurement data to validate and adjust/correct the numerical simulations. Measurement data form the basis for further evaluations at various levels. A wide variety of measured variables are required to carry out the remaining lifetime of a component using fatigue analysis. Those variables include pressure and acceleration signals, vibration monitoring, and strain gauge applications for mechanical stress analysis. The available measurement signals are divided into groups based on the developed method. Thus, already-available data from the control room are compared with machine monitoring and temporarily measured data. The correlation of all available data is essential today to determine an exact idea of the occurring flow phenomena and their effects on the mechanical stresses on the component. This interaction of the different data sources and, subsequently, the use of selected quantities for the numerical calculation are part of the newly developed concept for fatigue strength analysis of mechanical components of a turbine unit (methods). The results of this journal article are divided into the discussion of the necessary instrumentation and mounting of the sensors and into the evaluation, presentation, and interpretation of the measurement data. In addition, a fatigue strength assessment is made at the position of the strain gauges. These results serve as a basis for validating the numerical stress calculation. It is worth mentioning that the validation of the numerical results and the discussion of the deviations and error consideration is carried out in Part IV of this publication series (results). This journal article of the series on condition assessment of prototype Francis turbines ends with a discussion of the results and conclusions for further data processing (conclusion).

Microgrids are decentralized power production systems, where the energy production and consumption are very close to each other. Microgrids generally exploit renewable energy sources, encountering a problem of storage, as the power production from solar and wind is intermittent. This research presents a new integrated methodology and discusses a comparison of batteries and pumped storage hydropower (PSH) as energy storage systems with the integration of wind and solar PV energy sources, which are the major upcoming technologies in the renewable energy sector. We implemented the simulator and optimizer model (HOMER), which develops energy availability usage to obtain optimized renewable energy integration in the microgrid, showing its economic added value. Two scenarios are run with this model—one considers batteries as an energy storage technology and the other considers PSH—in order to obtain the best economic and technical results for the analyzed microgrid. The economic analysis showed a lower net present cost (NPC) and levelized cost of energy (LCOE) for the microgrid with PSH. The results showed that the microgrid with the storage of PSH was economical, with an NPC of 45.8 M€ and an LCOE of 0.379 €/kWh, in comparison with the scenario with batteries, which had an NPC of 95.2 M€ and an LCOE of 0.786 €/kWh. The role of storage was understood by differentiating the data into different seasons, using a Python model. Furthermore, a sensitivity analysis was conducted by varying the capital cost multiplier of solar PV and wind turbines to obtain the best optimal economic solutions.

The increasing penetration of wind energy in electric power systems leads to a great demand for flexible resources to regulate power fluctuations. This paper focuses on investigating the impacts of the operational flexibility of hydropower generation systems on reducing wind curtailment and load shedding in a hybrid hydro–wind power system. Considering timescale variabilities of wind power, the upward and downward regulation capabilities of hydro flexibility under sub-hour and hour dispatch scales are estimated. Based on developed flexible indicators, the ultimate access ratio of wind power penetration into the power system is obtained by using the estimated probability of insufficient regulation reserves. All these analyses are carried out under the wet and dry periods to better understand their differences with the hydro flexibility. The method and obtained results provide important guidance for the stable and high-efficiency operation of hybrid power systems.

Hydropower is one of the most sustainable and desirable renewable energy sources. Gravitational water vortex hydro turbine (GWVHT) systems are one of the most suitable and sustainable renewable power generation devices for remote and rural areas, particularly in developing countries, owing to their small scales and low costs. There are various GWVHT systems with different configurations and various operating conditions. The main components of a GWVHT system include the inlet and outlet channels, a basin, and a turbine on which there are a number of blades attached. This paper presents a comprehensive review regarding the progress and development of various GWVHT systems, covering broad aspects of GWVHT systems, particularly various types of basins, inlet and outlet channels, turbines with blades which have different shapes, orientations, sizes, numbers, etc. The nature of the previous studies is summarised. The fundamentals of the vortex dynamics involved and the quantitative analysis of the performance of GWVHT systems are also described. The turbulence models and multiphase models used in some leading numerical simulation studies have been reviewed. As a case study, the implementation of a GWVHT system in PNG is presented. Based on the review of previous studies regarding GWVHT systems, the major issues and challenges are summarised, and some key topics are recommended for future research work on the performance of GWVHT systems.

The Alaska Railbelt transmission system runs from Fairbanks to Anchorage to Homer and supplies 75% of the state’s population with power. In the near future, this system will experience significant increases in load due to electrification of the transportation and heating sectors. To account for this, several state organizations are working towards the creation of an integrated resource plan and reliability standards.This work encompasses the efforts of researching the operations, cost, and locations of desirable hydropower and pumped storage hydropower (PSH) resources in the areas surrounding the Railbelt transmission system. The aspects of conventional hydropower and PSH as well as adjustable-speed and ternary PSH were analyzed. With Alaska’s diverse and rugged landscape, QGIS was utilized to delineate the positions of energy resources within a reasonable distance from the Railbelt. By incorporating Digital Terrain Models and the QGIS processing toolbox, a least cost path analysis was completed to filter out resources within the designated distance of the Railbelt. Applying existing cost models to the data in this work helped to decide the energy resources that would be studied further. The future of this project includes modeling the selected energy sources in the PSS/e Railbelt model to examine their effects on the reliability and stability.

Hydropower has grown to play an important role in power systems including increasing clean and low-carbon energies, and the effect of electric loads should be basically evaluated for the reliable operation of these systems. For the hydraulic–mechanical–electrical system of the hydropower station, the state equation model for stability evaluation was derived with typical electric load models and elastic models for pipe flow, and after experimental confirmation with a built single-unit setup for a system, the effects of different electrical loads and pipe flow models on typical hydropower systems stability were investigated in detail. The results indicate that for the built single-unit system with different load characteristics, the numerical results were basically consistent with experimental research, and the unit’s regulation performance for the dynamic load was superior to that of the static load. Evident differences existed in the effects of different electric loads on the operational stability, mainly depending on the pipe length and the corresponding models, and an optimum-order elastic model of pipe flow was preferred to reveal the dynamic interactions between different systems. Furthermore, for a typical two-unit system, the potential coupling resonance hydraulic–mechanical–electrical system is pointed out with the preferred-order elastic model of pipe flow.

Hydropower is the most prevalent source of renewable energy production worldwide. As the global demand for robust and ecologically sustainable energy production increases, developing and enhancing the current energy production processes is essential. In the past decade, machine learning has contributed significantly to various fields, and hydropower is no exception. All three horizons of hydropower models could benefit from machine learning: short-term, medium-term, and long-term. Currently, dynamic programming is used in the majority of hydropower scheduling models. In this paper, we review the present state of the hydropower scheduling problem as well as the development of machine learning as a type of optimization problem and prediction tool. To the best of our knowledge, this is the first survey article that provides a comprehensive overview of machine learning and artificial intelligence applications in the hydroelectric power industry for scheduling, optimization, and prediction.

One of the challenges posed by renewable energies is the stabilization of parameters related to the quality of electrical energy. This study demonstrates the existence of a relationship between input blocks of hydropower and the variation of the fundamental frequency of the electricity grid. By mapping production data provided by the Spanish Electric Network with frequency measured in the laboratory, it is shown that gradients of hydropower are correlated with frequency fluctuations for certain characteristic times. Considering hourly instances of energy input, the study compares two methods for calculating hydropower gradients (linear regression and pseudo-linear regression) and two methods for calculating local frequency extrema (the “specular inertia” method and analysis by comparison with the moving average) in order to corroborate the results.

Power generation from river hydropower plants depends mainly on river flow. Water fluctuations in the river make the yield process unpredictable. To reduce these fluctuations, building a small reservoir at the river flow of the hydropower plant is recommended. Conventionally, classic single-pond models are commonly used to design run-of-river hydropower plants. However, such models are associated with fluctuations, sagging, and irregular power fluctuations that lead to irregular water fluctuations. This research proposes a novel idea to replace the single-pond model with a three-pond model to increase the plant’s overall efficiency. The three-pond model is developed as a three-tank nonlinear hydraulic system that contains the same amount of water as a conventional single pond. It also has the advantage of minimizing the run-of-river power plant’s dependence on river flow and increasing efficiency by trapping swell and turbulence in the water. To further increase the efficiency, the developed model was tested for smooth and effective level control using fuzzy control.

Hydropower plays an essential role in Europe’s energy transition and can serve as an important factor in the stability of the electricity system. This is even more crucial in areas that rely strongly on renewable energy production, for instance, solar and wind power, as for example the Peloponnese and the Ionian islands in Greece. To safeguard hydropower’s contribution to total energy production, an accurate prediction of the annual precipitation is required. Valuable tools to obtain accurate predictions of future observations are firstly a series of sophisticated data preprocessing techniques and secondly the use of advanced machine learning algorithms. In the present paper, a complete procedure is proposed to obtain accurate predictions of meteorological data, such as precipitation. This procedure is applied to the Greek automated weather stations network, operated by the National Observatory of Athens, in the Peloponnese and the Ionian islands in Greece. The proposed prediction algorithm successfully identified the climatic zones based on their different geographic and climatic characteristics for most meteorological stations, resulting in realistic precipitation predictions. For some stations, the algorithm underestimated the annual total precipitation, a weakness also reported by other research works.

The increasing demand for flexibility in hydropower systems requires pumped storage power plants to change operating modes and compensate reactive power more frequently. In this work, we demonstrate the potential of applying reinforcement learning (RL) to control the blow-out process of a hydraulic machine during pump start-up and when operating in synchronous condenser mode. Even though RL is a promising method that is currently getting much attention, safety concerns are stalling research on RL for the control of energy systems. Therefore, we present a concept that enables process control with RL through the use of a digital twin platform. This enables the safe and effective transfer of the algorithm’s learning strategy from a virtual test environment to the physical asset. The successful implementation of RL in a test environment is presented and an outlook on future research on the transfer to a model test rig is given.

Lubricant oil is used in hydropower units to minimize friction, improving the turbine efficiency and reducing the wear. However, oil production is a pollutant process, while eventual spills may affect water quality and damage freshwater ecosystems. In this study, the lubricant oil consumption of the European hydropower fleet was estimated (considering its installed capacity of 254 GW). The energy required to extract and process the oil was also estimated based on available literature data. The oil consumption was estimated to be 22 × 103 tons/year, and the associated CO2 emissions are 105 tons/year. The lubricant oil costs EUR 116 million per year. Although this is only 0.0022% of the oil consumed as a primary energy source in the European context, and less than 0.4% of the European industry consumption of lubricant oil, results show that new bearing types and oil-free turbines (e.g., self-lubricating or water-lubricated turbines) can improve the sustainability of the hydropower sector, minimizing the risks and impacts associated with incidental oil spills and leakages. The provided data can also be used for Life Cycle Assessment analyses.

This paper presents research on the dewatering areas during drawdown operations in the Kaunas Hydropower Plant (HPP) reservoir situated in the lowland area of Lithuania. It is a multipurpose reservoir primarily used for power generation by two large hydropower plants. Because of the HPP peaking operation and the reservoir morphology—a shallow, gently sloping littoral zone—significant dewatered areas can occur (during drawdown operations). This is especially dangerous during the fish spawning period. Therefore, reservoir operation rules are in force that limit operation of the HPPs and secure other reservoir stakeholder needs. There is a lack of knowledge about the fish spawning locations, how they are changing, and what areas are dewatered at different stages of HPP operation. This knowledge is crucial for decision making and efficient water resources management in order to increase power generation and protect the environment at the same time. A detailed survey of an area containing several potential spawning grounds (about 5 ha) was conducted to track changes in the dewatering areas. The aim of the study is to investigate different surveying methods, gather knowledge about potential fish spawning sites, and investigate the dewatered areas that occur during water level (WL) fluctuations. The methodology and insights of this study can be used in similar lowland countries to assist in improving the usage of water resources while increasing power generation.

The energy crisis is affecting a number of countries, but particularly those that are heavily dependent on the traditional energy generation formula (e.g., Poland), as well as those neighbouring the territory of the ongoing war in Ukraine, i.e., Poland, Lithuania, Latvia and Estonia. With this in mind, the authors of this study decided to explore the issue of water energy as a source of green (cheap and environmentally safe) energy in these countries. The main objective of the paper is to review the available literature, which is needed to identify the role hydropower plays in energy security and energy transition in these energy markets. This paper is based on a review and critical appraisal of the available literature and studies together with an inference. The structure of the paper consists of an introduction, the main part of the review and conclusions. The geopolitical location and socio-economic conditions of the adopted set of countries, form the basis of the review of the existing literature on the theme explored and the substantive inference. The main findings of this review indicate that the literature is most strongly focused on the overall assessment of the energy transition of the adopted countries for review, where the hydropower thread is most often taken up as one source of renewable energy supply. Hydropower, due to its relatively low share in the energy systems of the adopted set of countries, is, according to the authors, insufficiently explored. The most significant gap relates to the aspect of the potential for hydropower development in these areas, considering both the construction of new hydropower plants and opportunities signalled in the literature for the modernisation or restoration of existing ones. In this respect, the need for analyses (studies and simulations) of hydropower development, considering the economic benefits associated with their development juxtaposed with the safety dimension of this course of action for the environment (analysis and assessment of environmental costs) is indicated, which is the main recommendation of the review.

Run-of-river hydropower plants are a cost-efficient technology that produce a power output proportional to the instantaneous flow of water diverted from the exploited stream by exploiting several mechanical, hydraulic, and electric devices. However, as no storage is available, its design and operation is tailored according to the unpredictability of its power generation. Hence, the modelling of this type of power plants is a necessity for the promotion of its development. Accordingly, based on models from the literature, this study proposes a comprehensive methodology for optimally designed small run-of-river hydropower plants based on a levelized cost of energy (LCOE). The proposed methodology aims at facilitating a faster design for more cost-effective and energy-efficient small hydropower plants. Depending on the average daily flow rates and the gross head of a given site, the model proposed in this study calculates the diameter, thickness, and length of a penstock; it also suggests the optimal selection of a turbine, determines the admissible suction head of a turbine for its optimal implementation, and determines the optimal number of turbines, all in order to minimize the LCOE of the proposed project. The model is tested to design a small run-of-river hydropower plant with a capacity of 6.32 MW exploiting the river Nyong in Mbalmayo. The results confirm the profitability of the investment with an LCOE of around 0.05 USD/kWh, which is the lowest limit value of the LCOE range for small hydropower plants, as presented in the IPCC (Intergovernmental Panel on Climate Change) report, assuming a project lifespan of 50 years and a discount rate of 12.5%. These results also show that it may be worth to provide the energy sector with a small hydropower design tool with a graphical interface. In addition, it would be appropriate to use a similar method in an off-grid context where a hydropower plant, with or without storage, is combined with another source to meet the electrical needs of a given population.

Energy security, as one of the most important components of state security, is a permanent element of academic debates and political discussions. Owing to the multidimensional and multifaceted nature of energy security, defining it is a complex process, requiring the consideration of a wide range of factors straddling economics, geology, ecology and geopolitics which decide whether we are dealing with the state of energy security or the lack of it. Energy security is usually equated with the security of supply. Another group of definitions of energy security focuses on the concept of security of services. A different approach to energy security issues is presented by energy exporting countries, whose objective is to ensure sufficiently high and stable income from sales of energy resource exports (security of demand). The subject of this paper is an analysis of the energy security of hydropower-producing countries—Tajikistan and Kyrgyzstan. Energy security has been analyzed in the context of security of supply, services, and demand on the basis of the approach proposed by Llamosas and Sovacool. So far, no work has been carried out to analyse the hydropower sectors of Kyrgyzstan and Tajikistan in the context of the energy security comparison of both countries. It is worth emphasising that their energy security and mutual relations are important from the point of view of the stability of the entire Central Asian region. Kyrgyzstan and Tajikistan have large hydropower potential, which, if properly used, could cover their domestic electricity demand and the surplus can be exported to neighbouring countries. Unfortunately, both countries are not utilising this potential for the time being. The main difficulty in the area of security of supply and services is the seasonality and low reliability of electricity supplies. Among the reasons for this are the poor technical and economic conditions of energy companies as a result of maintaining low tariffs, the irrecoverability of consumers’ energy bills, electricity theft, significant transmission loses and a high level of corruption. Although both countries aspire to the role of an energy exporters, they are themselves forced to import electricity from neighboring countries.

The current production of water energy in Poland is much lower than the theoretical and technical potential. The aim of the article is to analyse the current state of hydropower in Poland as well as the prospects and conditions for development. Poland's total technical hydropower potential is estimated at 12,000–14,000 GWh/year, but currently, approx. 20% of this potential is used. The considerations undertaken in the study concern, for example, pumped-storage power plants and the development of small hydropower plants. Hydropower plants are not only important from the point of view of electricity production and storage, but also fulfill many other functions, including the general social, which is an essential element of the implementation of the concept of sustainable development. The analyses show that the hydropower sector in Poland may be an important element of low-carbon energy and an important element of energy security. Increasing the volume of electricity production from hydropower by 5% will contribute to the growth in CO2 reduction by 140,702 tons. The stabilization function of the power system in Poland is also significant.

The Francis hydro-turbine is a typical nonlinear system with coupled hydraulic, mechanical, and electrical subsystems. It is difficult to understand the reasons for its operational failures, since the main cause of failures is due to the complex interaction of the three subsystems. This paper presents an improved dynamic model of the Francis hydro-turbine. This study involves the development of a nonlinear dynamic model of a hydraulic unit, given start-up and emergency processes, and the consideration of the effect of water hammer during transients. To accomplish the objectives set, existing models used to model hydroelectric units are analyzed and a mathematical model is proposed, which takes into account the dynamics during abrupt changes in the conditions. Based on these mathematical models, a computer model was developed, and numerical simulation was carried out with an assessment of the results obtained. The mathematical model built was verified on an experimental model. As a result, a model of a hydraulic unit was produced, which factors in the main hydraulic processes in the hydro-turbine.

Micro hydropower (MHP) provides a viable renewable energy solution from which individuals, organisations and communities can also derive social value and benefits. Desk studies and literature reviews show limited studies that (a) quantify the social impact of MHPs in water networks and (b), establish evaluation methods for such analysis. To date, most studies relating to MHP projects have focused on physical and technological parameters, as well as cost and environmental factors that influence their design, installation, operation, and maintenance. Less attention has been given to the intangible social, political, and institutional considerations, which are also important for the acceptability and adoption of renewables such as MHPs, and for their performative longevity. This study addresses these gaps. The social return on investment (SROI) method was used as the basis to quantify the cost and social returns of three MHP demonstrators in a public and private water supply, and irrigation network in Europe. The value inputs and outputs from each case were analysed and a SROI range of between 2.6 and 5.8 euros for each one euro invested was determined. The findings were further evaluated using sensitivity tests. This work serves as a useful first step to establishing a SROI benchmark range for MHP schemes in water networks, extrapolatable for other renewable energy interventions. They also highlight the opportunities and challenges of quantifying and forecasting the social returns of MHPs to guide future work.

A pico hydropower plant is an energy harvesting system that allows energy production using the power of the water flowing in small watercourses, and in water distribution network. Axial Flow Flux Permanent Magnet Synchronous Generator (AFPMSG) are particularly suitable for this application, being efficient machines that achieve high power with small dimensions. This paper presents a parametrical study of several configurations and topologies of three-phase and single-phase AFPMSG, for pico hydropower application, to assess the most suitable dimensional characteristics for the most energy production using a safe voltage of 25 V. The AFPMSGs here considered has a simple single stator and rotor configuration, commercial-type permanent magnets, and concentric windings, to facilitate their cost-effective construction and the spread of their use also in developing countries. For each AFPMSG considered, the power output was calculated using 3-D modelling and Finite Element Analysis; besides, the different parameters and features that affect the power output were evaluated at different rotational speeds. The results achieving a power density up to 100 W/cm3, at 1000 rpm with energy produced to 1.7 kWh/day.

Slovenia is a Central European country with a long history of hydropower. This paper gives a brief introduction to the current status of hydropower utilization and informs about some selected successful examples of hydropower plant operation. One such example is fish passage and flood risk reduction on the lower reaches of the Sava River at the Brežice hydroelectric power plant, taking into account a complex of morphological, hydrological, hydraulic, and anthropogenic factors. Future development is considered against the background of the National Energy and Climate Plan, which does not envisage any significant expansion in the capacity or function of the hydropower sector. The envisaged capacity increase is from the current 4430 GWh to around 4580 GWh by 2030. It is shown that the current energy storage capacity of Slovenia’s only pumped storage plant will be sufficient to offset the introduction of new non-dispatchable renewable energy sources by 2030. By around 2028, the country will have a need for electrical energy storage from renewable energy sources, reaching a modest total of only 6140 MWh per year. However, by sticking to the unambitious National Energy and Climate Plan, Slovenia will miss the opportunity to remain self-sufficient in electricity generation and significantly increase its share of renewable energy sources. The National Energy and Climate Plan aims to increase the share of renewable energy in total energy generation from 25% in 2020 to 27% by 2030.

Some hydropower reservoirs are operated under different constraint levels. For these reservoirs, a multi-level (ML) dependent-chance (DC) model is established. In the model, only when the higher-level constraints are satisfied are the lower-level constraints or system benefits considered. The multi-level dependent-chance (MLDC) model is specified by two models. One is based on existing reliability-constrained (RC) dynamic programming (DP), in which the soft constraints are addressed using reliability constraints of 1, and the priorities are reflected using the order of magnitudes of Lagrange multipliers. The other is the explicit dependent-chance reasoning in the DP recursive function, in which each soft constraint is represented as an objective function of negative expected failure time and the optimum is the solution with a larger value for all higher-level objective functions. The proposed models are applied to derive long-term operation rules for the hydropower system on the middle-lower Lancang River. The results show the feasibility and performances of the explicit graded constraint control of the proposed model and the solution methods.

Hydropower plants often work in off-design conditions to regulate the power grid frequency. Frequent transient operation of hydraulic turbines leads to premature failure, fatigue and damage to the turbine components. The speed-no-load (SNL) operating condition is the last part of the start-up cycle and one of the most damaging operation conditions of hydraulic turbines. Hydraulic instabilities and high-stress pressure fluctuations occur due to the low flow rate and unsteady load on the runner blades. Numerical simulations can provide useful insight concerning the complex flow structures that develop inside hydraulic turbines during SNL operation. Together with experimental investigations, the numerical simulations can help diagnose failures and optimize the exploitation of hydraulic turbines. This paper introduces the numerical model of a full-scale 10 MW Kaplan turbine prototype operated at SNL. The geometry was obtained by scaling the geometry of the corresponding model turbine as the model and prototype are geometrically similar. The numerical model is simplified and designed to optimize the numerical precision and computational costs. The guide vane and runner domains are asymmetrical, the epoxy layer applied to two runner blades during the experimental measurements is not modelled and a constant runner blade clearance is employed. The unsteady simulation was performed using the SAS–SST turbulence model. The numerical results were validated with torque and pressure experimental data. The mean quantities obtained from the numerical simulation were in good agreement with the experiment. The mean pressure values were better captured on the pressure side of the runner blade compared to the suction side. However, the amplitude of the pressure fluctuations was more accurately predicted on the suction side of the runner blade. The amplitude of the torque fluctuations was considerably underestimated.

The role of hydropower has become increasingly essential following the introduction of intermittent renewable energies. Quickly regulating power is needed, and the transient operations of hydropower plants have consequently become more frequent. Large pressure fluctuations occur during transient operations, leading to the premature fatigue and wear of hydraulic turbines. Investigations of the transient flow phenomena developed in small-scale turbine models are useful and accessible but limited. On the other hand, experimental and numerical studies of full-scale large turbines are challenging due to production losses, large scales, high Reynolds numbers, and computational demands. In the present work, the operation of a 10 MW Kaplan prototype turbine was modelled for two operating points on a propeller curve corresponding to the best efficiency point and part-load conditions. First, an analysis of the possible means of reducing the model complexity is presented. The influence of the boundary conditions, runner blade clearance, blade geometry and mesh size on the numerical results is discussed. Secondly, the results of the numerical simulations are presented and compared to experimental measurements performed on the prototype in order to validate the numerical model. The mean torque and pressure values were reasonably predicted at both operating points with the simplified model. An analysis of the pressure fluctuations at part load demonstrated that the numerical simulation captured the rotating vortex rope developed in the draft tube. The frequencies of the rotating and plunging components of the rotating vortex were accurately captured, but the amplitudes were underestimated compared to the experimental data.

Groundwater storage is an important water management solution that is overlooked by several countries worldwide. This paper evaluates the potential for storing water in the Bananal sedimentary basin and proposes the construction of canals to reduce sediment obstructions in the river flow and harmful flood events. This would allow for better control of the water level. The water stored in the sedimentary basin can be used as a climate change adaptation measure to ensure that the level of the flood plain is maintained high during a drought or low during an intense flood event. Additionally, the flood plain will function as a water reservoir, regulate the river flow downstream from the flood plain, and enhance hydropower generation. A significantly smaller reservoir area is expected to store water, as the water will be stored as groundwater in the sedimentary basin. Results show that the Bananal basin has the potential to store up to 49 km3 of water, which can add up to 11.7 TWh of energy storage to the Brazilian energy matrix for a CAPEX energy storage cost of 0.095 USD/kWh. This is an interesting solution for the Araguaia basin and several other basins worldwide.

Albania’s electricity sector lacks energy storage systems (ESS); hence, large quantities of electricity generated during the off-peak time, and excess electricity cannot be stored. On the other hand, the transmission capacity upgrades do not keep pace with the growth in peak electric demand; thus, congestion-related issues occur. Congestion of transmission lines has led to considerable uncertainties. Drin River cascade is located north of Albania. It possesses enormous potential energy that is not used due to a lack of ESS. Security of supply, rational use of renewable energy sources (RES), diversification of the electricity sector, increased competitiveness, sheltering more future RES capacities that can benefit from deferring investment in the existing transmission system, and environmental protection are some of these the main benefits of integrating ESS. Regarding the energy transition, the Albanian government’s endeavor aims to maintain and further develop a flexible, sustainable, secure, efficiently supplied, and affordable energy supply system. The results of the simulation executed by using ES-select software to produce multiple benefits from a single device from the chosen application’s list (App1–App6) showed that the most adequate ESS for storing excess electricity in the Drin River cascade are: compressed air energy storage (CAES-c), pumped hydro energy storage (PHES), and sodium-sulfur batteries (NaS). Integrating such systems in the central or bulk generation makes the circumvented cost in 10 years profitable; therefore, moving towards 2030, it would be extremely difficult to tackle the energy sector’s challenges alone, without integrating the ESS.

Electricity generation is becoming increasingly flexible in Europe these days. Due to the integration of new renewable energy sources like wind and photovoltaic, other conventional resources, such as hydropower, operate within a brought range around their best efficiency point, thus leading to higher dynamical loads at the water-bearing parts, especially at the runner and the guide vanes (background). By scrutinizing the literature of the past years, one could summarize the outcome in that way, that research projects focused either on model measurements with higher visual accessibility or, less often, on prototype measurements in existing power plants. Today prototype measurements are performed, if possible, to eliminate scaling effects. Moreover, increasing computing power allows prototype simulations to be carried out within a reasonable time. At the acknowledged research projects, prototype and model measurements and numerical simulations have been performed to identify the main gaps in Francis turbines’ lifetime assessment (methods). One special outcome of these investigations was the impracticality of numerical simulations and calculation time, respectively, of start and stop events. Therefore, a prototype measurement with focus at this operating point should be performed to provide more data and an insight into the unit’s behavior. The future goal is a comprehensive machine unit lifetime assessment of the water-bearing parts in a Francis turbine machine set (results). This complex task needs several steps, beginning from measurements through simulations towards data processing. A particular challenge is posed, when the assessment methods are applied to old machines.

Part I of the publication series addressed the fundamentals of lifetime assessment of prototype Francis turbines. This paper (Part II) focuses on the numerical part of the procedure. The essential steps and requirements shall be presented (background). The starting points for the numerical considerations are the pressure fields of the transient CFD simulations, which are exported per time step and applied to the existing structure via a fluid–structure interaction. That enables a transient mechanical stress calculation to be conducted, resulting in the fatigue analysis of the component to estimate the remaining lifetime. The individual model requirements should be represented accordingly and applied to the prototype facility (method). The results obtained from this application should be discussed and evaluated. It has to be mentioned that the validation of the numerical results will be performed at Part IV of this publication series (results). The present paper will end up discussing the results and conclusions about further data processing (Conclusion).

Hydropower is the most widely used renewable power source worldwide. The current work presents a methodological tool to determine the hydropower potential of a reservoir based on available hydrological information. A Bayesian analysis of the river flow process and of the reservoir water volume is applied, and the estimated probability density function parameters are integrated for a stochastic analysis and long-term simulation of the river flow process, which is then used as input for the water balance in the reservoir, and thus, for the estimation of the hydropower energy potential. The stochastic approach is employed in terms of the Monte Carlo ensemble technique in order to additionally account for the effect of the intermediate storage retention due to the thresholds of the reservoir. A synthetic river flow timeseries is simulated by preserving the marginal probability distribution function properties of the observed timeseries and also by explicitly preserving the second-order dependence structure of the river flow in the scale domain. The synthetic ensemble is used for the simulation of the reservoir water balance, and the estimation of the hydropower potential is used for covering residential energy needs. For the second-order dependence structure of the river flow, the climacogram metric is used. The proposed methodology has been implemented to assess different reservoir volume scenarios offering the associated hydropower potential for a case study at the island of Crete in Greece. The tool also provides information on the probability of occurrence of the specific volumes based on available hydrological data. Therefore, it constitutes a useful and integrated framework for evaluating the hydropower potential of any given reservoir. The effects of the intermediate storage retention of the reservoir, the marginal and dependence structures of the parent distribution of inflow and the final energy output are also discussed.

Based on new policies of the European Union, green technologies are to be mostly considered for power generation. Hydropower generation is one of the essential elements of sustainable energy production. Therefore, specific attention, both economically and technically, needs to be given to this sector of energy production. The Vistula River in Poland is considered an international waterway. The power production potential of the river has been taken into account over the years. However, further configurations are needed to obtain a more in-depth ecological knowledge-base and economic plans, which are socially approved. In an attempt to make the project environmentally friendly, specific attention was put into sustainable transport. Different methods of transport were researched to find the most renewable transport combination, mainly based on waterways. Having performed a cost–benefit analysis related to the economic aspects of the project, it was found that such an investment is highly profitable (B/C = 2.81).

Construction of the Włocławek Barrage on the Vistula River in 1970 became an important source of energy; however, it discontinued sediment transport in the Vistula River. This phenomenon resulted in accumulation before and erosion below the barrage; a similar problem can be expected due to the planned construction of the Lower Vistula Cascade. This study is dedicated to finding an effective and feasible solution to sediment transport management, acceptable to a wide group of users (e.g., navigation, energy producers, and ecologists). A numerical 1D model was applied to carry out analysis of hydrodynamics and sediment transport in the river section from Włocławek Barrage to the Vistula River mouth in the Baltic Sea. For calibration, historical data describing the accumulation and erosion created by the Włocławek Barrage were used. The proposed model allowed incorporation of new barrages chronologically, in accordance with the proposed time schedules. Analysis was carried out in a 50-year horizon, using a set of historical flow data. For sediment flushing, it was proposed to use natural flooding events exceeding Q10% discharge and to control sediment management of the adjacent barrages. To use this method in practice requires verification.

This paper presents changes in the flow of 14 rivers located in the Warta River basin, recorded from 1951 to 2020. The Warta is the third-longest river in Poland. Unfortunately, the Warta River catchment area is one of the most water-scarce regions. It hosts about 150 hydropower plants with a capacity of up to 5 kW. The catchment areas of the 14 smaller rivers selected for the study differ in location, size, land cover structure and geological structure. The paper is the first study of this type with respect to both the number of analyzed catchments, the length of the sampling series and the number of analyzed flow characteristics in this part of Europe. The analysis of changes in the river flows was performed with reference to low minimum, mean and maximum monthly, seasonal and annual flows. Particular attention was paid to 1, 3, 7, 30 and 90-day low flows and durations of the flows between Q50 and Q90%. In addition, the duration of flows between Q50 and Q90% were analysed. Analysis of the direction and extent of particular flow types was performed by multitemporal analysis using the Mann–Kendall (MK) and Sen (S) tests. The analysis of multiannual flow sequences from the years 1951–2020 showed that the changes varied over the time periods and catchments. The most significant changes occurred in the low flows, while the least significant changes occurred in the high flows. From the point of view of the operation of the hydropower sector, these changes may be unfavourable and result in a reduction in the efficiency of run-of-river hydropower plants. It was established that local factors play a dominant role in the shaping of river flows in both positive and negative terms, for the efficiency of the hydropower plants.

The present paper indicates that hydropower, including small hydropower plants (SHPs), may play a very important role in Poland’s energy transformation in the near future. The development of SHPs may also increase water resources in the steppe Poland. Additionally, the aim of the present research is to conduct the PEST analysis of SHPs in Poland, taking into account the SHP potential. For the first time, maps showing the power and location of potential SHPs on the existing dams in Poland are presented. SHPs should be an important element of energy transition in Poland, especially on a local scale—it is stable energy production. Our analysis shows that there are 16,185 such dams in Poland, while the total capacity of potential hydropower plants in Poland would be 523.6 MW, and the total number of new jobs is estimated at 524. It was calculated that the annual avoided carbon dioxide emissions will amount to 4.4 million tons, which will reduce Poland’s emissions by 1.4%. The construction of SHPs can bring significant environmental and economic benefits. As far as the PEST analysis is concerned, the political environment of SHPs in Poland can be described as unfavorable (2.86 points). The economical nature of PEST analysis (3.86 points) should be considered as friendly for the development of SHPs. The social nature of PEST analysis can be considered as neutral (3.36 points). The technological nature of the PEST analysis can be considered as neutral (3.21 points).

Hydropower as stable power installations play an important role among renewable energy sources. Yet, their share in renewable energy is small. Currently, it is only 10% of energy from renewable energy sources (RES), compared to 27% in 2010. Therefore, the aim of this paper is to assess the RES support schemes in Poland related to hydropower, such as green certificates, auctions and FIT, with the use of the Levelized Cost of Electricity (LCOE) analysis in order to determine which support scheme is best incentivizing hydropower development. The evolution of the hydropower support scheme in Poland is presented. The total LCOE and possible revenues from support systems for various segments of hydropower installations are graphically analyzed for two analysis periods (15 and 50 years) and for two discount rates (7% and 11.4%). The analysis shows the great importance of the support schemes in the profitability of the hydropower plants investments. The LCOE graphical analysis proves to be suitable for showing sensitivity analysis of capital and operating costs of various sizes of hydropower plants. The analysis shows that the LCOE in micro-power plants is usually higher than the support and revenues available in the green certificates or auctions or FIT schemes in Poland.

In the Global South, pico- and micro-hydropower turbines are often made by local workshops. Despite several advantageous features, e.g., a high power density and capacity to handle silt, there is no commonly available Turgo turbine design appropriate for local manufacture. Technological developments including the internet, CAD, and additive manufacturing increase the opportunity to precisely transfer designs around the world. Consequently, design improvements can be shared digitally and used by manufacturers in their local context. In this paper, a rationalised CFD approach was used to guide simple design changes that improve the efficiency of a Turgo turbine blade. The typical manufacturing capacity of the micro-hydropower industry in Nepal was used to rationalise the variation of potential design changes. Using the geometry and operational parameters from an existing design as a benchmark, a two-blade, homogenous, multiphase model was developed and run using the commercial code ANSYS CFX. Initially, it was identified that the jet aim position had a significant effect on the efficiency. A design of experiments’ approach and subsequent analysis of numerical and visual results were used to make design changes that resulted in an improvement in efficiency from 69% to 81%. The design changes maintained the simple profile of the blade, ensuring that the resulting design was appropriate for manufacture in a local workshop.

The Ecuador’s expansion plans for the power sector promote the exploitation of hydro power potential, natural gas and a small share of alternative renewable energies. In 2019, electricity generation reached 76.3% from hydroelectric power, 21.9% from thermal plants and 1.8% from other renewable resources. Although the power energy mix is mainly based on renewable technologies, the total energy demand is still dependent on fossil fuels, which is the case of the transport sector that alone accounted for 50% of the total primary energy consumed in the country. This paper analyzes the pathway to develop a clean and diversified electricity mix, covering the demand of three specific development levels of electric transportation. The linear optimization model (urbs) and the Ecuador Land Use and Energy Netwrok Analysis (ELENA) are used to optimize the expansion of the power system in the period from 2020 to 2050. Results show that reaching an electricity mix 100% based on renewable energies is possible and still cover a highly electrified transport that includes 47.8% of land passenger, and 5.9% of land freight transport. Therefore, the electrification of this sector is a viable alternative for the country to rely on its own energy resources, while reinforcing its future climate change mitigation commitments.

Pressurized rock traps are constructed in many hydropower plants to stop sand and gravel from being transported through the turbines. Pressurized rock traps are typically located in the downstream end of unlined headrace tunnels, where the tunnel itself may be one of the sediment sources. This state-of-the-art review presents an overview of research on pressurized rock traps from both publicly available sources and unpublished sources. Limited scientific literature exists on rock traps, and most of the existing literature has previously been unavailable for an international audience. Based on this review, it is concluded that pressurized rock traps should be built with the flow area and sediment deposition volume separated by plates or ribs. Without any separation measures, the sediments risk being re-entrained due to turbulence. This review is separated into three sections: (1) sediment problems and sources of sediments, (2) theory for pressurized rock traps, and (3) design of pressurized rock traps. The recommended design for new pressurized rock traps, including a design flow chart, is provided. Finally, a recommended solution for rebuilding existing pressurized rock traps with an open design into a closed design is also presented.

The growth in renewable energy integration over the past few years, primarily fueled by the drop in capital cost, has revealed the requirement for more sustainable methods of integration. This paper presents a collocated hybrid plant consisting of solar photovoltaic (PV) and Ternary pumped-storage hydro (TPSH) and designs controls that integrate the PV plant such that the behavior and the controllability of the hybrid plant are similar to those of a conventional plant within operational constraints. The PV array control and hybrid plant control implement a neural–network-based framework to coordinate the response, de-loading, and curtailment of multiple arrays with the response of the TPSH. With the help of the designed controls, a symbiotic relationship is developed between the two energy resources, where the PV compensates for the TPSH nonlinearities and provides required speed of response, while the TPSH firms the PV system and allows the PV to be integrated using its existing infrastructure. Simulations demonstrate that the designed controls enable the PV system to track references, while the TPSH’s firming and shifting transforms the PV system into a base load plant for most of the day and extends its hours of operation.

Deposition of debris on the screens of hydroelectric power plants translates into measurable economic losses. Occurring plant debris, although it is an organic material, is characterised by different forms and structure. It is often leaves, branches, and grasses in lowland areas, while in mountainous regions, broken boughs and trees can be expected. On the trash racks of power plants, debris may be deposited in different forms, shapes, and places. This work aims to determine the impact of the degree of submergence of debris on the values of the force acting on the racks. This paper analyzes the influence of the rectangular shape of the debris deposited on the trash racks and its degree of submergence and weight on the obtained values of the force acting on the racks as a result of water pressure, which directly affects the hydraulic losses and productivity of hydroelectric power plants. Our research confirms the negative influence of the deposited plant debris on the value of forces recorded on the gratings. The increase in the recorded force, and thus the resistance on the grating, is obviously dependent on the degree of obstruction of the debris by the grating obtained by changing the degree of debris immersion and its weight. In the case of changing the degree of submergence, the increase in force recorded on the gratings varied during the experiment from about 25% recorded for the fully submerged debris compared to that of the partially submerged debris for the mass of 100 g; in comparison, an increase of about 31% was recorded for that of the mass of 200 g. However, comparing the values of the forces recorded on the obstructed grids to that of the forces recorded on the clean grids, the increase ranged from about 15–53%.

We analyzed United States Federal Energy Regulatory Commission (FERC) documents prepared for 29 recently licensed hydropower projects and created two novel datasets to improve understanding of the environmental study life cycle, defined here as the process that begins with an environmental study being requested by a hydropower stakeholder or regulator, and ends with the study either being rejected or approved/conducted. Our two datasets consisted of summaries of information taken from (1), study determination letters prepared by FERC for 23 projects that were using the integrated licensing process, and (2), environmental study submittals and issuances tracked and attributed to seven projects using the FERC record. Our objective was to use the two resulting environmental life cycle datasets to understand which types of environmental studies are approved, rejected, and implemented during FERC licensing, and how consistently those types of studies are required across multiple hydropower projects. We matched the requested studies to a set of 61 river function indicators in eight categories and found that studies related to the category of biota and biodiversity were requested most often across all 29 projects. Within that category, studies related to river function indicators of presence, absence, detection of species and habitat/critical habitat were the most important to stakeholders, based on the relative number of studies requested. The study approval, rejection, and request rates were similar within each dataset, although the 23 projects with study determination letters had many rejected studies, whereas the dataset created from the seven projects had very few rejected studies.

Reservoirs in Taiwan often provide hydroelectric power, irrigation water, municipal water, and flood control for the whole year. Taiwan has the climatic characteristics of concentrated rainy seasons, instantaneous heavy rains due to typhoons and rainy seasons. In addition, steep rivers in mountainous areas flow fast and furiously. Under such circumstances, reservoirs have to face sudden heavy rainfall and surges in water levels within a short period of time, which often causes the water level to continue to rise to the full level even though hydroelectric units are operating at full capacity, and as reservoirs can only drain the flood water, this results in the waste of hydropower resources. In recent years, the impact of climate change has caused extreme weather events to occur more frequently, increasing the need for flood control, and the reservoir operation has faced severe challenges in order to fulfil its multipurpose requirements. Therefore, in order to avoid the waste of hydropower resources and improve the effectiveness of the reservoir operation, this paper proposes a real-time 48-h ahead water level forecasting system, based on fuzzy neural networks with multi-stage architecture. The proposed multi-stage architecture provides reservoir inflow estimation, 48-h ahead reservoir inflow forecasting, and 48-h ahead water level forecasting. The proposed method has been implemented at the Techi hydropower plant in Taiwan. Experimental results show that the proposed method can effectively increase energy efficiency and allow the reservoir water resources to be fully utilized. In addition, the proposed method can improve the effectiveness of the hydropower plant, especially when rain is heavy.

Pumped Hydropower Storage (PHS) is the maturest and most economically viable technology for storing energy and regulating the electrical grid on a large scale. Due to the growing amount of intermittent renewable energy sources, the necessity of maintaining grid stability increases. Most PHS facilities today require a geographical topology with large differences in elevation. The ALPHEUS H2020 EU project has the aim to develop PHS for flat geographical topologies. The present study was concerned with the initial design of a low-head model counter-rotating pump-turbine. The machine was numerically analysed during the shutdown and startup sequences using computational fluid dynamics. The rotational speed of the individual runners was decreased from the design point to stand-still and increased back to the design point, in both pump and turbine modes. As the rotational speeds were close to zero, the flow field was chaotic, and a large flow separation occurred by the blades of the runners. Rapid load variations on the runner blades and reverse flow were encountered in pump mode as the machine lost the ability to produce head. The loads were less severe in the turbine mode sequence. Frequency analyses revealed that the blade passing frequencies and their linear combinations yielded the strongest pulsations in the system.