Search Results (148)

In hydropower tunnel systems, unlined pressurized tunnels in competent rock are commonly used for cost-effective construction. Incorporating pressurized sand traps at the downstream end of these tunnels can increase plant capacity and improve energy efficiency. The present work focuses on optimizing the performance of existing pressurized sand traps. Hydraulic scale models were developed and tested at the Hydraulic Laboratory of NTNU, Within the 960 MW Tonstad Hydropower Plant in southern Norway as a case study. This study compares 1:1 velocity/sediment scaling with Froude scaling through physical experiments, analyzing velocity profiles via Particle Image Velocimetry (PIV) and sediment trap efficiency. Results show that Froude scaling, combined with geometric sediment scaling, provides superior accuracy in trap efficiency scaling across varying factors. However, in many practical hydropower applications, the large scaling factor required for laboratory models results in very small model sediments, leading to cohesion limitations. In such cases, Froude scaling may not be feasible. The 1:1 scaling method provides a conservative alternative. Hence, for practical applications, 1:1 scaling may be more cost-effective and sufficient for designing pressurized sand traps. This study emphasizes the importance of accounting for unscaled parameters and flow phenomena in hydraulic model design. Full article

Distributed renewable energy sources with significant output fluctuations can negatively impact the power grid stability when it is connected to the power grid. Therefore, it is necessary to develop a capacity configuration method that improves the output stability of highly uncertain energy sources such as wind and photovoltaic (PV) power by integrating pumped storage units. In response, this study proposes a capacity configuration method for a cascade small hydropower-pumped storage–wind–PV complementary system. The method utilizes the regulation capacity of cascade small hydropower plants and pumped storage units, in conjunction with the fluctuating characteristics of local distributed wind and PV, to perform power and energy time-series matching and determine the optimal capacity allocation for each type of renewable energy. Furthermore, an optimization and scheduling model for the cascade small hydropower-pumped storage–wind–PV complementary system is constructed to verify the effectiveness of the configuration under multiple scenarios. The results demonstrate that the proposed method reduces system energy deviation, improves the stability of power output and generation efficiency, and enhances the operational stability and economic performance of the system. Full article

In the Amazon, nearly one million people remain without reliable access to electricity. Moreover, the rural electricity grid is a mostly single-phase, ground-return type, with poor energy quality and high expenses. This study examines very low-head micro-hydropower (MHP) sites in the Amazon, emphasizing the integration of multiple axial-flow turbines. It includes an analysis of flow duration curves and key curves, both upstream and downstream, to design an MHP plant with multiple units targeting maximized energy yield. The presence of multiple turbines is crucial due to the substantial annual flow variation in the Amazon rivers. One contribution of this work is its scalable framework for ultra-low-head and high flow variability in small rivers, which is applicable in similar hydrological configurations, such as those typical of the Amazon. The design applies the minimum pressure coefficient criterion to increase turbine efficiency. Computational Fluid Dynamics (CFD) simulations forecast turbine efficiency and flow behavior. The CFD model is validated using experimental data available in the literature on a similar turbine, which is similarly used in this study for cost reasons, with discrepancies under 5%, demonstrating robust predictions of turbine efficiency and head behavior as a function of flow. This study also explores the implications of including inlet guide vanes (IGVs). We use a case study of a small bridge in Vila do Janari, situated in the southeastern part of Pará state, where heads range from 1.4 to 2.4 m and turbine flow rates span from 0.23 to 0.92 m³/s. The optimal configuration shows the potential to generate 63 MWh/year. Full article

Hydropower is the main source of renewable energy and the most feasible for implementation in remote areas without access to conventional energy grids. Therefore, knowledge of actual, potential, and future perspectives of sustainable hydropower projects is decisive for their viability. This study aims to estimate the present and future potential capacity of Peru’s hydropower system and from the potential small hydroelectric plants, specifically Run-of-River class. First, we employed geospatial databases and hydroclimatological products to describe the current hydropower system and potential sites for Run-of-River projects. The findings identified 11,965 potential sites for Run-of-River plants. Second, we executed and validated a hydrological model to estimate historical daily streamflows (1981–2020) and hydropower parameters for actual and potential sites. It was determined there is an installed capacity of 5.2 GW in the current hydropower system and a total potential capacity of 29.1 GW for Run-of-River plants, mainly distributed in the northern and central Andes. Finally, we evaluated future changes driven by ten global climate models under three emission scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5), compared with the baseline period of 1981–2010 with two future time slices. The main results about capacity indicated that operational hydroelectric plants (Run-of-River plants) are projected to decrease by 0.5 to −5.4% (−7.2 to −2.2%) during 2036–2065 and by −9.2 to 3.8% (1.8 to −11.9%) during 2071–2100. These outcomes provide relevant information to support policymakers in addressing sustainable development gaps in the coming decades and stakeholders involved in the implementation and mitigation of climate change impacts on hydropower projects in Peru. Full article

This article proposes the concept of an integrated system consisting of two components: a small hydropower plant (SHPP) and a solar power plant (SPP), where the SHPP operates as a pumped-storage hydropower plant, and the SPP supplies energy for lifting water to the upper reservoir. A methodology is proposed for evaluating the joint operation of a solar power plant and a small hydropower plant. The methodology is based on modeling the electricity generation processes of combined solar and small hydropower plants. Additionally, a novel hybrid method is proposed for identifying interval models of small hydropower plants (SHPPs) and solar power plants (SPPs). This method integrates a metaheuristic algorithm for model structure synthesis, inspired by the behavioral model of a bee colony, with gradient-based methods for parameter identification. Using the proposed method, interval models have been developed for both small hydropower plants and the electricity generation of solar power plants. This study confirms the feasibility of using interval models to describe the relationship between electricity generation in a small hydropower plant and factors such as head difference, reactive power, and water level in the reservoir (i.e., available water resources). Furthermore, a mathematical model in the form of a difference equation is used to describe the daily electricity generation of a solar power plant. This model accounts for the characteristics of compressors that pump water from the lower to the upper reservoir. Based on the developed models, an assessment is conducted on the efficiency of the pumped-storage SHPP in ensuring operational stability during peak loads in the power grid and addressing seasonal variations. Full article

Ensuring secure and efficient water level monitoring is critical for the intelligent management of hydropower plants, especially in challenging indoor environments. Existing methods, which are tailored for open areas with optimal conditions (adequate lighting, absence of debris interference, etc.), frequently falter in scenarios characterized by poor lighting, water vapor, and confined spaces. To address this challenge, this study introduces a robust indoor water level monitoring framework specifically for hydropower plants. This framework integrates a temporal super-resolution technique with an improved Yolov5 model. Specifically, to enhance the quality of indoor monitoring images, we propose a temporal super-resolution enhancement module. This module processes low-resolution water-level images to generate high-resolution outputs, thereby enabling reliable detection even in suboptimal conditions. Furthermore, unlike existing complex model-based approaches, our enhanced, lightweight Yolov5 model, featuring a small-scale feature mapping branch, ensures real-time monitoring and accurate detection across a variety of conditions, including daytime, nighttime, misty conditions, and wet surfaces. Experimental evaluations demonstrate the framework’s high accuracy, reliability, and operational efficiency, with recognition speeds reaching O(n). This approach is suitable for deployment in emerging intelligent systems, such as HT-for-Web analysis software 0.2.3 and warning platforms, providing vital support for hydropower plant security and emergency management. Full article

This article presents the simulation results of synchronization of a permanent magnet synchronous generator (PMSG) dedicated for a hydroelectric plant without power converter devices. The proposed machine design allows to connect a generator to the grid in two different ways. With the first method, the machine is connected to the grid in a similar way as in the case of an electrically excited synchronous generator. The second method is a direct line-start process based on asynchronous torque—similar to asynchronous motor start. Both methods can be used alternately. The advantages of the presented design are elimination of converter devices for starting the PMSG, possibility of use in small and medium hydroelectric power plants, operation with a high efficiency and high power factor in a wide range of generated power, and smaller dimensions in comparison to the generators currently used. The described rotor design allows for the elimination of capacitor batteries for compensation of reactive power drawn by induction generators commonly used in small hydroelectric plants. In addition, due to the high efficiency of the PMSG, high power factor, and appropriately selected design, the starting current during synchronization is smaller than in the case of an induction generator, which means that the structural elements wear out more slowly, and thus, the generator’s service life is increased. In this work, it is shown that PMSG with a rotor cage should have permanent magnets with an increased temperature class in order to avoid demagnetization of the magnets during asynchronous start-up. In addition, manufacturers of such generators should provide the number of start-up cycles from cold and warm states in order to avoid shortening the service life of the machine. The main objective of the article is to present the methods of synchronizing a generator of such a design (a rotor with permanent magnets and a starting cage) and their consequences on the behavior of the machine. The presented design allows synchronization of the generator with the network in two ways. The first method enables synchronization of the generator with the power system by asynchronous start-up, i.e., obtaining a starting torque exceeding the braking torque from the magnets. The second method of synchronization is similar to the method used in electromagnetically excited generators, i.e., before connecting, the rotor is accelerated to synchronous speed by means of a water turbine, and then, the machine is connected to the grid by switching on the circuit breaker. This paper presents electromagnetic phenomena occurring in both cases of synchronization and describes the influence of magnet temperature on physical quantities. Full article

This study explores the application of Temporal Fusion Transformers (TFTs) to improve the predictability of hourly potential hydropower production for a small run–of–the–river hydropower plant in Portugal. Accurate hourly power forecasts are essential for optimizing participation in the spot electricity market, where deviations incur penalties. This research introduces the novel application of the TFT, a deep–learning model tailored for time series forecasting and uncovering complex patterns, to predict hydropower production based on meteorological data, historical production records, and plant capacity. Key challenges such as filtering observed hydropower outputs (to remove strong, and unpredictable human influence) and adapting the historical series to installed capacity increases are discussed. An analysis of meteorological information from several sources, including ground information, reanalysis, and forecasting models, was also undertaken. Regarding the latter, precipitation forecasts from the European Centre for Medium–Range Weather Forecasts (ECMWF) proved to be more accurate than those of the Global Forecast System (GFS). When combined with ECMWF data, the TFT model achieved significantly higher accuracy in potential hydropower production predictions. This work provides a framework for integrating advanced machine learning models into operational hydropower scheduling, aiming to reduce classical modeling efforts while maximizing energy production efficiency, reliability, and market performance. Full article

In order to enhance the overall power generation efficiency of cascade hydropower, it is essential to conduct modelling optimization of its in-plant operation. However, existing studies have devoted minimal attention to the detailed modelling of turbine operating performance curves within the in-plant economic operation model. This represents a significant challenge to the practical application of the optimization results. This study presents a refined model of a hydraulic turbine operating performance curve, which was established by combining a particle swarm optimization (PSO) algorithm and a backpropagation (BP) neural network. The model was developed using a cascade small hydropower group as an illustrative example. On this basis, an in-plant economic operation model of a cascade small hydropower group was established, which is based on the principle of ’setting electricity by water’ and has the goal of maximizing power generation. The model was optimized using a genetic algorithm, which was employed to optimize the output of the units. In order to ascertain the efficacy of the methodology proposed in this study, typical daily operational scenarios of a cascade small hydropower group were selected for comparison. The results demonstrate that, in comparison with the actual operational strategy, the proposed model and method enhance the total output by 3.38%, 2.11%, and 3.56%, respectively, across the three typical scenarios. This method enhances the efficiency of power generation within the cascade small hydropower group and demonstrates substantial engineering application value. Full article

This article devises the Artificial Intelligence (AI) methods of designing models of short-term forecasting (in 12 h and 24 h horizons) of electricity production in a selected Small Hydropower Plant (SHP). Renewable Energy Sources (RESs) are difficult to predict due to weather variability. Electricity production by a run-of-river SHP is marked by the variability related to the access to instantaneous flow in the river and weather conditions. In order to develop predictive models of an SHP facility (installed capacity 760 kW), which is located in Southern Poland on the Skawa River, hourly data from nearby meteorological stations and a water gauge station were collected as explanatory variables. Data on the water management of the retention reservoir above the SHP were also included. The variable to be explained was the hourly electricity production, which was obtained from the tested SHP over a period of 3 years and 10 months. Obtaining these data to build models required contact with state institutions and private entrepreneurs of the SHP. Four AI methods were chosen to create predictive models: two types of Artificial Neural Networks (ANNs), Multilayer Perceptron (MLP) and Radial Base Functions (RBFs), and two types of decision trees methods, Random Forest (RF) and Gradient-Boosted Decision Trees (GBDTs). Finally, after applying forecast quality measures of Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Coefficient of Determination (R²), the most effective model was indicated. The decision trees method proved to be more accurate than ANN models. The best GBDT models’ errors were MAPE 3.17% and MAE 9.97 kWh (for 12 h horizon), and MAPE 3.41% and MAE 10.96 kWh (for 24 h horizon). MLPs had worse results: MAPE from 5.41% to 5.55% and MAE from 18.02 kWh to 18.40 kWh (for 12 h horizon), and MAPE from 7.30% to 7.50% and MAE from 24.12 kWh to 24.83 kWh (for 24 h horizon). Forecasts using RBF were not made due to the very low quality of training and testing (the correlation coefficient was approximately 0.3). Full article

In light of Switzerland’s 2050 energy goals, the nation aims to boost its domestic hydroelectric output, notably focusing on small-scale hydroelectric power plants. Concurrently, there is an effort to renovate hydroelectric plants to make them more environmentally friendly, emphasizing ecological flow regulation to improve river conditions. This study explores the application of a non-proportional flow allocation method to better assess both ecological and economic outcomes. Unlike traditional fixed or proportional flow methods, this approach allows for a more dynamic balance between hydropower generation and riverine ecosystem health. This study focuses on two key species, brown trout and grayling. In particular, this work highlighted that trout are better suited for low-flow conditions (Weighted Usable Area, WUA, peaks below 1 m³/s), while grayling require significantly higher flows (WUA peaks over 4.5 m³/s). This disparity in habitat preferences raises concerns about the current reliance on single-species models, emphasizing the need for multi-species ecological assessment in future studies. When applied to a small hydropower plant in the Swiss Jura, the non-proportional flow method resulted in an improvement of ecological conditions of at least 37.7%, which consequently led to a reduction of the hydroelectric production of at least 10%. Through strategic upgrades to the facility (e.g., by minimizing hydraulic losses, implementing more efficient turbines, or incorporating photovoltaic panels over water channels), it is possible to simultaneously enhance both energy output and environmental sustainability. These findings suggest that non-proportional flow allocation holds significant potential for broader use in sustainable hydropower management, providing a pathway toward meeting both energy production and ecological conservation goals. Full article

The impacts of hydropower plants and their reservoirs on floodplains can potentially create new environmental filters and reduce the exchange of organisms and access to habitats. In this study, we aimed to compare the fish assemblage associated with aquatic macrophytes between floodplain lakes under natural conditions and a regulated floodplain lake in the Environmental Protection Area of Rio Pandeiros, Brazil. We tested the hypothesis that in the regulated floodplain lake, there would be a lower richness and a greater of abundance of macrophytes and fish than is natural. We also verified the influence of the seasons, macrophyte bank richness, and biomass on the fish assemblage abundance. The fish assemblages differed between the regulated and natural floodplains due to the higher richness and abundance of fish in the natural floodplains. The presence of non-native and generalist species in the regulated floodplain influenced the dissimilarity between the floodplains. Migratory species have been found only in natural floodplains. Fish abundance was negatively related to macrophyte richness on the regulated lake. There was a lower fish abundance and macrophyte richness in the regulated lake. There was no evidence that macrophyte biomass affected the abundance and richness of fishes. Our results confirm that the Pandeiros small hydroelectric dam affects the fishes’ assemblage and the macrophyte community, since the regulated floodplain lake has a lower richness and abundance of fish. The regulated floodplain lake is connected to a reservoir created by a small hydroelectric dam, which will be removed in the coming years. The removal of this dam might change these dynamics, and this must be evaluated when the change is implemented. Full article

This article provides a comparative analysis of pendulum and radial micro-hydropower plants. The novelty of this study lies in the comparative analysis of units that are fundamentally different in design to achieve the most rational option for low-speed rivers. It has been established that a pendulum micro-hydropower plant has a high torque with relatively small dimensions but operates cyclically. At a diameter of 1 m and a blade area of 0.3 m², the peak torque was 140 N·m. At the same time, the design is sensitive to the blade area and at 0.6 m² and a lever length of 1.5 m, the torque reached 430 N·m. A radial micro-hydropower plant has lower torque but operates constantly. At an area of 1.23 m² and a diameter of 1 m, the torque was 40.4 N·m. Accordingly, in terms of specific area with a diameter of 1 m, a pendulum micro-hydropower plant has up to 12 times more torque. It has been established that the pendulum hydropower plant best satisfies the requirements for converting a low river speed into high revolutions of a current generator. Full article

During the 1950s, numerous small-capacity hydroelectric power plants were built in Spain. Seventy-five years on, it must now be decided whether to continue their operation or demolish them. In order to provide a valid answer, it is necessary to have access to decision-making tools that enable sustainable economic and environmental decision making. The present work proposes a methodology that employs an economic indicator of life cycle cost and environmental indicators of carbon footprint and embodied energy by means of life cycle data analysis. Quantification of the impacts was carried out with the support of construction cost databases and the PREDICE software tool for the quantification of environmental impacts incorporated into maintenance tasks. The case study of the “Cerrajón” power plant was analyzed, where historical hydrological cycles were considered. A life cycle scenario was evaluated in which renovation extended the life of the power plant by a further 75 years. The results show savings in environmental impacts with respect to the impacts of the Spanish energy mix of up to 175 kgCO₂ per MWh produced, although no economic benefit was found. It was also shown that in climate change scenarios, the profit price breakeven increases. Rehabilitation appears to present the best choice when combining the two criteria. Full article

In the last two decades, Peru has experienced a process of transformation in the sources of its energy matrix, increasing the participation of clean energy such as solar photovoltaic (PV), on-shore wind, biomass, and small hydro. However, hydropower and natural gas remain the main sources of electricity, whereas off-shore wind, biogas, waves, tidal, and geothermal sources are currently underdeveloped. This article presents the enormous potential of Peru for the generation of electrical energy from a solar source equivalent to 25 GW, as it has in one of the areas of the world with the highest solar radiation throughout the year. In addition, this article presents the main advantages, benefits, and considerations of the implementation of solar photovoltaic technology, with emphasis on (i) the potential of solar energy, showing the available potential and an installed capacity by the year 2024 equivalent to 398 MW, (ii) current solar energy sources, characterizing existing industrial solar photovoltaic (PV) energy plants, and (iii) future solar energy facilities projections, stating the portfolio of solar renewable energy plant projects to be implemented in the future considering an installed capacity of 7.2 GW by 2028. Additionally, lessons learned, challenges, and directions for the future development of solar energy in the country are presented. Finally, the article concludes that if Peru takes advantage of solar potential by considering a sustainable future perspective and implementing strategic land-use planning, the southern region will be transformed into a world-class territory for renewable energy development considering the hybridization of concentrated solar power (CSP) systems with solar photovoltaic (PV) systems and solar energy storage systems. Full article