Search Results (776)

The evolution of the generation mix towards deep decarbonization poses pressing questions about the role of hydropower and its possible share in the future mix. Most technical–economic analyses of deeply decarbonized systems either rule out hydropower growth due to lack of additional hydro resources or take it into account in terms of additional reservoir capacity. This paper analyzes a generation mix made of photovoltaic, wind, open-cycle gas turbines, electrochemical storage and hydroelectricity, focusing on the optimal generation mix’s reaction to different methane gas prices, hydroelectricity availabilities, pumped hydro reservoir capacities, and mean filling durations for hydro reservoirs. The key feature of the developed model is the sizing of both optimal peak power and reservoir energy content for hydropower. The results of the study point out two main insights. The first one, rather widely accepted, is that cost-effective decarbonization requires the greatest possible amount of hydro reservoirs. The second one is that, even in the case of totally exploited reservoirs, there is a strong case for increasing hydro peak power. Application of the model to the Italian generation mix (with 9500 MWp and 7250 MWp of non-pumped and pumped hydro fleets, respectively) suggests that it is possible to achieve methane shares of less than 10% if the operating costs of open-cycle gas turbines exceed 160 EUR/MWh and with non-pumped and pumped hydro fleets of at least 9200 MWp and 28,400 MWp, respectively. Full article

Hydroelectricity, one of the oldest and most potent forms of renewable energy, not only provides low-cost electricity for the grid but also preserves nature through flood control and irrigation support. Forecasting hydroelectricity generation is vital for utilizing alleviating resources effectively, optimizing energy production, and ensuring sustainability. This paper provides an innovative approach to hydroelectricity generation forecasting (HGF) of a 138 MW hydroelectric power plant (HPP) in the Eastern Mediterranean by taking electricity productions from the remaining upstream HPPs on the Ceyhan River within the same basin into account, unlike prior research focusing on individual HPPs. In light of tuning hyperparameters such as number of trees and learning rates, this paper presents a thorough benchmark of the state-of-the-art tree-based machine learning models, namely categorical boosting (CatBoost), extreme gradient boosting (XGBoost), and light gradient boosting machines (LightGBM). The comprehensive data set includes historical hydroelectricity generation, meteorological conditions, market pricing, and calendar variables acquired from the transparency platform of the Energy Exchange Istanbul (EXIST) and MERRA-2 reanalysis of the NASA with hourly resolution. Although all three models demonstrated successful performances, LightGBM emerged as the most accurate and efficient model by outperforming the others with the highest coefficient of determination (R²) (97.07%), the lowest root mean squared scaled error (RMSSE) (0.1217), and the shortest computational time (1.24 s). Consequently, it is considered that the proposed methodology demonstrates significant potential for advancing the HGF and will contribute to the operation of existing HPPs and the improvement of power dispatch planning. Full article

The study of aquatic biodiversity in the context of ecosystem sustainability is of urgent research importance, with several existing knowledge gaps. Among the under-studied groups are silica-scaled chrysophytes. Their cells are covered with silica scales and bristles/spines, the species-specific structure of which can be distinguished only by electron microscopy. In June and August 2024, samples were collected from a broad aquatic system comprising the southern part of Lake Baikal and a cascade of four reservoirs formed after the construction of hydroelectric dams on the Angara River flowing from Lake Baikal. Using electron microscopy, we identified 45 species of silica-scaled chrysophytes in phytoplankton in 2024, and the overall checklist was expanded to 57, accounting for interannual differences. Clear differences in species composition and richness were observed both between seasons and among reservoirs. Approximately a quarter of the recorded species were heterotrophs, which do not contribute to primary production, whereas 44% were phototrophs and 31% mixotrophs, both groups contributing to the Si cycle and to primary production. Continuous monitoring of reservoirs is essential for understanding the processes shaping silica-scaled chrysophytes diversity and may serve as an additional criterion for assessing the sustainability and transformation of freshwater ecosystems. Full article

Our study addresses how large-scale hydrological alterations shape zooplankton biodiversity in floodplain ecosystems, which are highly sensitive to changes in river connectivity. Following the operation of the Gabčíkovo hydroelectric power plant in the Danube inland delta, we examined the long-term responses of crustacean zooplankton communities, as these organisms are key indicators of hydromorphological disturbance. Based on previous evidence that river regulation often reduces habitat heterogeneity, we hypothesized that hydrological alterations in the Danube riverscape would promote increasing taxonomic and functional homogenization within sites, while simultaneously enhancing differentiation between sites over the past three decades. A total of 121 planktonic crustacean species were recorded across six monitored sites between 1991 and 2020, comprising 49 copepods and 72 cladocerans. Communities showed rising species richness, especially during the first decade of the hydropower plant’s operation. While overall richness increased, dam-induced hydromorphological changes triggered habitat-specific community shifts. In the main channel and adjacent parapotamal arm, taxonomic and functional homogenization occurred, dominated by resilient tychoplanktonic species with a gathering or secondary filter-feeding strategy. In contrast, isolated side arms experienced gradual eutrophication, favoring euplanktonic and primary filter-feeding taxa. The observed taxonomic and functional convergence within both habitat groups reflects the loss of connectivity and the cessation of artificial flooding. Full article

Hydraulic turbine governor servomotors in wind solar hydro complementary energy systems face significant fatigue failure challenges due to high-frequency regulation. This study develops an intelligent fatigue monitoring and prediction system based on strain sensors, specifically designed for the frequent regulation requirements of complementary systems. A multi-point monitoring network was constructed using resistive strain sensors, integrated with temperature and vibration sensors for multimodal data fusion. Field validation was conducted at an 18.56 MW hydroelectric unit, covering guide vane opening ranges from 13% to 63%, with system response time <1 ms and a signal-to-noise ratio of 65 dB. A simulation model combining sensor measurements with finite element simulation was established through fine-mesh modeling to identify critical fatigue locations. The finite element analysis results show excellent agreement with experimental measurements (error < 8%), validating the simulation model approach. The fork head was identified as the critical component with a stress concentration factor of 3.4, maximum stress of 51.7 MPa, and predicted fatigue life of 1.2 × 10⁶ cycles (12–16 years). The cylindrical pin shows a maximum shear stress of 36.1 MPa, with fatigue life of 3.8 × 10⁶ cycles (16–20 years). Monte Carlo reliability analysis indicates a system reliability of 51.2% over 20 years. This work provides an effective technical solution for the predictive maintenance and digital operation of wind solar hydro complementary systems. Full article

This work focuses on optimizing energy dispatch in a hydroelectric power plant (HPP) with a large number of generating units (GUs) and uncertainties caused by sediment accumulation in the water intakes. The study was realized at Jirau HPP, and integrates Markov Decision Processes (MDPs) and Particle Swarm Optimization (PSO) to minimize losses and enhance the performance of the plant’s GUs. Given the complexity of managing the huge number of units (50) and mitigating load losses from sediment accumulation, this approach enables real-time decision-making and optimizes energy dispatch. The methodology involves modeling the operational characteristics of the GUs, developing an objective function to minimize water consumption and maximize energy efficiency, and utilizing MDPs and PSO to find globally optimal solutions. Our results show that this methodology improves efficiency, reducing the turbinated flow by $0.9\%$ while increasing energy generation by $0.34\%$ and overall yield by $0.33\%$ compared to the HPP traditional method of dispatch over the analyzed period. This strategy could be adapted to varying operational conditions, and could provide a reliable framework for hydropower dispatch optimization. Full article

As the global shift toward renewable energy accelerates, large-scale energy storage is essential to balance intermittent supply and growing demand. While conventional Pumped Hydro Storage remains dominant, Underground Pumped Hydro Storage (UPHS) offers a promising alternative, particularly in flat regions with ample subsurface space. Southern Ontario, Canada, underlain by thick salt formations and a history of salt mining, presents favorable conditions for UPHS development, yet relative studies remain limited. This work presents the first UPHS-specific geomechanical feasibility assessment in the Canadian Salina Group, introducing a paired-cavern layout tied to Units B and A2 and explicitly capturing both elasto-plastic and creep behavior. Using COMSOL Multiphysics 6.3, a three-dimensional numerical model was developed featuring two vertically separated cylindrical caverns located in Unit B and the lower part of Unit A2. A 24 h operating cycle was simulated over a 10-year period, incorporating elasto-plastic deformation and salt creep. Minimum working pressures were varied to evaluate long-term cavern stability. The results show that a minimum pressure of 0.3 σ_v balances structural integrity and operational efficiency, with creep strain and volumetric convergence remaining within engineering limits. Beyond previous salt-cavern studies focused on hydrogen or CAES, this study provides the first coupled elasto-plastic and creep simulation tailored to UPHS operations in bedded salt, establishing a safe operating-pressure guideline and offering site-relevant design insights for modular underground energy storage systems in sedimentary basins. Full article

To accommodate the integration of emerging energy sources such as wind and solar power, hydroelectric units are increasingly required to operate across a broader range of conditions. This operational expansion often leads to elevated pressure pulsations within turbines under non-design conditions, resulting in intensified hydraulic vibrations and, in some cases, structural damage and overall stability concerns. In this study, the Shear Stress Transport (SST) k-ω turbulence model is employed to perform unsteady numerical simulation calculation of a Francis-99 mixed-flow model turbine operating at a head of 400 m. Simulations are conducted for three operating regimes: low-flow and low-load conditions, optimal conditions, and high-flow and high-load conditions. Internal flow in the full flow channel of the turbine and pressure pulsation in the full flow channel components is systematically analyzed. The findings indicate that under low-flow and low-load conditions, the ability of the runner blades to constrain the water flow is significantly decreased. Across all three operational scenarios, the dominant pressure pulsation frequencies observed in both the stationary and guide vane are 30f_n, primarily influenced by dynamic and static disturbance caused by the rotation of the runner’s long and short blades. In low-flow and low-load conditions, a low-frequency component at 0.2f_n, due to the existence of vortices in the draft tube, exhibits the highest amplitude—up to 0.6%—in the straight cone section. Within the runner, pressure pulsation frequencies are predominantly associated with the rotation of the guide vane. Conversely, the draft tube region is characterized by frequency components related to both the runner’s dynamic-static interaction at 30f_n and vortex-induced pulsations at 0.2f_n. Full article

To mitigate the impact of hydroelectric power plants on downstream fish migration, fish-friendly intakes, combining a low bar spacing rack and several bypasses, are implemented. There are still sites that can be improved thanks to a better bypass design. For this purpose, Computational Fluid Dynamics (CFD) can be a useful tool, even if such devices are still uncommon. This paper investigates the use of a 3D model based on the Reynolds-Averaged Navier–Stokes (RANS) equation for a single phase to simulate the flow in a real-scale water intake equipped with an inclined bar rack and three surface bypasses. The results of numerical simulations are compared to in situ measurements of flow velocities at four cross-sections along the rack, gauging the discharge flowing into the bypasses. The simulated velocities are in accordance with the velocities measured in situ, with a mean square error for the longitudinal velocity ($v_x$) of 0.034 (m²/s²) for the initial simulation and 0.021 (m²/s²) for the improved simulation. The split of the total bypass discharge between the three bypass entrances was satisfyingly predicted by the simulation with the true inlet velocity condition, showing the significant influence of upstream flow non-uniformity. Full article

The global energy crisis demands efficient electricity production solutions, especially for isolated communities where hydraulic energy can be harnessed sustainably. This paper presents a case study analyzing the efficiency of a 13,330 kW hydrogenerator, consisting of a bulb-type hydro-aggregate using the calorimetric method—a viable alternative when testing at nominal load is not feasible due to technical limitations. The method involves measuring the thermal energy absorbed by the cooling water under three operating conditions: no-load unexcited, no-load excited, and symmetric three-phase short-circuit. Measurements followed IEC standards and were conducted with high-precision instruments for temperature, flow, voltage, and current. The results quantify mechanical, ventilation, iron, and copper losses, as well as additional losses via radiation and convection. Thermal analysis revealed significant heat accumulation in the rotor and stator windings, indicating the need for improved cooling solutions. The calorimetric method enables efficiency evaluation without interrupting generator operation, offering a valuable tool for diagnostics, predictive maintenance, and informed decisions on modernization. Furthermore, integrating an intelligent operational control system could enhance efficiency and improve the quality of the supplied energy, supporting long-term sustainability in hydroelectric power generation. Full article

Micro-hydroelectric power plants play a fundamental role in microgrid systems and rural electrification projects based on non-conventional renewable energies, where the stability of the electricity supply and load variability are critical factors for efficient operation. This work focuses on analyzing the impact of electrical load variation on the performance of a 10 kW micro hydroelectric power plant equipped with a Pelton turbine coupled to an electric generator. The main objective is to characterize the behavior of the turbine–generator system under different operating conditions, evaluating the hydraulic performance of the turbine, the electrical performance of the generator, and the overall performance of the micro power plant. Key variables such as flow rate, pressure, shaft speed, mechanical torque, current, and electrical voltage are monitored, considering the effect of electrical consumption on each of them. The experimental methodology includes tests at different electrical loads connected to the generator, using the spear system, which allows the flow rate in the injector to be modulated. The results indicate that reducing the flow rate using the spear increases the torque on the shaft, as well as the electrical current and voltage, for the same energy demand. Likewise, it is observed that the electrical efficiency of the generator remains stable for shaft speeds above 400 rpm, while the overall efficiency of the turbine–generator improves by up to 25% at this same speed. However, a voltage drop of more than 8% is recorded when the electrical power consumption increases from 3 kW to 9 kW, which demonstrates the sensitivity of the system to load variations. This work provides a comprehensive view of the dynamic behavior of micro-hydraulic power plants under realistic operating conditions, proposing an experimental methodology that can be applied to the design, optimization, and control of small-scale hydroelectric systems. These results provide novel experimental evidence on how electrical load variations affect the global performance of P -based micro hydropower systems. Full article

To address the issues of reduced operational efficiency, shortened equipment lifespan, and significant safety hazards caused by bearing wear and blade cavitation in hydroelectric turbine generators due to prolonged high-load operation, this paper proposes a ResNet + self-attention-based acoustic fingerprint fault diagnosis algorithm for hydroelectric turbine generators. First, to address the issue of severe noise interference in acoustic signature signals, the ensemble empirical mode decomposition (EEMD) is employed to decompose the original signal into multiple intrinsic mode function (IMF) components. By calculating the correlation coefficients between each IMF component and the original signal, effective components are selected while noise components are removed to enhance the signal-to-noise ratio; Second, a fault identification network based on ResNet + self-attention fusion is constructed. The residual structure of ResNet is used to extract features from the acoustic signature signal, while the self-attention mechanism is introduced to focus the model on fault-sensitive regions, thereby enhancing feature representation capabilities. Finally, to address the challenge of model hyperparameter optimization, a Bayesian optimization algorithm is employed to accelerate model convergence and improve diagnostic performance. Experiments were conducted in the real working environment of a pumped-storage power station in Zhejiang Province, China. The results show that the algorithm significantly outperforms traditional methods in both single-fault and mixed-fault identification, achieving a fault identification accuracy rate of 99.4% on the test set. It maintains high accuracy even in real-world scenarios with superimposed noise and environmental sounds, fully validating its generalization capability and interference resistance, and providing effective technical support for the intelligent maintenance of hydroelectric generator units. Full article

The Ile River is the main water artery of the Lake Balkhash basin and the main fresh water resource supplying the south-eastern part of Kazakhstan. Increasing human economic activity makes it necessary to assess the anthropogenic load of the river on various ecosystems, including possible harmful effects. The assessment of anthropogenic load on the Ile River ecosystem was realized by the anthropogenic load fraction indicator and by the values of the chemical substance inflow modulus. For this purpose, the Ile River was divided into 3 sections: section I—from the border post HP Dobyn to 164 km above Kapshagai hydroelectric power plant (HPP); section II—between the points 164 km above and 37 km below Kapshagai HPP; and section III —from 37 km below HPP to Ushzharma village. The anthropogenic load strongly depends on the share of anthropogenic impact contributed by pollutants. Characteristic pollution components are copper, and in some cases zinc, ammonium, and nitrite nitrogen. The assessment of anthropogenic load also considers organic and biogenic substances in the chemical composition of river water. The variability in the volume of dissolved chemical inflows in different sections of the river made it possible to assess the transformation of anthropogenic load along the length of the Ile River. Full article

Rapid pressure fluctuations—known as hydraulic transients—occur during valve operations or load changes in turbines and pumps. The presence of biofouling, particularly caused by the golden mussel (Limnoperna fortunei), can intensify these effects and compromise the structural integrity of pressurized systems. This study experimentally evaluated the influence of such biofouling on pressure peaks during transient events in forced conduits. A hydraulic test rig was developed using PVC pipes with nominal diameters of 2½”, 3”, and 4”, tested under both clean conditions and with simulated biofouling printed in 3D, replicating mussel morphology. Results showed that, under the same initial flow rates, pressure peaks in biofouled pipes were significantly higher than in clean ones, especially in smaller diameters. To mitigate structural risks, the downstream shut-off valve closure time was modulated using a needle valve, effectively reducing peak pressures to levels closer to design limits. It is concluded that L. fortunei colonization alters transient hydraulic behavior and should be considered in the design and operation of systems vulnerable to biofouling, particularly in critical infrastructure such as water supply networks and hydroelectric power plants. Full article

High-precision measurement of water turbine flow is critical for ensuring the stable operation of hydropower stations and enhancing power generation efficiency. Ultrasonic transit-time flow meters, owing to their non-intrusive measurement capability and robust environmental adaptability, have gained widespread application in flow monitoring within hydropower settings. However, under complex operating conditions, their measurement accuracy remains susceptible to constraints imposed by installation environments, construction quality, and intrinsic device performance limitations. This review systematically examines the fundamental principles, system architecture, and typical classifications of ultrasonic transit-time flow meters for flow measurement. It critically evaluates key techniques for field deployment and methodologies for the accurate acquisition of geometric parameters. A primary focus lies in synthesizing and categorizing the principal sources of error affecting measurement accuracy, alongside an analysis of their underlying causes. Building upon this analysis, the review explores and summarizes current key technological pathways and engineering solutions aimed at enhancing ultrasonic transit-time flow meters’ measurement precision. Furthermore, it critically assesses the associated application challenges and emerging development trends (exploration of cutting-edge directions). Collectively, this work offers comprehensive theoretical reference and technical guidance to support the high-reliability application and optimized design of ultrasonic transit-time flow meters within the complex environments characteristic of hydropower stations. Full article