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Research Status of Operation and Management of Hydropower Station

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydraulics and Hydrodynamics".

Deadline for manuscript submissions: 20 November 2025 | Viewed by 4602

Special Issue Editors


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Guest Editor
College of Energy and Power Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Interests: hydropower; simulation and modeling; performance evaluation; diagnosis and control; coordinated operation
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Guest Editor
School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan, China
Interests: hydropower; pumped storage; multi-energy system; modeling; control; intelligent diagnosis; operation and management

Special Issue Information

Dear Colleagues,

A new type of power system based on renewable energy is one of the effective ways to achieve carbon peaking and carbon neutrality. With the continuous development and improvement of new power systems, the mission of hydropower stations has gradually changed from ‘power supply’ to ‘power supply + grid regulation’. Against this background, this Special Issue is dedicated to publishing original research related to the operation and management of hydropower stations or pumped storage power stations. Research covering the following areas is particularly welcome: combined optimal operation of hydropower and new energy sources, optimal control of hydropower/pumped storage units, system integration and stability analysis, intelligent monitoring, early warning and diagnosis. The aim of this Special Issue is to provide researchers, operators and policy makers in this field with new insights into the optimal operation of hydropower energy under the new power system, in order to further enhance the regulating role of hydropower in maintaining the stability of the power grid, and to effectively respond to the challenges posed by the integration of renewable energy sources, such as wind and solar energy, into the grid.

Dr. Dong Liu
Dr. Yanhe Xu
Guest Editors

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Keywords

  • conventional hydropower stations
  • cascade hydropower stations
  • pumped storage power stations
  • non-linear modelling
  • combined operation
  • optimal control
  • multi-energy systems
  • stability analysis
  • new power systems
  • performance evaluation
  • fault diagnosis
  • trend prediction and early warning
  • renewable energy
  • artificial intelligence
  • optimization algorithms

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Published Papers (7 papers)

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Research

19 pages, 2137 KiB  
Article
Optimal Configuration and Empirical Analysis of a Wind–Solar–Hydro–Storage Multi-Energy Complementary System: A Case Study of a Typical Region in Yunnan
by Yugong Jia, Mengfei Xie, Ying Peng, Dianning Wu, Lanxin Li and Shuibin Zheng
Water 2025, 17(15), 2262; https://doi.org/10.3390/w17152262 - 29 Jul 2025
Viewed by 183
Abstract
The increasing integration of wind and photovoltaic energy into power systems brings about large fluctuations and significant challenges for power absorption. Wind–solar–hydro–storage multi-energy complementary systems, especially joint dispatching strategies, have attracted wide attention due to their ability to coordinate the advantages of different [...] Read more.
The increasing integration of wind and photovoltaic energy into power systems brings about large fluctuations and significant challenges for power absorption. Wind–solar–hydro–storage multi-energy complementary systems, especially joint dispatching strategies, have attracted wide attention due to their ability to coordinate the advantages of different resources and enhance both flexibility and economic efficiency. This paper develops a capacity optimization model for a wind–solar–hydro–storage multi-energy complementary system. The objectives are to improve net system income, reduce wind and solar curtailment, and mitigate intraday fluctuations. We adopt the quantum particle swarm algorithm (QPSO) for outer-layer global optimization, combined with an inner-layer stepwise simulation to maximize life cycle benefits under multi-dimensional constraints. The simulation is based on the output and load data of typical wind, solar, water, and storage in Yunnan Province, and verifies the effectiveness of the proposed model. The results show that after the wind–solar–hydro–storage multi-energy complementary system is optimized, the utilization rate of new energy and the system economy are significantly improved, which has a wide range of engineering promotion value. The research results of this paper have important reference significance for the construction of new power systems and the engineering design of multi-energy complementary projects. Full article
(This article belongs to the Special Issue Research Status of Operation and Management of Hydropower Station)
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13 pages, 6786 KiB  
Article
Hydropower Microgeneration in Detention Basins: A Case Study of Santa Lúcia Basin in Brazil
by Azuri Sofia Gally Koroll, Rodrigo Perdigão Gomes Bezerra, André Ferreira Rodrigues, Bruno Melo Brentan, Joaquín Izquierdo and Gustavo Meirelles
Water 2025, 17(15), 2219; https://doi.org/10.3390/w17152219 - 24 Jul 2025
Viewed by 378
Abstract
Flood control infrastructure is essential for the development of cities and the population’s well-being. The goal is to protect human and economic resources by reducing the inundation area and controlling the flood level and peak discharges. Detention basins can do this by storing [...] Read more.
Flood control infrastructure is essential for the development of cities and the population’s well-being. The goal is to protect human and economic resources by reducing the inundation area and controlling the flood level and peak discharges. Detention basins can do this by storing a large volume of water to be released after the peak discharge. By doing this, a large amount of energy is stored, which can be recovered via micro-hydropower. In addition, as the release flow is controlled and almost constant, Pumps as Turbines (PAT) could be a feasible and economic option in these cases. Thus, this study investigates the feasibility of micro-hydropower (MHP) in urban detention basins, using the Santa Lúcia detention basin in Belo Horizonte as a case study. The methodology involved hydrological modeling, hydraulic analysis, and economic and environmental assessment. The results demonstrated that PAT selection has a crucial role in the feasibility of the MHP, and exploiting rainfall with lower intensities but higher frequencies is more attractive. Using multiple PATs with different operating points also showed promising results in improving energy production. In addition to the economic benefits, the MHP in the detention basin produces minimal environmental impact and, as it exploits a wasted energy source, it also reduces the carbon footprint in the urban water cycle. Full article
(This article belongs to the Special Issue Research Status of Operation and Management of Hydropower Station)
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25 pages, 5428 KiB  
Article
Multi-Objective Optimal Dispatch of Hydro-Wind-Solar Systems Using Hyper-Dominance Evolutionary Algorithm
by Mengfei Xie, Bin Liu, Ying Peng, Dianning Wu, Ruifeng Qian and Fan Yang
Water 2025, 17(14), 2127; https://doi.org/10.3390/w17142127 - 17 Jul 2025
Viewed by 233
Abstract
In response to the challenge of multi-objective optimal scheduling and efficient solution of hydropower stations under large-scale renewable energy integration, this study develops a multi-objective optimization model with the dual goals of maximizing total power generation and minimizing the variance of residual load. [...] Read more.
In response to the challenge of multi-objective optimal scheduling and efficient solution of hydropower stations under large-scale renewable energy integration, this study develops a multi-objective optimization model with the dual goals of maximizing total power generation and minimizing the variance of residual load. Four complementarity evaluation indicators are used to analyze the wind–solar complementarity characteristics. Building upon this foundation, Hyper-dominance Evolutionary Algorithm (HEA)—capable of efficiently solving high-dimensional problems—is introduced for the first time in the context of wind–solar–hydropower integrated scheduling. The case study results show that the HEA performs better than the benchmark algorithms, with the best mean Hypervolume and Inverted Generational Distance Plus across nine Walking Fish Group (WFG) series test functions. For the hydro-wind-solar scheduling problem, HEA obtains Pareto frontier solutions with both maximum power generation and minimal residual load variance, thus effectively solving the multi-objective scheduling problem of the hydropower system. This work provides a valuable reference for modeling and efficiently solving the multi-objective scheduling problem of hydropower in the context of emerging power systems. This work provides a valuable reference for the modeling and efficient solution of hydropower multi-objective scheduling problems in the context of emerging power systems. Full article
(This article belongs to the Special Issue Research Status of Operation and Management of Hydropower Station)
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25 pages, 4641 KiB  
Article
Progressive Linear Programming Optimality Method Based on Decomposing Nonlinear Functions for Short-Term Cascade Hydropower Scheduling
by Jia Lu, Zhou Fang, Zheng Zhang, Yaxin Liu, Yang Xu, Tao Wang and Yuqi Yang
Water 2025, 17(10), 1441; https://doi.org/10.3390/w17101441 - 10 May 2025
Viewed by 438
Abstract
Short-term optimal scheduling of cascade hydropower stations enhances their flexible regulation and power generation capabilities. However, nonlinear function relationships and multistage and hydraulic interdependencies present significant challenges, resulting in considerable solution errors, premature convergence, and high computational demands. This study proposes a progressive [...] Read more.
Short-term optimal scheduling of cascade hydropower stations enhances their flexible regulation and power generation capabilities. However, nonlinear function relationships and multistage and hydraulic interdependencies present significant challenges, resulting in considerable solution errors, premature convergence, and high computational demands. This study proposes a progressive linear programming method that decomposes nonlinear functions to address these challenges. First, to accurately represent nonlinear functions and mitigate computational complexity, the entire feasible domain is partitioned into multiple contiguous subdomains in which nonconvex nonlinear functions within each subdomain can be equivalently replaced by linear relationships. Second, a progressive linear programming optimization algorithm is devised to prevent premature convergence, utilizing continuous subdomains rather than discrete points as state variables and incorporating the progressive optimality principle. Finally, to increase the solution efficiency, a dimensionality reduction strategy via the feasible domain state dynamic acquisition method is presented and optimized after excluding the infeasible states in each stage. The simulation of three cascade hydropower stations in a river basin in southwest China shows that the proposed method can achieve a superior peak regulation effect compared to the conventional mixed integer linear programming and progressive optimality algorithm. During the dry and wet seasons, the residual load peak–valley differences at the three stations are reduced by 612 MW and 521 MW compared to the MILP and 1889 MW and 2439 MW compared to the POA, which underscores the effectiveness of the method in optimizing the short-term scheduling of cascade hydropower stations. Full article
(This article belongs to the Special Issue Research Status of Operation and Management of Hydropower Station)
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17 pages, 4574 KiB  
Article
A Hydraulic Turbine Fault Diagnosis Method Based on Synchrosqueezed Wavelet Transform and SE-ResNet
by Ye Liu, Yanhe Xu, Jie Liu and Xinqiang Niu
Water 2025, 17(3), 447; https://doi.org/10.3390/w17030447 - 5 Feb 2025
Viewed by 817
Abstract
To tackle the challenges associated with conventional methods of diagnosing hydraulic turbine faults, which depend heavily on expert knowledge and exhibit low efficiency and precision, a model for detecting hydraulic turbine faults has been developed that integrates the synchrosqueezed wavelet transform (SWT) with [...] Read more.
To tackle the challenges associated with conventional methods of diagnosing hydraulic turbine faults, which depend heavily on expert knowledge and exhibit low efficiency and precision, a model for detecting hydraulic turbine faults has been developed that integrates the synchrosqueezed wavelet transform (SWT) with SE-ResNet. Initially, a 1D non-stationary vibration signal is converted into a high-frequency time–frequency representation in two dimensions using SWT, which then acts as the input for the convolutional neural network. Secondly, a model based on SE-ResNet is designed, incorporating an attention mechanism that enhances the extraction of features from two-dimensional images, thereby increasing the emphasis on crucial features and bolstering the model’s representation capabilities. Finally, results related to fault detection are produced via the softmax layer. To evaluate the proposed model’s efficiency, two datasets were utilized for the experiments conducted, one sourced from Case Western Reserve University and the other from hydraulic turbine vibration signals. Compared to conventional approaches, this technique demonstrates significant practicality and effective convergence characteristics, offering considerable value in real-world applications. Full article
(This article belongs to the Special Issue Research Status of Operation and Management of Hydropower Station)
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20 pages, 5026 KiB  
Article
Numerical Simulation Study on Dominant Factors of Surge Hazards in Semi-Submerged Landslides
by Jie Lei, Weiya Xu, Qingfu Huang, Lei Tian, Fugang Zhao and Changhao Lyu
Water 2025, 17(1), 22; https://doi.org/10.3390/w17010022 - 25 Dec 2024
Cited by 1 | Viewed by 836
Abstract
Landslide-generated surge waves are significant natural hazards, posing severe risks to engineering safety. Despite extensive research on the dynamics of landslide-generated waves, studies analyzing controlling factors and their mechanisms remain limited, leaving key influencing processes inadequately understood. This study utilizes computational fluid dynamics [...] Read more.
Landslide-generated surge waves are significant natural hazards, posing severe risks to engineering safety. Despite extensive research on the dynamics of landslide-generated waves, studies analyzing controlling factors and their mechanisms remain limited, leaving key influencing processes inadequately understood. This study utilizes computational fluid dynamics (CFD) to perform a numerical simulation of a semi-submerged landslide in a hydropower station reservoir area. The research systematically investigated the effects of key variables, including slide volume, velocity, centroid height, and water depth, on the behavior of semi-submerged landslide-generated surge waves. Results demonstrate a positive correlation of slide volume, velocity, and centroid height with the initial wave height and run-up on the opposing shoreline. However, the impact of water depth reveals a more complex pattern, exhibiting distinct surge characteristics in the near-field and far-field zones. Via correlation and sensitivity analyses, this study elucidated the relationships between these factors and surge dynamics, identifying the primary factors influencing the size of the semi-submerged landslide-generated surge. The findings provide critical insights for predicting and mitigating surge disasters, offering both theoretical foundations and practical application value for landslide disaster prevention and management. Full article
(This article belongs to the Special Issue Research Status of Operation and Management of Hydropower Station)
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17 pages, 13769 KiB  
Article
A New Procedure for Determining Monthly Reservoir Storage Zones to Ensure Reliable Hourly Hydropower Supply
by Shuangquan Liu, Jingzhen Luo, Kaixiang Fu, Huixian Li, Guoyuan Qian, Wang Xia and Jinwen Wang
Water 2024, 16(24), 3605; https://doi.org/10.3390/w16243605 - 14 Dec 2024
Viewed by 948
Abstract
The uncertainty of natural inflows and market behavior challenges ensuring a reliable power balance in hydropower-dominated electricity markets. This study proposes a novel framework integrating hourly load balancing on typical days into a monthly scheduling model solved with Gurobi11.0.1 to evaluate demand-met reliability [...] Read more.
The uncertainty of natural inflows and market behavior challenges ensuring a reliable power balance in hydropower-dominated electricity markets. This study proposes a novel framework integrating hourly load balancing on typical days into a monthly scheduling model solved with Gurobi11.0.1 to evaluate demand-met reliability across storage and inflow states. By employing total storage as a system state to reduce dimensional complexity and simulating future runoff scenarios based on current inflows, the method performs multi-year statistical simulations to assess reliability over the following year. Applied to a system of 39 hydropower reservoirs in China, the case studies of present models and procedures suggest: (1) controlling reservoir storage levels during the dry season is crucial for ensuring the power demand-met rate in the following year, with May being the most critical month; (2) the power demand-met rate does not monotonically increase with higher storage levels—there is an optimal storage level that maximizes the demand-met rate; and (3) June and October offer the greatest flexibility in storage adjustment to achieve the highest demand-met reliability. Full article
(This article belongs to the Special Issue Research Status of Operation and Management of Hydropower Station)
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