Unlocking hydropower synergies: Multi-objective optimization drawdown operation of cascade reservoirs

Fanqi Lin, Yanlai Zhou, Zhihao Ning, Pan Liu, Fi-John Chang and Chong-Yu Xu

Renewable Energy, 2025, vol. 247, issue C

Abstract: Reservoirs' seasonal drought-limited water level (SDLWL) plays a pivotal role during drawdown periods, crucial for balancing energy demands, mitigating drought impacts, and sustaining ecological health. This study proposes an innovative framework for cascade reservoirs’ multi-objective drawdown operation, uniquely designed to optimize the interplay between hydropower generation, drought resilience, and ecological conservation. The proposed framework was validated through a case study involving seven cascade reservoirs in the upper Yangtze River. First, SDLWLs for the drought season were determined using a month-by-month moving calculation method, which explains seasonal streamflow variations and hydraulic interdependencies between reservoirs. Next, a SDLWL-based multi-objective drawdown operation model was built and optimized using the Non-dominated Sorting Genetic Algorithm II, generating a Pareto set of solutions. Last, the entropy weight method was employed to pinpoint the optimal solution, enhancing hydropower synergies. The results are compelling: the optimal solution boosts average annual power generation by 6.26 billion kW·h, reflecting a 5.7 % increase, while simultaneously reducing average annual drought risk by 5.1 % and decreasing the average amended annual proportional flow deviation by 0.27, a 5.2 % improvement. This study offers a groundbreaking approach to reservoir drawdown operations and provides decision-makers with practical strategies to optimize renewable energy generation during critical periods.

Keywords: Drawdown operation; Multi-objective optimization; Seasonal drought-limited water level; Yangtze river; Cascade reservoirs (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:247:y:2025:i:c:s0960148125007591

DOI: 10.1016/j.renene.2025.123097

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