Optimal allocation of flood prevention storage and dynamic operation of water levels to increase cascade reservoir hydropower generation

Yuzuo Xie, Shenglian Guo, Sirui Zhong, Zhipeng He, Pan Liu and Yanlai Zhou

Renewable Energy, 2024, vol. 228, issue C

Abstract: The existing trade-off between flood control and water conservation measured by flood limited water level (FLWL) during flood season hinders multi-reservoir system from realizing comprehensive benefits. To overcome this barrier, we reasonably allocated the complementary flood prevention storage based on the aggregation-decomposition technique, theoretically deduced the mathematical formula of power generation variation simplified from the cascade reservoir operation model, and dynamically operated reservoir water levels considering the inflow forecasting information. The Wudongde (WDD) ∼ Baihetan (BHT) ∼ Xiluodu (XLD) ∼ Xiangjiaba (XJB) cascade reservoirs in the downstream Jinsha River in China is selected as the case study. Results demonstrate that: (1) The derived power generation function monotonically increases only with the growth of the pre-discharge water volume. (2) The reduced proportion of the flood prevention storage of the WDD (or XJB) is favorable to boost the hydroelectric benefits of the WDD ∼ BHT (or XLD ∼ XJB) cascade reservoirs. Optimal allocation of flood prevention storage can increase 1.933 billion kW∙h power generation annually (+2.15 %) for the WDD ∼ BHT ∼ XLD ∼ XJB cascade reservoirs. (3) Further cooperated with dynamic operation of water levels, the WDD ∼ BHT ∼ XLD ∼ XJB cascade reservoirs can totally generate 5.925 billion kW∙h more hydropower annually (+6.60 %) using effective 5-day lead-time inflow forecasting information, while maintaining the design flood prevention standards.

Keywords: Cascade reservoirs; Hydropower generation; Flood prevention storage; Flood control risk; Dynamic operation; Downstream Jinsha river (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:228:y:2024:i:c:s0960148124007444

DOI: 10.1016/j.renene.2024.120676

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