电力系统保护与控制2025，Vol.53Issue(11)：1-13,13.DOI:10.19783/j.cnki.pspc.241071
考虑流域小水电-农排灌溉聚合效应的抽蓄体水库容量优化配置
Optimal capacity allocation of pumped storage reservoirs considering the synergistic effect of small hydropower and agricultural irrigation in river basins
摘要
Abstract
In order to alleviate the shortage of flexible resources in power systems in remote areas and to reduce economic losses caused by the fluctuating and uncertain output of wind and solar power stations,this paper proposes an optimal capacity allocation method for pumped storage reservoirs considering the synergistic effect of small hydropower and agricultural irrigation station in river basins.First,the method fully utilizes the idle capacity of agricultural irrigation stations during different seasons and integrates them with small hydropower plants to form a pumped storage aggregation unit.Then,the uncertainties of wind,solar and hydro power in different seasons are modelled using scenario sets.Based on Gale-Shapley bilateral matching mechanism,wind and solar power stations act as the selection party and aim to maximize economic returns in the optimization model.The pumped storage aggregation unit acts as the receiving party and a two-layer optimal allocation model is established.The upper layer focuses on maximizing annual profits to determine reservoir capacity allocation,while the lower layer targets maximizing aggregation benefits to optimize the aggregated system.Finally,the combination of particle swarm optimization algorithm and CPLEX solver is utilized to solve the model.Case studies show that the proposed method can fully leverage the flexible regulation capability of the pumped storage aggregation unit and effectively cope with the volatility and uncertainty of wind and solar output.关键词
农排灌溉站/小水电/抽蓄体/不确定性/优化配置Key words
agricultural irrigation station/small hydropower/pumped storage system/uncertainty/optimal allocation引用本文复制引用
钟浩,刘浩宇,石宇,王秋杰,张永豪,汪星火..考虑流域小水电-农排灌溉聚合效应的抽蓄体水库容量优化配置[J].电力系统保护与控制,2025,53(11):1-13,13.基金项目
This work is supported by the National Natural Science Foundation of China(No.52307109). 国家自然科学基金项目资助(52307109) （No.52307109）
湖北省自然科学基金联合基金项目资助(2022CFD167) （2022CFD167）
