| 引用本文: | 钟 浩,刘浩宇,石 宇,等.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.[点击复制] |
| ZHONG Hao,LIU Haoyu,SHI Yu,et al.Optimal capacity allocation of pumped storage reservoirs considering the synergistic effect of small hydropower and agricultural irrigation in river basins[J].Power System Protection and Control,2025,53(11):1-13[点击复制] |
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| 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 |
| 钟浩1,2,刘浩宇1,2,石宇3,王秋杰1,2,张永豪1,2,汪星火1,2 |
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| (1.三峡大学梯级水电站运行与控制湖北省重点实验室，湖北 宜昌 443002;2.三峡大学电气与新能源学院，
湖北 宜昌 443002;3.国网湖南省电力公司长沙供电分公司，湖南 长沙 410035) |
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| 摘要: |
| 为缓解偏远地区电力系统灵活性资源短缺问题，减少风、光电站因其出力波动性和不确定性造成的经济损失，提出一种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方法。首先，充分挖掘农排灌溉站在不同季节的闲置容量，联合小水电构建抽蓄体。然后，以场景集描述不同季节风、光、水的不确定性。基于Gale-Shapley双边匹配机制，风、光电站作为选择方，以经济收益最大为目标建立优化模型。以抽蓄体作为接受方，建立双层优化配置模型。上层以年利润最大为目标建立水库容量配置模型，下层以聚合收益最大为目标建立聚合体优化模型。最后，采用粒子群算法与CPLEX求解器对模型进行求解。算例分析表明，所提方法能充分发挥抽蓄体的灵活调节能力，有效应对风、光出力的波动性和不确定性。 |
| 关键词: 农排灌溉站 小水电 抽蓄体 不确定性 优化配置 |
| DOI：10.19783/j.cnki.pspc.241071 |
| 投稿时间：2024-08-10修订日期：2024-09-26 |
| 基金项目:国家自然科学基金项目资助(52307109)；湖北省自然科学基金联合基金项目资助(2022CFD167) |
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| Optimal capacity allocation of pumped storage reservoirs considering the synergistic effect of small hydropower and agricultural irrigation in river basins |
| ZHONG Hao1,2,LIU Haoyu1,2,SHI Yu3,WANG Qiujie1,2,ZHANG Yonghao1,2,WANG Xinghuo1,2 |
| (1. Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydro-power Station, China Three Gorges University,
Yichang 443002, China; 2. College of Electrical Engineering & New Energy, China Three Gorges University, Yichang
443002, China; 3. Changsha Power Supply Branch, State Grid Hunan Electric Power Company, Changsha 410035, China) |
| 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. |
| Key words: agricultural irrigation station small hydropower pumped storage system uncertainty optimal allocation |
