| 摘要: |
| 针对偏远地区小水电富集流域灵活性资源不足及风、光、水电站容量小、难以参与电力市场的问题，提出一种电力市场环境下多流域型虚拟电厂(river basin virtual power plant，RBVPP)抽蓄机组容量优化配置方法。通过改造流域库容式小水电，构建混合式抽水蓄能电站，联合风电、光伏及小水电组建RBVPP。建立基于合作博弈的双层优化配置模型，上层以各RBVPP年净利润加权和最大为目标优化抽蓄装机容量；下层模拟RBVPP联盟参与日前电力市场，第一阶段考虑可再生能源不确定性，建立以联盟收益最大和电网购电成本最小为目标的竞标与出清模型，第二阶段结合流域水力耦合特性，以水量贡献度为权重改进Shapley值法进行收益分配，并将结果反馈至上层进一步优化容量配置。采用粒子群算法嵌套CPLEX求解，算例表明该方法有效提升了RBVPP的市场灵活性与经济性，实现了收益均衡与资源优化配置。 |
| 关键词: 流域型虚拟电厂 合作博弈 优化配置 不确定性 水力耦合特性 电力市场 |
| DOI： |
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| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目）；湖北省自然科学基金联合基金项目 |
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| Optimal capacity allocation of pumped storage units in multiple river basin virtual power plants under electricity market environment |
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ZHONG Hao1, DU Tao2, ZOU Xianqiu3, ZHAO Yishen2, OUYANG Zhenhui2
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1.Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydro-power Station, China Three Gorges University;2.College of Electrical Engineering and New Energy, China Three Gorges University;3.Loudi Power Supply Company, State Grid Hunan Electric Power Co., Ltd.
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| Abstract: |
| Aiming at the problems of lack of flexible resources in small hydropower rich basins in remote areas, and the small capacity of wind, solar and hydropower stations, it is difficult to participate in the power market, an optimal capacity allocation method of pumped storage units in multiple river basin virtual power plants(RBVPPs) under electricity market environment is proposed. Through the transformation of small hy-dropower with storage capacity in the basin, a hybrid pumped storage power station is built, and RBVPP is formed by combining wind power, photovoltaic power and small hydropower. A two-level optimal allocation model based on cooperative game is established, and the upper level optimizes the pumping and storage in-stalled capacity with the weighted sum of the annual net profits of each RBVPP as the goal; The lower level simulates RBVPP alliance participating in the day ahead electricity market. In the first stage, considering the uncertainty of renewable energy, a bidding and clearing model is established with the goal of maximizing al-liance revenue and minimizing grid power purchase cost. In the second stage, combined with the hydraulic coupling characteristics of the basin, the Shapley value method is improved with the weight of water contri-bution, and the results are fed back to the upper level to further optimize the capacity allocation. The particle swarm optimization algorithm nested CPLEX is used to solve the problem. The example shows that the method effectively improves the market flexibility and economy of RBVPP, and realizes the income balance and op-timal allocation of resources. |
| Key words: river basin virtual power plant cooperative game optimal allocation uncertainty hydraulic coupling charac-teristics electricity market |
