屈克庆, 乔敬茂, 毛玲, 朱少杰, 赵晋斌. 共享储能电站优化配置及选址评价方法[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2023.0313
引用本文: 屈克庆, 乔敬茂, 毛玲, 朱少杰, 赵晋斌. 共享储能电站优化配置及选址评价方法[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2023.0313
QU Keqing, QIAO Jingmao, MAO Ling, ZHU Shaojie, ZHAO Jinbin. Optimal Configuration and Site-selection Evaluation Method for Shared Energy Storage Stations[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2023.0313
Citation: QU Keqing, QIAO Jingmao, MAO Ling, ZHU Shaojie, ZHAO Jinbin. Optimal Configuration and Site-selection Evaluation Method for Shared Energy Storage Stations[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2023.0313

共享储能电站优化配置及选址评价方法

Optimal Configuration and Site-selection Evaluation Method for Shared Energy Storage Stations

  • 摘要: 新型电力系统中储能单元的选型优化是系统经济性、稳定性运行的保障。现有储能电站常采用单独配置的分布式框架,无法充分发挥储能资源调峰调频作用。为提升大量可调可控资源接入的利用效率,计及储能的“共享”特性展开对共享储能电站的优化配置和选址策略研究。首先,构建单个共享储能电站与多个分布式新能源协同发展的混合整数线性规划配置模型;其次,在考虑风光出力特性的情况下,设定共享储能电站优化选址评价指标;然后,在满足负荷需求以及日均经济成本最小的前提下,采用Yalmip工具与CPLEX商业求解器求解,得到共享储能电站的最优容量功率配置,进一步采用灰色关联度法确定共享储能电站最优接入位置;最后,采用IEEE33节点算例进行仿真分析和验证。结果表明:所提出的共享储能电站的优化配置及选址策略,不仅可以得到最优规划决策,而且可以服务于多个用户,满足多节点需求。

     

    Abstract: The site-selection and optimization of energy storage units in new power systems are crucial for ensuring system economy and stability. Existing energy storage stations often employ separate distributed frameworks, which fail to fully utilize the peaking and frequency regulation capabilities of energy storage resources. To enhance the utilization efficiency of a large number of controllable and adjustable resources, in this study we investigate the optimization and site-selection strategy for shared energy storage stations, taking into account the "shared" characteristics of energy storage. First, a mixed-integer linear programming configuration model is established for a single shared energy storage station in conjunction with multiple distributed renewable energy sources. Second, the evaluation criteria for the optimal siting of shared energy storage stations are defined, with the output characteristics of wind and solar power taken into account. Then, under the premise of meeting load demand and minimizing daily average economic costs, the Yalmip tool and CPLEX commercial solver are employed to solve the proposed model and obtain the optimal capacity and power configuration for shared energy storage stations. Furthermore, the gray relation analysis method is used to determine the optimal connection location for shared energy storage stations. Finally, simulation analysis and verification are conducted using an IEEE 33-node test case. The results demonstrate that the proposed optimization and site-selection strategy for shared energy storage stations not only achieves optimal planning decisions, but also serves multiple users and meets the requirements of multiple nodes.

     

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