引用本文:程浩,秦文萍,韩肖清,景祥,朱志龙,逯瑞鹏.基于功角稳定性的区域电网储能选址定容方法[J].电力自动化设备,2024,44(7):21-29
CHENG Hao,QIN Wenping,HAN Xiaoqing,JING Xiang,ZHU Zhilong,LU Ruipeng.Site selection and capacity determination method of energy storage in regional power grid based on power angle stability[J].Electric Power Automation Equipment,2024,44(7):21-29
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基于功角稳定性的区域电网储能选址定容方法
程浩, 秦文萍, 韩肖清, 景祥, 朱志龙, 逯瑞鹏
太原理工大学 电力系统运行与控制山西省重点实验室,山西 太原 030024
摘要:
为了缓解跨传输断面的调峰压力,同时提升电网的功角稳定性,建立了兼顾经济性与功角稳定性的储能选址定容双层优化模型,并给出了模型的求解方法。上层模型考虑区域电网的运行经济性,以储能电站收益最大为优化目标,确定储能配置总容量。下层模型考虑区域电网的功角稳定性,以储能调度期间总网损最小和储能调节区域电网功角稳定性能力最大为优化目标,进行储能选址与总容量的分配。双层模型的上层采用遗传算法进行求解,下层采用改进多目标人工蜂群算法进行求解。以某实际电网为算例进行仿真验证,结果表明,根据所提双层优化模型进行储能配置可以在保证经济性的同时,提升区域电网的功角稳定性。
关键词:  储能  双层规划  选址定容  功角稳定性  改进多目标人工蜂群算法
DOI:10.16081/j.epae.202312025
分类号:TM715
基金项目:国家自然科学基金联合基金重点支持项目(U1910216);区域创新发展联合基金资助项目(U21A600003)
Site selection and capacity determination method of energy storage in regional power grid based on power angle stability
CHENG Hao, QIN Wenping, HAN Xiaoqing, JING Xiang, ZHU Zhilong, LU Ruipeng
Shanxi Key Laboratory of Power System Operation and Control, Taiyuan University of Technology, Taiyuan 030024, China
Abstract:
In order to alleviate the peak shaving pressure across the transmission sections and improve the power angle stability of the power grid, a two-layer site selection and capacity determination optimization model of energy storage considering both economy and power angle stability is established, and the solution method of the model is given. The upper model considers the operation economy of the regional power grid and takes the maximum benefit of the energy storage station as the optimization objective to determine the total configuration capacity of the energy storage. The lower model considers the power angle stability of the regional power grid and takes the minimum total network loss during the energy storage dispatch period and the maximum power angle stability ability of the energy storage regulation regional power grid as the optimization objectives to carry out the site selection and total capacity allocation of energy storage. The upper layer of the two-layer model is solved by using genetic algorithm and the lower layer is solved by using improved multi-objective artificial bee colony algorithm. An actual power grid is taken as an example for simulation verification. The results show that energy storage configuration based on the proposed two-layer optimization model can improve the power angle stability of regional power grid while ensuring economy.
Key words:  energy storage  bi-level programming  site selection and capacity determination  power angle stability  improved multi-objective artificial bee colony algorithm

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