杨天鑫, 黄云辉, 唐金锐, 王栋, 周克亮, 朱国荣. 高比例新能源下含调频控制的储能系统多目标优化[J]. 高电压技术, 2023, 49(7): 2744-2753. DOI: 10.13336/j.1003-6520.hve.20230580
引用本文: 杨天鑫, 黄云辉, 唐金锐, 王栋, 周克亮, 朱国荣. 高比例新能源下含调频控制的储能系统多目标优化[J]. 高电压技术, 2023, 49(7): 2744-2753. DOI: 10.13336/j.1003-6520.hve.20230580
YANG Tianxin, HUANG Yunhui, TANG Jinrui, WANG Dong, ZHOU Keliang, ZHU Guorong. Multi-objective Optimization of Energy Storage System with Frequency Regulation Control Under High Proportion of Renewable Energy[J]. High Voltage Engineering, 2023, 49(7): 2744-2753. DOI: 10.13336/j.1003-6520.hve.20230580
Citation: YANG Tianxin, HUANG Yunhui, TANG Jinrui, WANG Dong, ZHOU Keliang, ZHU Guorong. Multi-objective Optimization of Energy Storage System with Frequency Regulation Control Under High Proportion of Renewable Energy[J]. High Voltage Engineering, 2023, 49(7): 2744-2753. DOI: 10.13336/j.1003-6520.hve.20230580

高比例新能源下含调频控制的储能系统多目标优化

Multi-objective Optimization of Energy Storage System with Frequency Regulation Control Under High Proportion of Renewable Energy

  • 摘要: 储能在高比例新能源系统中有非常重要的作用,比如调峰、调频和调压等,而储能的作用能否充分体现出来,取决于其容量和位置的配置。为解决高比例新能源下含调频控制的储能系统的优化配置问题,首先研究了一种基于非线性变K系数的储能一次调频控制策略并对其控制参数进行优化,在此基础上,提出了面向高比例新能源电力系统的储能定容选址多目标优化配置方法。该方法采用改进多目标粒子群优化算法,将储能容量、位置作为决策变量,并将系统频率波动指标、电网脆弱性指标和储能成本指标最小作为优化目标,求得帕雷托解集后,通过信息熵求得各个目标的权重后采用优劣解距离法计算得到最优方案。最后,对安阳市某区域电网数据进行实际算例分析,得到了该区域电网的储能最优配置方案,并验证了所提储能定容选址配置方法和控制策略的有效性与优越性。

     

    Abstract: Energy storage plays a crucial role in high-proportion renewable energy systems, such as peak shaving, frequency regulation, and voltage regulation. However, the effectiveness of energy storage depends on its capacity and location configuration. In order to solve the problem of optimal configuration of energy storage system with frequency regulation control under high proportion of renewable energy systems, a primary frequency regulation control strategy based on nonlinear variable K coefficient is first studied, and its control parameters are optimized. On this basis, a multi-objective optimization configuration method for energy storage location and capacity is proposed for high-proportion renewable energy power systems. In the method, a multi-objective particle swarm optimization algorithm with energy storage capacity and location is used as decision variables. The system frequency fluctuation index, grid vulnerability index, and energy storage economy index are minimized as optimization objectives to obtain the Pareto solution set. After obtaining the weights of each objective through information entropy, the optimal solution is calculated using the inferior solution distance method. Finally, an actual case analysis of a regional power grid in Anyang City is conducted, and the optimal configuration scheme for energy storage in the region is obtained, verifying the effectiveness and superiority of the proposed energy storage location and capacity configuration method and control strategy.

     

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