Energy Storage Frequency Regulation Energy Management Strategy Based on K-Means Analysis

2019 IEEE 3rd International Conference on Green Energy and Applications (ICGEA) Pub Date : 2019-03-01 DOI:10.1109/ICGEA.2019.8880782

Chen Hao, Jia Yanbing, Zheng Jin, Zhu Yanfang, Luo Gang, Xie Dong

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引用次数: 6

Abstract

The energy storage system participates in the power grid Frequency Regulation (FR), which can give full play to the advantages of fast energy storage return speed and high adjustment precision. Based on the optimal response FR scheduling instruction of energy storage power station, based on K-means clustering method, the comprehensive performance index of FR (adjustment speed, response time and adjustment precision) is analyzed. The different energy flow states of power grid and energy storage unit are summarized. The impact of performance indicators, explored the battery cell control strategy to achieve a network-storage win-win energy storage. By modifying the existing response sequence and combining the SOC state of each unit, the dynamic adaptive sensing adapts to the grid automatic power generation control (AGC) variable load task, so that the fire storage combined FR system can obtain more compensation and reduce storage. The total number of foldbacks can be reduced to reduce operating costs.

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基于k均值分析的储能调频能量管理策略

储能系统参与电网频率调节(FR)，可以充分发挥储能回电速度快、调节精度高等优势。基于储能电站最优响应FR调度指令，基于k均值聚类方法，分析了FR的综合性能指标(调节速度、响应时间和调节精度)。总结了电网和储能单元的不同能量流状态。在影响电池性能指标的基础上，探索了电池单体控制策略，实现了网络储能与储能的双赢。动态自适应传感通过修改现有响应序列，结合各机组的SOC状态，适应电网自动发电控制(AGC)变负荷任务，使火电储联合FR系统获得更多补偿，降低存储。可以减少折叠的总数，从而降低操作成本。

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2019 IEEE 3rd International Conference on Green Energy and Applications (ICGEA)

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