确定应用场景下的储能系统典型运行曲线挖掘  

Typical Operation Curve Mining of Energy Storage System Oriented to Specific Application Scenario

作　　者：韩晓娟[1] 籍天明 李蓓[2] 王丽娜[1] 

机构地区：[1]华北电力大学控制与计算机工程学院,北京市昌平区102206 [2]中国电力科学研究院,北京市海淀区100192

出　　处：《中国电机工程学报》2016年第4期978-985,共8页Proceedings of the CSEE

基　　金：国家电网公司科技项目(DG71-14-046);国家自然科学基金项目(51577065)~~

摘　　要：通过对确定应用场景下的储能系统运行曲线进行典型特征的挖掘,可以实现对该应用场景下储能系统运行特性的整体认知,为储能系统容量配置提供计算依据。依托储能系统平抑光伏电站功率波动的应用场景,提出一种基于云模型的典型运行曲线挖掘算法。将储能系统纵向时序功率值的频率分布分解为若干个不同粒度的云模型,对正态云模型组的期望加权求和,从而整合出储能系统典型运行曲线。在分析6种典型天气类型下储能功率分布与典型运行曲线功率分布的基础上,采用非参数估计法实现功率值分布的拟合,计算得出拟合偏差,验证所提取典型运行曲线的合理性。根据该曲线给出了储能系统的容量配置。通过仿真实例验证了典型运行曲线的有效性和正确性,为实现储能系统的容量配置提供了理论支持。Typical operation curve mining of energy storage system （ESS） can provide an overall cognition of power features of ESS and provide a calculation basis for determining capacity configuration in a certain application scenario. Based on restraining PV power fluctuation application scenario, a typical operation curve mining algorithm based on cloud model of ESS was proposed in this paper. Frequency distribution of longitudinal moment power of ESS was decomposed into several normal cloud groups by multiple cloud transform, typical power values was calculated by expectations of normal cloud model group with weight sum. In this way, the typical operation curve mining of ESS was Obtained in integration. Take a nonparametric kernel density estimation for ESS power distribution under 6 typical weather patterns and the typical operation curve, the fitness bias was obtained to verify the rationality of the typical operation curve. ESS Capacity configuration was obtained according to the typical operation curve. Effectiveness and correctness of the typical operation curve was verified by a simulation example. Theoretical support of ESS capacity configuration was provided in this paper.

关 键 词：储能系统 云模型 典型曲线 容量配置 

分 类 号：TM71[电气工程—电力系统及自动化]