文章摘要
吴杰,丁明,张晶晶.基于云模型和k-means聚类的风电场储能容量优化配置方法[J].电力系统自动化. DOI: 10.7500/AEPS20180725007.
WU Jie,DING Ming,ZHANG Jingjing.Capacity Configuration Method of Energy Storage System Based on Cloud Model and K-means Clustering for Wind Farm[J].Automation of Electric Power Systems. DOI: 10.7500/AEPS20180725007.
基于云模型和k-means聚类的风电场储能容量优化配置方法
Capacity Configuration Method of Energy Storage System Based on Cloud Model and K-means Clustering for Wind Farm
DOI:10.7500/AEPS20180725007
关键词: 风电平抑  储能配置  云模型  k-means聚类
KeyWords: wind power smoothing  energy storage configuration  cloud model  k-means clustering
上网日期:2018-11-06
基金项目:国家重点研发计划资助项目(2016YFB0900400)
作者单位E-mail
吴杰 安徽省新能源利用与节能重点实验室 hf1993wj@163.com 
丁明 安徽省新能源利用与节能重点实验室 mingding56@126.com 
张晶晶 安徽省新能源利用与节能重点实验室 dragonzjj@126.com 
摘要:
      合理确定风电场侧储能系统容量配置方案是实现风电输出功率波动有效平抑的关键问题。针对传统k-means聚类算法难以给定聚类数目且算法稳定性较差的问题,在采用自适应小波包分解法处理风电输出得到储能运行曲线的基础上,基于云模型理论将储能充放电功率的概率分布分解成若干个正态云模型的叠加,根据数据特性自动确定聚类数目和初始聚类中心,然后应用k-means聚类算法从储能运行曲线中聚合出具有代表性的充放电曲线集合作为储能容量优化模型的输入,从而最终确定储能系统的配置方案。仿真结果验证了所提算法的合理性和稳定性。
Abstract:
      The key problem of realizing effectively smoothing of wind power fluctuation is how to reasonably determine the capacity configuration of energy storage system for wind farm. The adaptive wavelet packet decomposition method is used to decompose the wind power to determine the operation curve of energy storage system. Considering that the traditional k-means clustering algorithm is difficult to automatically determine clustering number and the stability of the algorithm is poor, this paper decomposes the probability distribution of the charging and discharging power of energy storage system into a superposition of several normal cloud models based on cloud model theory, and automatically determines clustering number and initial cluster centers according to the characteristics of power data. Then the k-means clustering algorithm is used to aggregate the representative charging and discharging curve set from energy storage system operation curve as the input of capacity optimization model, so as to ultimately determine the configuration scheme of energy storage system. The simulation results show the rationality and stability of the proposed method.
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