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基于k-means 聚类的含风电电力系统暂态稳定风险评估

发表时间:2015-11-30  浏览量:1568  下载量:486
全部作者: 梁立龙,白雪峰
作者单位: 哈尔滨工业大学电气工程及自动化学院
摘 要: 基于风险理论,利用预想事故的严重程度和风速概率模型定义预想事故的风险指标,在表示预想事故的 严重程度时,采用系统内在特性的物理指标稳定裕度表征。将聚类分析理论应用于风险分析,利用k-means 聚类方法对系统的暂态安全风险进行综合评估,选取符合实际情况的聚类中心数目,将风险进行有效的归类 与划分,最后通过算例仿真验证该方法的有效性。结果证实了所提方法的准确性和实际性,具有一定的现实 指导意义。
关 键 词: 电力系统及其自动化;暂态稳定;风电; 稳定裕度;风险评估;k-means 聚类
Title: Transient security risk assessment of power system with large scale wind farm based on k-means clustering
Author: LIANG Lilong, BAI Xuefeng
Organization: School of Electrical Engineering and Automation, Harbin Institute of Technology
Abstract: In this paper, the risk indicator is defined by the severity and wind speed probability model based on the theory of risk. The stability margin, as a physical indicator to characterize the intrinsic properties of the system, is used to indicate the severity of contingency. And the clustering analysis theory is applied to the risk analysis, the k-means clustering method is used to comprehensively evaluate transient security of power system. The risks are classified and divided effectively by selecting the number of clusters with the actual situation. Finally, the effectiveness of the proposed method is verified through the simulation example. The result verifies the accuracy and practicality of this method, which has certain practical significance.
Key words: electric power system and automation; transient stability; wind power; stability margin; risk assessment; k-means clustering
发表期数: 2015年11月第22期
引用格式: 梁立龙,白雪峰. 基于k-means 聚类的含风电电力系统暂态稳定风险评估[J]. 中国科技论文在线精品论文,2015,8(22):2320-2328.
 
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