母线负荷异常数据复杂不确定性检测与基于综合云的修正模型  

Complex uncertainty detection and synthesized cloud correction model for abnormal bus load data

作　　者：尹星露 肖先勇[1] 孙晓璐[1] 

机构地区：[1]四川大学电气信息学院,四川成都610065

出　　处：《电力自动化设备》2015年第6期117-122,共6页Electric Power Automation Equipment

摘　　要：母线负荷数据异常具有复杂不确定性,是进行母线负荷预测、确定电网运行方式和安全校核等必须解决的重要课题。用聚类分析法确定待测日负荷的相似集,基于母线负荷纵向分布规律和横向连续性,提出异常数据复杂不确定性检测方法;研究母线负荷数据的期望、熵和超熵等数学特征,提出基于综合云的异常数据修正模型。以所提方法对某电网110 k V母线负荷数据进行了分析和预测,结果证明了该方法的可行性、正确性和有效性。The complex uncertainty of abnormal bus load data is a key issue of bus load forecasting,power grid operating mode determination and security check. The cluster analysis is applied to determine the similar set of daily load to be forecasted and a method of complex uncertainty detection for abnormal data is proposed based on the vertical distribution regularity and horizontal continuity of bus load. The mathematical characteristics of bus load data,such as expectation,entropy and hyper entropy,are studied and an abnormal data correction model based on the synthesized cloud is proposed. The 110 kV bus load data of a power grid are analyzed and forecasted by the proposed method and effectiveness. and the resuhs demonstrate its feasibility,correctness

关 键 词：母线负荷 负荷预测 异常数据 相似集 不确定性分析 数学特征 检测与修正方法 综合云模型 聚类算法 

分 类 号：TM715[电气工程—电力系统及自动化]