多数据源配电网不良数据的辨识与校核  

Bad data identification and correction in multi-data source distribution networks

作　　者：徐玮[1] 刘东[1] 陆佳南[1] 陆融[2] 邱继东[2] 潘华明[2] 

机构地区：[1]上海交通大学,上海200240 [2]上海电力公司市东供电公司,上海200122

出　　处：《华东电力》2009年第7期1133-1136,共4页East China Electric Power

基　　金：国家自然基金资助项目(90612018);教育部新世纪优秀人才与计划

摘　　要：不良量测数据较多是配电系统状态估计不能正常工作的主要原因,针对配电网数据采集中多数据源的情况,提出了具有实用性的多源数据预处理技术,即综合利用上下电压等级的冗余量测数据,对部分不良数据进行修补,提高状态估计输入数据质量;综合利用遥信量和遥测量,提高遥信量的准确度,从而能够充分利用冗余数据的优势,避免数据预处理中的误判和漏判。实际的算例验证了该方法的有效性。Bad data existence is usually the main cause of failures in condition estimation for distribution networks. A practical multi-source data preprocessing method for current distribution networks was proposed which takes advantage of muhi-data sources and corrects some of the real-time data according to redundant data. Thus the quality of input data for condition estimation was improved and the risk of misjudgment was reduced. Verification of remote data was also discussed. Calculation examples proved the method effective.

关 键 词：配电网 多源数据 遥信与遥测 辨识与校核 

分 类 号：TM732[电气工程—电力系统及自动化]