摘要
为满足高压配电网不良数据处理实用化的需求,提出一种针对高压配网不良数据处理的实用方法。该方法充分考虑高压配网的可观测性与辐射性,采用数据挖掘技术对坏数据进行检测与辨识,并综合利用前推回代潮流法与改进遗传算法获得加权估计值。该方法已在某市的调度系统中得到实际应用,表明了其有效性。
A practical method for bad data processing of high voltage distribution network is proposed, aiming at meeting the practical need of high voltage distribution network. This method, considering the observability and radiation of high voltage distribution network sufficiently, uses the technique of data mining to detect and identify bad data and gets weighted estimates applying back/forward sweep power flow method combined with improved genetic algorithm. The effectiveness of this method is proved by practical application in a grid scheduling system of a city.
出处
《计算机工程与应用》
CSCD
2014年第8期255-259,共5页
Computer Engineering and Applications
基金
湖南省自然科学基金委员会与衡阳市政府自然科学联合基金资助(No.11JJ8003)
关键词
高压配电网
不良数据
遥测布尔变量
前推回代法
改进遗传算法
加权平均潮流
high voltage distribution network
bad data
boolean variable telemetry
back/forward sweep method
im-proved genetic algorithm
weighted average trend
