基于数据挖掘技术的电网网损的评价算法的研究

Study on the Evaluation Algorithm of Power Loss Based on Data Mining Technology

针对电网网损数据样本聚合精度较低、计算精度不高的问题,提出一种基于数据挖掘计算的电网网损评价算法。该算法基于最近聚类算法原理,通过聚类中心优化调整、最远数据点二次聚类、阈值动态选取等技术,使得基于电网断面采集数据的聚类质量得到有效提升,并使基于该聚类结果的电网网损评价算法的精度得到可靠保证。仿真测试证明了,通过该算法能得出拟合度较高的电网网损曲线。

Aiming at the problems of low polymerization accuracy and low calculation accuracy of power loss data samples,this paper proposes a power loss evaluation algorithm based on data mining.On the basis of the nearest neighbor clustering algorithm,through optimization and adjustion of the clustering center and secondary clustering of the farthest data points based on dynamic selection technology of clustering threshold,the clustering quality of the collected data based on power grid tie-line is effectively improved,and the accuracy of power loss evaluation algorithm based on the results is reliable guaranteed.The simulation test proves that,with this algorithm,the power loss curve with a high fitting degree can be obtained.