基于PSO-SVM的直流配电网电能质量扰动辨识

直流配电网是未来配电系统发展趋势,为更好地针对性治理改善直流电能质量问题,推动直流配用电技术的发展,需要提出一种适用于直流电能质量扰动特征的辨识方法。文中剖析了直流配电网中4类电能质量问题的形成机理和扰动特征,并针对各类问题的特点提出了5种特征指标,以此作为辨识直流电能质量问题的特征要素。采用k-means聚类分析的方法对所提特征集的类内聚集性和类间分离性进行了验证。最后利用PSO-SVM分类器实现了直流电能质量事件的准确辨识,仿真算例验证了所提方法的准确性与有效性。

Identification of power quality disturbance in DC distribution network based on PSO-SVM

DC distribution network is the development trend of power distribution system in the future, in order to achieve the targeted improvement of DC power quality problems and promote the in-depth development of DC power distribution technology, it is necessary to propose an identification method suitable for DC power quality disturbance characteristics. In this paper, the formation mechanism and disturbance characteristics of four types of power quality problems in DC distribution network are deeply analyzed, and five characteristic indicators are proposed for the characteristics of various problems, which are used as the characteristic elements to identify DC power quality problems. The intra-class aggregation and inter-class separation of the proposed feature set were proved by k-means cluster analysis. Finally, the PSO-SVM classifier is used to accurately identify the DC power quality problem. Simulation examples verify the accuracy and effectiveness of the proposed method.