A New Var Optimal Compensation Strategy Based On Data Mining And Ant Colony Algorithm

Power system is nolinear and multi-coupled. And a lot of data are collected in the darily running. How to extract the useful information and make the wise decision of var optimal compensation is of great siginificance.This paper firstly introduce the course, classification, typic methods and application of data mining technique , the effect, solution of var compensation, and the application of power capicitors in grid recently. Then it analyzed the status quo of var compensation in Shanghai and the new problems of var control strategy and substation automation because of the centred-control mode.Based on the analysis above, for the problem of the var compensation and voltage control in center-substations, this paper induced a new algorithm to find the reactive optimization method of power system, using the data collected in power substations. The new algorithm is combined with improved Apriori data mining techniques and ant colony algorithm. The mathematic model of var optimization of power system is described as two parts. The improved Apriori algorithm mines the useful information and association rules on practical system for the decision of var optimization. The improved ant colony algorithm is applied to find the optimal schemes of reactive compensation based on the results of data mining.The total mathematic model of var optimization of power system is applied to resolve the reactive optimal compensation problem of Wanhang substation (220kV) in Shanghai based on its darily running history data. The optimal schemes in different working conditions are woked out and the results are analyaed and compared.Test results show that the application of the new algorithm proposed in this paper for determining the plan of reactive optimization can raise the system operation efficiency and reduce the loss. And it is of great economical significance for the system voltage control.