Reactive power optimization of power system based on multi-objective concordance evolutionary algorithm

Based on traditional reactive power optimization model, a new multi-objective concordance evolutionary algorithm (MOCEA) is proposed for the active power loss, voltage deviation, static voltage margin and reactive power compensation capacity. The algorithm combines the multi-objective decision-making concordance model with group evolution thought organically. In a limited group each individual is ranked with concordance model to improve the effectiveness of optimization method. IEEE 30-bus system is used to test the performance of the algorithm by Matlab 7.0, and the results show the method having low power loss, low voltage deviation, low reactive power compensation capacity and high static voltage margin.