Multi-Objective Reactive Power Optimization Based on Improved Artificial Searching Swarm Algorithm

In order to solve the problem of multi-objective reactive power optimization, firstly the defects of current algorithms are analyzed, then an improved chaos artificial searching swarm algorithm based on artificial search is proposed. The optimization performance of the algorithm is improved by introducing chaos theory and the dynamic improvement of algorithm step. This algorithm was tested with classical test functions. The results show that the optimization ability of the artificial search swarm algorithm is significantly improved. In the MATLAB 2014b environment, ICASSA is used to optimize the simulation of the IEEE14 and IEEE30 buses of the standard power system. Comparing the performance of ICASSA, IPSO and IDE, the results show the ICASSA has better search ability. Finally, the reactive power optimization of a real power network is simulated, and the results show that the ICASSA algorithm has potential application value.