Optimizing power system stabilizer parameters using hybridized differential evolution and particle swarm optimization

In order to better optimize power system stabilizer (PSS) parameters, a differential evolution particle swarm optimization (DEPSO) algorithm is proposed. The DEPSO algorithm can seek the global optimal location through information exchange mechanisms between PSO populations and DE populations, so that the algorithm has dynamic adaptability to skip local optimums easily. First, the paper expatiates on the optimization method of PSS lead-lagging link and gain parameters by the DEPSO algorithm in the low frequency range (0.1-2.5Hz). Then the paper builds a model of single machine infinite system with Matlab. The simulation results show that the PSS stability designed by the DEPSO algorithm is improved greatly, and the effect of the DEPSO algorithm is superior to the PSO algorithm. Afterwards, we design a set of software system via the proposed method to optimize PSS parameters of some units, Anhui power grid, and get good results.