Identification of time-varying energy systems based on improved particle swarm optimization algorithm

摘要

Aiming to identification the time-varying energy system, on the basis of the basic particle swarm algorithm, an improved particle swarm optimization method for identification of time-varying energy system was presented. The essence is the identification problem was converted to the function optimization problems in parameter space. Then use the parallel search ability of improved particle swarm algorithm for parameter optimization. Simulation results show that compared with other algorithm, the improved algorithm not only improves the identification accuracy, but improves the tracking precision of the time-varying parameters, which verify the validity and feasibility of the algorithm.