A study on the load model based on particle swarm optimization

摘要

Based on comparing between the Composite Load Model (CLM) with the Synthesis Load Model (SLM), the SLM has been adopted in this paper. In view of the load model parameter identification's characteristics of complexity and low accuracy, a parameter identification method of the SLM based on Particle Swarm Optimization algorithm was proposed and used in the specific case study. It is shown by the case that the power curves simulated are closer to the measured ones, the particle swarm optimization has a certain superiority in the aspect of load model parameter identification, and the synthesis load model is reasonable.