A Particle Swarm Optimiser with Passive Congregation Approach To Thermal Modelling For Power Transformers
Wenhu Tang, Suining He, Emmanuel Prempain, Qinghua Wu, John F. Fitch · 2005
This paper employs an intelligent learning technique based on a particle swarm optimiser with passive congregation (PSOPC) algorithm to identify the thermal parameters of a simplified thermoelectric analogous thermal model (STEATM) for transformers, based upon only a few onsite measurements instead of experimental methods. The model outputs deliver good agreements with the onsite data based upon a single set of parameters obtained from the PSOPC learning with a fast convergence rate. The simulation results are compared with that obtained using an artificial neural network (ANN) approach.