A novel PSO (Particle Swarm Optimization)-based approach for optimal schedule of refrigerators using experimental models

摘要: Refrigerators have considerable share of residential consumption. They can be, however, flexible loads because their operating time and consumption patterns be changed to some extent. Accordingly, they selected as a target for the study Demand Side Management plans. In this paper, two experimental models refrigerator are derived. obtaining first model, following assumptions made: ambient temperature is assumed constant door remained closed. However, in second model variation door-opening effects considered according general patterns. Further, strategies proposed reduce annual electricity cost electric power at peak-load times. These together with aforementioned form an optimization problem which is, then, solved by Particle Swarm Optimization algorithm. Simulation results indicate reduction more than 28.61% cost. Also, has decreased 20.46% load shifting from peak periods achieved about 40%. addition, these approaches implemented laboratory performance confirmed results.