Long term electric load forecasting based on particle swarm optimization

This paper presents a new method for annual peak load forecasting in electrical power systems. The problem is formulated as an estimation problem and presented in state space form. A particle swarm optimization is employed to minimize the error associated with the estimated model parameters. Actual recorded data from Kuwaiti and Egyptian networks are used to perform this study. Results are reported and compared to those obtained using the well known least error squares estimation technique. The performance of the proposed method is examined and evaluated. Finally, estimated model parameters are used in forecasting the annual peak demands of Kuwait network.