Comparison Between the Dynamic Programming and Particle Swarm Optimization for Solving Unit Commitment Problems

Abstract

This paper presents a comparison between Dynamic Programming (DP) and Particle Swarm optimization (PSO) approaches for minimizing fuel cost and CO 2 emissions and solving Unit Commitment (UC) problem in Microgrid Central Energy Management System (MCEMS). Both approaches minimize the fuel cost and CO 2 emissions for the Micro Gas Turbine (MGT). These techniques are applied to ten subsystems in MCEMS. The MCEMS adjusts itself during the operation in the generation system. The test results of DP and PSO are compared with emphasis on a more practical solution. A MATLAB program was written to minimize the UC problem. Simulation results demonstrate that the PSO technique is more accurate than DP the technique in solving UC problems.