Quantum-behaved Particle Swarm Optimization for Economic/Emission Dispatch Problem of Power System

Abstract

This paper proposes a quantum-behaved particle swarm optimization with multiplier updating (QPSO-MU) for solving economic /emission dispatch problems (EEDP) of power system. The quantum-behaved particle swarm optimization (QPSO) has the ability to efficiently search and actively explore solutions. Multiplier updating (MU) is introduced to avoid deforming the augmented Lagrange function and resulting in difficulty to solution searching. The ε-constraint technique is employed to handle the EEDP. The proposed algorithm integrates the ε-constraint technique, QPSO, and the MU. The simulation using the proposed method is carried out on a 6-unit test system, and results are compared with that obtained using other different methods. Numerical results indicate that the proposed approach is superior to other methods in solution quality and computational burden.