A Multi-Objective Optimization for Power Economic Dispatch

This paper presents a multi-objective optimization algorithm for power economic dispatch considering emission. The Improved Genetic Algorithm (IGA) equipped with an improved evolutionary direction operator and a migration operation can efficiently search and actively explore solutions. The Multiplier Updating (MU) technique is introduced to avoid deforming the augmented Lagrange function and resulting in difficulty to solution searching. To handle the multi-objective problem, the ε-constraint technique is employed. The proposed approach integrates the ε-constraint technique, IGA, and the MU technique. The simulation using the proposed method is carried out on a 6-unit test system, and the 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.