Multi-objective economic emission dispatch solution using hybrid FFA (firefly algorithm) and considering wind power penetration

Abstract

This paper presents a new and efficient method for solving EPD (economic power dispatch) problem. To solve this problem we have combined two meta-heuristic methods, the FFA and the mGA. The acceleration of the convergence speed, the improved solution quality and the balance between exploration and exploitation are achieved with FFA–mGA approach. The searching process starts with the FFA by initializing a group of random fireflies. After that, the search is pursued by the mGA. Then, the best results (better than FFA) found from mGA are still communicated to the FFA as an initial space search.The process is repeated than until the final solution is reached. The strength of the proposed approach is tested and validated on the standard IEEE 30-bus system by solving several cases as: the fuel cost minimization, Emission minimization, Emission and cost minimization simultaneously, fuel cost minimization with Sine Components, Piece-wise quadratic cost functions minimization and finally, the effect of the integration of wind energy in the system. The obtained results are compared with the classic FFA and the GA (genetic algorithm) and those in literature. The results show that the proposed approach provides accurate solutions for any type of the objective functions.