Solving fuzzy combined-emission dispatch by using differential evolution immunized Ant Colony Optimization technique

Emission dispatch deals with the process of determining the emission level produced by thermal power plants. Since the concerns toward environmental health paramount, emission dispatch has become a crucial consideration during energy dispatch planning. Different fuel types produce different types of pollutant and thus the total emission level may vary. However, the fluctuation of future load demand and fuel cost causes emission dispatch problems in dynamic system. Therefore, this paper proposes the implementation of fuzzy logic in solving the combined emission dispatch and termed as Fuzzy Combined-Emission Dispatch (FCED). A newly developed optimization technique termed as Differential Evolution Immunized Ant Colony Optimization (DEIANT) technique is employed to optimize FCED. DEIANT is compared with Evolutionary Programming (EP) and Ant Colony Optimization (ACO) techniques in order to evaluate its performance. Results indicate that the proposed FCED technique outperformed EP and PSO in terms of achieving lower minimal emission level and reduce operating cost.