Economic Emission Load Dispatch with Multiple Fuel Options Using Cuckoo Search Algorithm with Gaussian and Cauchy Distributions

Abstract

Cuckoo Search Algorithm (CSA), a new meta-heuristic algorithm based on natural phenomenon of Cuckoo species and Lévy flights random walk, has been successfully applied to several optimization problems so far. In the paper two modified versions of CSA, where new solutions are generated using two distributions including Gaussian and Cauchy distributions are proposed for economic emission load dispatch (EELD) problem with multiple fuel options. The advantages of CSA with Gaussian distribution (CSA-Gauss) and CSA with Cauchy distribution (CSA-Cauchy) over CSA with Lévy distribution are fewer parameters and fewer equations and shorter computational process. The proposed method is tested on one test system consisting of ten generating units with various load demands and compared to other methods. In addition, the best compromise from the set of obtained solutions is found and compared to this from lamda-iteration (LI) method and Hopfield Lagrange Network (HLN). The result comparisons have indicated that the proposed method is a highly effective method. Nomenclature a ik , b ik , c ik : Cost coefficients of thermal unit i for kth fuel d ik , e ik , f ik : Emission coefficients of thermal unit I for kth fuel B ij , B 0i , B 00 : Transmission loss formula coefficients N: Number of online generating units P D : Total load demand of the system (MW) P L : Total network loss of the system (MW) Pi: Output power of unit i (MW) P imin , P imax : Lower and upper generation limits of unit i (MW) w 1, w 2 Weights corresponding to the fuel cost and NOx emission objectives.