An effective cuckoo search algorithm for large-scale combined heat and power economic dispatch problem

This paper develops an effective cuckoo search algorithm (ECSA) for searching optimal solutions for the problem of combined heat and power economic dispatch. The main task of the problem is to determine the optimal value of power of the pure power generators, of the heat of the pure heat generators and of both power and heat of cogenerators so that fuel cost is minimized while exactly meeting power and heat demands and power and heat limits as well as the complicated feasible operating zone of cogenerators. The proposed ECSA is a newly improved version of conventional cuckoo search algorithm to improve the quality of solutions and reduce the maximum number of iterations based on two modified techniques. The first technique is based on the ratio of the difference between the fitness function value of each solution and the lowest fitness function value of the best current solution to the lowest one to determine an effective operation for producing the second new solution generation. The second technique aims to integrate both previous and current solutions into one group and sort them in the descending order of fitness value. The effectiveness of ECSA has been validated via six cases corresponding to six test systems where the scale of the systems is ranged from the smallest system with four units to the largest one with forty-eight units with valve point loading effects. The comparisons of obtained results with other existing methods have indicated that the proposed ECSA is very effective and robust for finding optimal solutions for the CHPED problem.