Constrained economic dispatch by combined genetic and simulated annealing algorithm

This article proposes a combined genetic and simulated annealing algorithm (CGSA) to solve ramp rate constrained economic dispatch (ED) problems for generating units with non-mono tonically and monotonically increasing incremental cost (IC) functions. The developed CGSA method is tested on the systems with the number of generating units in the range of 10 to 80 over the entire dispatch periods. The obtained solutions are near the optimal solutions of zoom brute force (ZBF) and zoom dynamic programming (ZDP), and are less expensive than those obtained from local search (LS), simulated annealing (SA), genetic algorithm (GA), GA based on SA solutions (GA-SA) and merit order loading (MOL) methods, thereby leading to substantial generator fuel cost savings. The proposed CGSA is effective in solving constrained ED problem in terms of the quality of solutions.