Genetic Algorithms for non-convex combined heat and power dispatch problems

This paper investigates into performance of Genetic Algorithms (GA) for solving combined heat and power dispatch (CHPD) problems in power systems. Different algorithms in different combinations of crossover and mutation functions of GA are explored and tested on a test case of combined heat and power dispatch problem. The simulation results show that all the floating point GAs (FPGA) perform better than binary GA in solving non-convex CHPD problems. Amongst the FPGAs, the performance of the FPGA with heuristic crossover and multi-nonuniform mutation is the best in terms of the efficiency in achieving better quality solutions.