Fuel constrained economic emission dispatch using nondominated sorting genetic algorithm-II

This paper presents nondominated sorting genetic algorithm-II for solving fuel constrained economic emission dispatch problem of thermal generating units. This is a multi-objective optimization problem which includes the standard load constraints as well as the fuel constraints. The generation schedule is compared to that which would result if fuel constraints are ignored. The comparison shows that fuel consumed can be adequately controlled by adjusting the power output of various generating units so that the power system operates within its fuel limitations and within contractual constraints. It has been found that one of the two objectives (i.e. fuel cost and emission level) may be increased while other may be decreased to serve the same power demand but this may well compensate for the penalty that might be otherwise imposed for not maintaining the fuel contract. Numerical results for two test systems have been presented and the test results are compared with those obtained from strength pareto evolutionary algorithm 2.