Dynamic economic emission dispatch based on group search optimizer with multiple producers

This paper presents a new method for dynamic economic emission dispatch (DEED) of power systems, using a novel multi-objective evolutionary algorithm, group search optimizer with multiple producers (GSOMP) that includes a constraint handling scheme introduced to deal with complex constraints. The DEED is divided into 24 decomposed DEEDs, which are then solved hour by hour in the time sequence. A technique for order preference similar to an ideal solution (TOPSIS), is then developed to determine the final solution from the Pareto-optimal solutions considering a decision maker's preference. The performance of GSOMP has been evaluated on the DEEDs of the IEEE 30-bus and 118-bus systems, respectively, in comparison with those of multi-objective particle swarm optimizer (MOPSO) and non-dominated sorting genetic algorithm-II (NSGA-II). The simulation results show that DEED is well solved by the proposed method as a set of widely distributed Pareto-optimal solutions can be obtained and that GSOMP has better convergence performance than MOPSO and NSGA-II and consumes much less time than NSGA-II. All the NOx, CO2 and SO2 are integrated into the emission objective function of the DEED, on which the solution obtained can have relatively low emission of each pollutant. (C) 2011 Elsevier B.V. All rights reserved.