Simulated annealing approach to solution of multi-objective optimal economic dispatch

An efficient and reliable evolutionary based meta-heuristic approach, termed as simulated annealing, is presented for the solution of optimal economic power dispatch. The generation of electricity from the fossil fuel releases several contaminants, such as sulphur oxides, nitrogen oxides and carbon dioxide, into the atmosphere. Simulated annealing algorithmic approach to power system optimization, as reported here for a case of economic power dispatch, consists essentially of minimizing the objective function while gradually satisfying the constraint relations. The advantages of the approach in terms simulated annealing algorithmic problem reduction, flexibility and solution methodology are also discussed. In the Multi-objective problem formulation, four important non-commensurable objectives in an electrical thermal power system are considered. These are economy and environmental impacts because of NOx, SO2, CO2 emissions. The feasibility of the proposed method is compared with a simple genetic algorithm is described to multi-objective optimal economic dispatch of electrical power systems.