Genetic algorithm approach to environmental constrained optimal economic dispatch

Genetic Algorithm (GA) approach to function optimization consists essentially of minimizing an objective function while gradually satisfying the constraint relations. Suitability of GAs for multi-objective optimization is presented in this paper Detailed aspects of problem definition, formulation and implementation of GAs to the multi-objective optimization problem, with fuel cost (economy) nod Non emission (pollution) as conflicting objectives are discussed. The GA approach is similar to the fuzzy optimization approach in handling multiple objectives. Graphical approach for the determination of the pareto-optimal solution is proposed In the GA approach, the pareto-optimal solution finally converges to the optimal operating point for a particular load power demand. Environment constrained optimal economic dispatch results for a 6 generator unit of the IEEE 30 bus power are presented for various loading conditions.