Comparison of PSO variants with traditional solvers for large scale multi-area economic dispatch

Economic load dispatch (ELD) has the objective of generation allocation to the power generators such that the total fuel cost is minimized and all operating constraints are satisfied. Generally ELD is solved without accounting for transmission constraints, however, in deregulated power system environment it is essential to include practical multi-area cases with tie line constraints. A number of traditional methods are used for solving ELD and other power system problems. During the last decade soft computing methods like particle swarm optimization (PSO), have been increasingly proposed for complex optimization problems. This paper proposes some improved PSO technique in which premature convergence is avoided by tuning the PSO parameters for enhanced global and local search. The paper reviews and compares the performance of the proposed PSO variants with traditional solver GAMS for multi-area economic dispatch (MAED) on four standard test systems having different sizes and complexity levels. A large 120-unitpower system is included for validating the results.