Heuristic Algorithms for Solving Convex and Nonconvex Economic Dispatch

Economic dispatch (ED) is a power system optimization problem and its objective is to reduce the total generation cost of units while satisfying constraints. The presence of nonlinearities in practical generator operation makes solving the ED problem more challenging. These generator nonlinearities are modeled as constraints to be met in the form of ramp-rate limits and prohibited operating zones. This paper proposes three heuristic algorithms, namely, the genetic algorithm (GA), differential evolution (DE) and modified particle swarm optimization (MPSO) to solve this ED problem for two test systems. Simulation, numerical results and convergence performances of these three algorithms are presented and compared as a way of demonstrating and validating the heuristic algorithms in solving this complex and challenging power system problem characterized by practical and nonconvex generator constraints.