Genetic algorithms for economic dispatch with valve point effect

Economic dispatch (ED) is an important daily optimization task in the power system operation. To solve effectively the ED problem, most calculus based industrial algorithms, e.g., the Lagrangian multiplier method, require the incremental cost curves to be of monotonically increasing nature or of piece-wise linearity. Thus, this conventional procedure either ignores or flattens out the portions of the incremental cost curve that are not continuous or monotonically increasing, resulting in inaccurate dispatch. In this paper, four genetic algorithms: simple genetic algorithm (SGA), SGA with generation-apart elitism, SGA with atavism and atavistic genetic algorithm (AGA) are compared on three test systems: 3-generator system, 13-generator system, and the standard IEEE 30-bus test system. Numerical results on the test systems are presented and compared to previous approaches using Lagrange and Tabu search methods.