Recent trends of meta-heuristics applications in power systems

Abstract

Electric utilities are quite interested in operational cost saving measures. This implies that the global optimization technique is more attractive in power system operation and planning. As typical meta-heuristics, the tabu search (TS), genetic algorithm (GA) and simulated annealing (SA) have widely been adopted. TS is an extension of the hill-climbing method in a sense that TS has adaptive memory in the hill-climbing method. It is noteworthy that TS is a transition-type algorithm like chaos search. GA comes from the natural selection of genes in biology. Genetic operations improve the quality of solution in the multi-point solution search process. SA is based on the analogy of annealing of crystal or metal in heat bath. As temperature of SA parameter cools down, the solution converges. In particular, TS is more attractive due to the good performance. In this paper, applications of TS to power systems are discussed.