Metaheuristics approaches to solve combinatorial optimization problems in distribution power systems. An application to Phase Balancing in low voltage three-phase networks.

Abstract

Metaheuristics algorithms are widely recognized as one of most practical approaches for combinatorial optimization problems. One the most interesting areas of application are the power systems. In particular, Distribution Systems planning and operation. This paper presents some metaheuristics approaches tosolve a typical combinatorial optimization problem: the Phase Balancing in Low Voltage Electric Distribution Systems. A model supported in Linear Integer-Mixed Programming is presented, to observe and discussing its limitations. From this, is introduced a new metaheuristic, called Fuzzy EvolutionaryParticle Swarm Optimization, based in the Swarm Intelligence Principles and Evolution Strategies, which is extended to fuzzy domain to modeling a multi-objective optimization, by mean of a fuzzy fitness function.A simulation on a real system is presented, and advantages of this approach respect to the Classical Simulated Annealing and Particle Swarm metaheuristics, selected between the most representatives, areevidenced.