A multi-objective evolutionary algorithm for reactive power compensation in distribution networks

In this paper, the problem of locating and sizing capacitors for reactive power compensation in electric radial distribution networks is modeled as a multi-objective programming problem. An evolutionary approach consisting of an elitist genetic algorithm with secondary population is used to characterize the Pareto optimal (non-dominated) frontier, namely regarding well-distributed and diverse solutions. Two objective functions of technical and economical nature are explicitly considered in this model: minimization of system losses and minimization of capacitor installation costs. Constraints refer to quality of service, power flow, and technical requirements. The performance of the distribution network before and after the reactive power compensation is exploited.