Reactive power compensation using a multi-objective evolutionary algorithm

This paper presents a new approach to treat reactive power compensation in power systems using a multiobjective optimization evolutionary algorithm. A variant of the strength Pareto evolutionary algorithm is proposed to independently optimize several parameters instead of traditional constrained single-objective approach where an objective function is a linear combination of several factors, such as, investment and transmission losses, with several constrains that limit other parameters as reliability and voltage profile. With the proposed approach, a set of optimal solutions known as Pareto set is found before deciding which solution best combines different features. This set is compared with a set of compensation schemes elaborated by a team of specialized engineers, using appropriate test suit metrics. Comparison results emphasize outstanding advantages of the proposed computational approach, such as: ease of calculation, better defined Pareto front and a larger number of Pareto solutions