Multi-objective reactive power compensation

Reactive power compensation in electric systems is usually studied as a constrained single-objective optimization problem where an objective function is a linear combination of several factors, such as, investment and transmission losses. At the same time, constrains limit other parameters as reliability and voltage profile. This paper presents a new approach using multi-objective optimization evolutionary algorithms. It proposes a variant of the strength Pareto evolutionary algorithm (SPEA) that independently optimizes several parameters, turning most traditional constraints into new objective functions. That way, a wide set of optimal solutions, known as Pareto set, is found before deciding which solution best combines different features. Several sets of solutions calculated by different methods are compared to a Pareto set found with the proposed approach using appropriate test suite 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