Multi-objective optimal power management in microgrids: A comparative study

The design of Energy Management System involves important technological challenges to obtain optimal power management in microgrids, especially when two or more objectives must be reached. As an approach, several constrained multi-objective optimization (MO) algorithms partially can address optimal power management. For these cases, a decision-maker must choose not only the final set-points, but the best MO algorithm applied to the process. This paper presents a comparative study among four MO algorithms: MOGA, NSGAII, SPEA2 and IMOPSO to propose a comparative framework to ease choosing of a better MO algorithm. The comparative study proposes five criteria to evaluate the performance based on the average of: total operation costs, total emissions, energy share, runtime and non-dominated solutions in grid-connected mode. Results show IMOPSO offers overall better performance while MOGA provides good behavior in average of emissions and runtime. Nonetheless, this framework could improve decisions by increasing the set of criteria properly.