Probabilistic multi objective microgrid planning methodology for optimizing the ancillary services provision
Abstract Microgrids have attracted the attention of researchers and stakeholders because of their well known impacts and related benefits. Especially the provision of ancillary services has drawn attention. However, traditional planning should be re defined to optimally achieve such promising advantages, which leads to a complex decision making problem that should be progressively addressed with a more modern and comprehensive holistic approach. Hence, this paper proposes an enhanced version of the probabilistic multi objective microgrid planning methodology (POMMP2) that includes a novel strategy to apply graph partitioning and metaheuristic optimization to consider simultaneously the planning of a cluster based topology with the size and location of distributed energy resources under the paradigm of a microgrid with capacity for providing ancillary services. POMMP2 is tested in an adapted IEEE 37 node system, and NSGAII and AHP are used as optimization and decision making algorithms, respectively. Results show the benefits of a planning methodology viewed as a comprehensive problem and not a set of independent tasks.