Optimal expansion planning of microgrids clusters: A robust collaborative approach

Abstract

Integrating electrical demands and distributed generators into microgrids facilitates their coordination and enables safe and reliable power supply to remote areas. When multiple microgrids share the same geographical area and transmission network, they can be organized into clusters to exchange energy in a peer-to-peer fashion, improving the overall efficiency and economy of the system. This paper proposes a novel methodology for optimal expansion planning of microgrid clusters, explicitly considering resource sharing. The model preserves the privacy of each microgrid by exchanging only boundary information. A three-level formulation is presented, incorporating uncertainties in renewable generation and demand through polyhedral uncertainty sets, whose bounds are determined using a novel clustering strategy. The resulting model is solved with a tailored algorithm based on robust optimization and a column-and-constraint generation scheme. The methodology is tested on a three-microgrid cluster, demonstrating its ability to manage uncertainty robustly and adapt to different levels of risk and budget constraints. In the case study, increasing robustness leads to higher costs (+31 %), lower renewable generation (-13 %), and increased unserved energy (+60 %). Finally, sensitivity analyses on fuel costs and the number of microgrids show that the proposed approach scales well with system size.