A self-evolving type-2 fuzzy energy management strategy for multi-microgrid systems

The integration of several microgrids into conventional grids, which form multi-microgrid (MMG) systems, can increase operational complexity. Moreover, electric power networks are exposed to unpredictable faults, which directly affect energy management systems. From this point of view, this paper proposes a self-evolving type-2 fuzzy energy management strategy (EMS) to provide an optimized and coordinated energy management of MMG systems. In the proposed EMS, the probability of the failure is considered, and decentralized multi-operators determine their optimum energy management considering faulted and normal operation modes. For this purpose, an improved optimization algorithm called targeted search shuffled complex evolution is presented to tune the parameters of type-2 fuzzy sets for different operation modes that are challenging to improve due to our limited experience and knowledge. Finally, the effectiveness of the proposed method is demonstrated based on a modified reliability test system using various case studies. (c) 2020 Elsevier Ltd. All rights reserved.