A self-evolving type-2 fuzzy energy management strategy for multi-microgrid systems. (July 2020)

• Record Type: Journal Article
• Authors: Afrakhte, Hossein; Bayat, Peyman
• Is Part Of: Computers & electrical engineering. Volume 85(2020)
• Publication Date: 2020-07
• Subjects: Energy management -- Multi-microgrid (MMG) -- Reliability -- Shuffled complex evolution -- Type-2 fuzzy sets; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2020.106702
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: A robust EMS is introduced for the coordinated energy management of MMG systems with multiple resources, namely renewable and dispatchable DERs as well as BESSs. The system uses type-2 fuzzy sets with adaptive fuzzy rules and adaptive MFs. An improved heuristic optimization algorithm called TSSCE is presented to efficiently optimize the parameters of the proposed type-2 fuzzy based EMS during the system operation process. The study considers various uncertainties associated with the contingency faults. Based on both emergency and optimality conditions, the expert system proposed here attempts to design different strategies with different objective functions. An extensive modified reliability test system with MMGs is presented to investigate the performance and feasibility of the proposed method. Abstract: 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. Graphical abstract: Image, graphical abstract