Fuzzy Adaptive Granulation Multi-Objective Multi-microgrid Energy Management

Sabahi, F.

doi:10.22044/jadm.2019.6985.1828

Document Type : Original/Review Paper

Author

F. Sabahi

Department of Electrical Engineering, Faculty of Engineering, Urmia University, Urmia, Iran.

https://doi.org/10.22044/jadm.2019.6985.1828

Abstract

This paper develops an energy management approach for a multi-microgrid (MMG) taking into account multiple objectives involving plug-in electric vehicle (PEV), photovoltaic (PV) power, and a distribution static compensator (DSTATCOM) to improve power provision sharing. In the proposed approach, there is a pool of fuzzy microgrids granules that they compete with each other to prolong their lives while monitored and evaluated by the specific fuzzy sets. In addition, based on the hourly reconfiguration of microgrids (MGs), granules learn to dispatch cost-effective resources. To promote interactive service, a well-defined, multi-objective approach is derived from fuzzy granulation analysis to improve power quality in MMGs. A combination of the meta-heuristic approach of genetic algorithm (GA) and particle swarm optimization (PSO) eliminates the computational difficulty of the nonlinearity and uncertainty analysis of the system and improves the precision of the results. The proposed approach is successfully applied to a 69-bus MMG test with results reported in terms of stored energy improvement, daily voltage profile improvement, MMG operations, and cost reduction.

Keywords

Main Subjects

A.10. Power Management

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Fuzzy Adaptive Granulation Multi-Objective Multi-microgrid Energy Management

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Volume 8, Issue 4November 2020Pages 481-489

Volume 8, Issue 4
November 2020
Pages 481-489