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Optimization of Fuzzy Energy Management System for Grid-Connected Microgrid Using NSGA-II

Lookup NU author(s): Tiong Teck Teo, Dr Thillainathan Logenthiran, Dr Wai Lok Woo, Dr Khalid Abidi, Dr Neal Wade, Dr David Greenwood, Dr Haris Patsios, Dr Thomas John, Professor Phil Taylor

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This is the authors' accepted manuscript of an article that has been published in its final definitive form by Institute of Electrical and Electronics Engineers, 2020.

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Abstract

This paper propose a fuzzy logic based energy management system (FEMS) for a grid-connected microgrid with renewable energy sources (RES) and energy storage system (ESS). The objectives of the FEMS are reducing the average peak load and operating cost through arbitrage operation of the ESS. These objectives are achieved by controlling the charge and discharge rate of the ESS based on the state-of-charge of ESS, the power difference between load and RES, and electricity market price. The effectiveness of the fuzzy logic greatly depends on the membership functions. The fuzzy membership functions of the FEMS are optimized offline using a Pareto based multi-objectiveevolutionary algorithm, non-dominated sorting genetic algorithm (NSGA-II). The best compromise solution is selected asthe final solution and implemented in the fuzzy logic controller. A comparison with other control strategies with similar objectives are carried out at a simulation level. The proposed FEMS is experimentally validated on a real microgrid in the energy storage test bed at Newcastle University, UK.


Publication metadata

Author(s): Teo TT, Logenthiran T, Woo WL, Abidi K, Wade NS, Greenwood DM, Patsios C, John T, Taylor PC

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Cybernetics

Year: 2020

Pages: epub ahead of print

Online publication date: 11/11/2020

Acceptance date: 06/10/2020

Date deposited: 02/08/2020

ISSN (print): 2168-2267

ISSN (electronic): 2168-2275

Publisher: Institute of Electrical and Electronics Engineers

URL: https://doi.org/10.1109/TCYB.2020.3031109

DOI: 10.1109/TCYB.2020.3031109


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