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Lookup NU author(s): Tiong Teck Teo, Dr Thillainathan Logenthiran, Dr Wai Lok Woo, Dr Khalid Abidi, Dr Neal WadeORCiD, Dr David Greenwood, Professor Haris Patsios, Dr Thomas John, Professor Phil Taylor
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, 2021.
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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.
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: 2021
Volume: 51
Issue: 11
Pages: 5375-5386
Print publication date: 01/11/2021
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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