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Microgrids energy management systems: A critical review on methods, solutions, and prospects

Zia, Muhammad Fahad, Elbouchikhi, Elhoussin, Benbouzid, Mohamed·2018·Applied Energy

Abstract

Abstract Renewable energy resources are currently being deployed on a large scale to meet the requirements of increased energy demand, mitigate the environmental pollutants, and achieve socio-economic benefits for sustainable development. The integration of such distributed energy sources into utility grid paves the way for microgrids. The microgrid concept is introduced to have a self-sustained system consisting of distributed energy resources that can operate in an islanded mode during grid failures. In microgrid, an energy management system is essential for optimal use of these distributed energy resources in intelligent, secure, reliable, and coordinated ways. Therefore, this review paper presents a comparative and critical analysis on decision making strategies and their solution methods for microgrid energy management systems. To manage the volatility and intermittency of renewable energy resources and load demand, various uncertainty quantification methods are summarized. A comparative analysis on communication technologies is also discussed for cost-effective implementation of microgrid energy management systems. Finally, insights into future directions and real world applications are provided.

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Metadata

Authors
Zia, M. F., Elbouchikhi, E., & Benbouzid, M.
Venue
Applied Energy
Publisher
Elsevier BV
Published
2018-07
Volume
222
Pages
1033-1055
ISSN
0306-2619 (ISSN-L)
OpenAlex
W2802339474
Cited by
1,005
References
1
FWCI
61.59
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Microgrids energy management systems: A critical review on methods, solutions, and prospects. https://app.cochat.ai/papers/10.1016/j.apenergy.2018.04.103
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Zia, M. F., Elbouchikhi, E., & Benbouzid, M. (2018). Microgrids energy management systems: A critical review on methods, solutions, and prospects. Applied Energy. https://doi.org/10.1016/j.apenergy.2018.04.103

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.