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Advanced Control Methods and Optimization Techniques for Microgrid Planning: A Review.

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Title: Advanced Control Methods and Optimization Techniques for Microgrid Planning: A Review.
Authors: Bentata, Ahlame1 (AUTHOR), El Aazzaoui, Omar2 (AUTHOR), Oproescu, Mihai3 (AUTHOR), Errouha, Mustapha4 (AUTHOR), El Ouanjli, Najib5 (AUTHOR), Bossoufi, Badre1 (AUTHOR)
Source: Energies (19961073). May2026, Vol. 19 Issue 9, p2019. 34p.
Subject Terms: *Microgrids, *Artificial intelligence, *Renewable energy source management, *Cascade control, *Energy storage, *Mathematical optimization, *Internet security, *Clean energy
Abstract: The increasing emphasis on sustainable and decentralized energy has elevated microgrids as a central element of modern power systems. By integrating renewable energy sources, advanced energy storage technologies, and intelligent control strategies, microgrids enhance efficiency, stability, and flexibility and play a vital role in creating resilient and adaptable energy networks. This review provides a comprehensive analysis of Energy Management Systems (EMSs) in microgrids, distinguishing between planning-oriented tools for techno-economic evaluation and control-oriented platforms for real-time operation and optimization. Hierarchical control architectures spanning primary, secondary, and tertiary levels are examined, highlighting their roles in frequency and voltage regulation, load sharing, and economic dispatch. Optimization techniques for EMSs are analyzed across deterministic, stochastic, metaheuristic, and artificial intelligence/machine learning methods, addressing objectives, constraints, uncertainties, and multi-timeframe decision-making. AI-based methods, including supervised learning, deep learning, and reinforcement learning, are highlighted for their ability to enhance predictive control, system autonomy, and operational efficiency, despite their computational demands. Future trends emphasize AI-based predictive control, deep learning for energy forecasting, multi-microgrid coordination, hybrid energy storage management, and cybersecurity enhancements. Overall, an intelligent EMS, combined with innovative technologies, is critical for developing resilient, scalable, and sustainable microgrid solutions that meet the evolving demands of modern energy systems. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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  Availability: 1
Header DbId: enr
DbLabel: Energy & Power Source
An: 193715915
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Advanced Control Methods and Optimization Techniques for Microgrid Planning: A Review.
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. May2026, Vol. 19 Issue 9, p2019. 34p.
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  Data: *<searchLink fieldCode="DE" term="%22Microgrids%22">Microgrids</searchLink><br />*<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Renewable+energy+source+management%22">Renewable energy source management</searchLink><br />*<searchLink fieldCode="DE" term="%22Cascade+control%22">Cascade control</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+storage%22">Energy storage</searchLink><br />*<searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br />*<searchLink fieldCode="DE" term="%22Internet+security%22">Internet security</searchLink><br />*<searchLink fieldCode="DE" term="%22Clean+energy%22">Clean energy</searchLink>
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  Data: The increasing emphasis on sustainable and decentralized energy has elevated microgrids as a central element of modern power systems. By integrating renewable energy sources, advanced energy storage technologies, and intelligent control strategies, microgrids enhance efficiency, stability, and flexibility and play a vital role in creating resilient and adaptable energy networks. This review provides a comprehensive analysis of Energy Management Systems (EMSs) in microgrids, distinguishing between planning-oriented tools for techno-economic evaluation and control-oriented platforms for real-time operation and optimization. Hierarchical control architectures spanning primary, secondary, and tertiary levels are examined, highlighting their roles in frequency and voltage regulation, load sharing, and economic dispatch. Optimization techniques for EMSs are analyzed across deterministic, stochastic, metaheuristic, and artificial intelligence/machine learning methods, addressing objectives, constraints, uncertainties, and multi-timeframe decision-making. AI-based methods, including supervised learning, deep learning, and reinforcement learning, are highlighted for their ability to enhance predictive control, system autonomy, and operational efficiency, despite their computational demands. Future trends emphasize AI-based predictive control, deep learning for energy forecasting, multi-microgrid coordination, hybrid energy storage management, and cybersecurity enhancements. Overall, an intelligent EMS, combined with innovative technologies, is critical for developing resilient, scalable, and sustainable microgrid solutions that meet the evolving demands of modern energy systems. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=193715915
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.3390/en19092019
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 34
        StartPage: 2019
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      – SubjectFull: Microgrids
        Type: general
      – SubjectFull: Artificial intelligence
        Type: general
      – SubjectFull: Renewable energy source management
        Type: general
      – SubjectFull: Cascade control
        Type: general
      – SubjectFull: Energy storage
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Internet security
        Type: general
      – SubjectFull: Clean energy
        Type: general
    Titles:
      – TitleFull: Advanced Control Methods and Optimization Techniques for Microgrid Planning: A Review.
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            NameFull: Bentata, Ahlame
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            NameFull: El Aazzaoui, Omar
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            NameFull: Oproescu, Mihai
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            NameFull: El Ouanjli, Najib
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            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
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              Value: 19
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            – TitleFull: Energies (19961073)
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