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Optimization Strategies in Residential Energy Management Systems: A Comprehensive Review.

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Title: Optimization Strategies in Residential Energy Management Systems: A Comprehensive Review.
Authors: Alsultan, Aqeel Mezher Thajeel, Bani, Nurul Aini, Muhtazaruddin, Mohd Nabil, Muhammad-Sukki, Firdaus, Usman, Sahnius, Ahmad, Nurfadzilah, Kamarudin, Mohd Khairul Amri, Zulkipli, Muhammad, Boshagh, Fatemeh
Source: International Journal of Energy Research; 6/16/2026, Vol. 2026, p1-39, 39p
Subject Terms: Mathematical optimization, Energy management, Renewable energy sources, Home energy use, Heuristic, Predictive control systems
Abstract: The energy industry is undergoing a series of profound changes, leading to increased participation of consumers in grid operation. Prosumers, namely consumers who use energy and also produce it, are relying more on domestic renewable energy sources that offer environmental benefits but also impose new demands on the governance of these energies. A reliable energy supply in residential areas is an important issue; thus, poor management may cause interruptions and high operation costs. Home energy management systems (EMS) help consumers in overcoming these challenges by reducing energy usage for better cost savings while improving grid resiliency. This paper provides a complete study of the developmental techniques utilized at these systems, focusing on technical as well as computational aspects. The literature review is systematically classified into four categories: classical mathematical optimization, model predictive control (MPC), heuristics and metaheuristics, and other iterative control strategies. The period from 2019 to 2025 is examined, highlighting the need for clear ontology analysis due to the rapid growth of IoT‐oriented EMSs, increased use of renewable generation, and the expansion of artificial intelligence (AI)–based solutions for optimization. The review highlights both current advancements and existing limitations in the field. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Energy Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Optimization Strategies in Residential Energy Management Systems: A Comprehensive Review.
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  Data: <searchLink fieldCode="AR" term="%22Alsultan%2C+Aqeel+Mezher+Thajeel%22">Alsultan, Aqeel Mezher Thajeel</searchLink><br /><searchLink fieldCode="AR" term="%22Bani%2C+Nurul+Aini%22">Bani, Nurul Aini</searchLink><br /><searchLink fieldCode="AR" term="%22Muhtazaruddin%2C+Mohd+Nabil%22">Muhtazaruddin, Mohd Nabil</searchLink><br /><searchLink fieldCode="AR" term="%22Muhammad-Sukki%2C+Firdaus%22">Muhammad-Sukki, Firdaus</searchLink><br /><searchLink fieldCode="AR" term="%22Usman%2C+Sahnius%22">Usman, Sahnius</searchLink><br /><searchLink fieldCode="AR" term="%22Ahmad%2C+Nurfadzilah%22">Ahmad, Nurfadzilah</searchLink><br /><searchLink fieldCode="AR" term="%22Kamarudin%2C+Mohd+Khairul+Amri%22">Kamarudin, Mohd Khairul Amri</searchLink><br /><searchLink fieldCode="AR" term="%22Zulkipli%2C+Muhammad%22">Zulkipli, Muhammad</searchLink><br /><searchLink fieldCode="AR" term="%22Boshagh%2C+Fatemeh%22">Boshagh, Fatemeh</searchLink>
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  Data: International Journal of Energy Research; 6/16/2026, Vol. 2026, p1-39, 39p
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  Data: <searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+management%22">Energy management</searchLink><br /><searchLink fieldCode="DE" term="%22Renewable+energy+sources%22">Renewable energy sources</searchLink><br /><searchLink fieldCode="DE" term="%22Home+energy+use%22">Home energy use</searchLink><br /><searchLink fieldCode="DE" term="%22Heuristic%22">Heuristic</searchLink><br /><searchLink fieldCode="DE" term="%22Predictive+control+systems%22">Predictive control systems</searchLink>
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  Label: Abstract
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  Data: The energy industry is undergoing a series of profound changes, leading to increased participation of consumers in grid operation. Prosumers, namely consumers who use energy and also produce it, are relying more on domestic renewable energy sources that offer environmental benefits but also impose new demands on the governance of these energies. A reliable energy supply in residential areas is an important issue; thus, poor management may cause interruptions and high operation costs. Home energy management systems (EMS) help consumers in overcoming these challenges by reducing energy usage for better cost savings while improving grid resiliency. This paper provides a complete study of the developmental techniques utilized at these systems, focusing on technical as well as computational aspects. The literature review is systematically classified into four categories: classical mathematical optimization, model predictive control (MPC), heuristics and metaheuristics, and other iterative control strategies. The period from 2019 to 2025 is examined, highlighting the need for clear ontology analysis due to the rapid growth of IoT‐oriented EMSs, increased use of renewable generation, and the expansion of artificial intelligence (AI)–based solutions for optimization. The review highlights both current advancements and existing limitations in the field. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Energy Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1155/er/6685065
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        Text: English
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        PageCount: 39
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      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Energy management
        Type: general
      – SubjectFull: Renewable energy sources
        Type: general
      – SubjectFull: Home energy use
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      – SubjectFull: Heuristic
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      – SubjectFull: Predictive control systems
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      – TitleFull: Optimization Strategies in Residential Energy Management Systems: A Comprehensive Review.
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              Text: 6/16/2026
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