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Recent Techniques Used in Home Energy Management Systems: A Review

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  • Isaías Gomes

    (Faculty of Science & Technology, University of Algarve, 8005-294 Faro, Portugal
    IDMEC, Instituto Superior Técnico, Universidade de Lisboa, 1950-044 Lisboa, Portugal
    ICT, University of Évora, 7002-554 Evora, Portugal)

  • Karol Bot

    (Faculty of Science & Technology, University of Algarve, 8005-294 Faro, Portugal)

  • Maria Graça Ruano

    (Faculty of Science & Technology, University of Algarve, 8005-294 Faro, Portugal
    CISUC, University of Coimbra, 3030-290 Coimbra, Portugal)

  • António Ruano

    (Faculty of Science & Technology, University of Algarve, 8005-294 Faro, Portugal
    IDMEC, Instituto Superior Técnico, Universidade de Lisboa, 1950-044 Lisboa, Portugal)

Abstract

Power systems are going through a transition period. Consumers want more active participation in electric system management, namely assuming the role of producers–consumers, prosumers in short. The prosumers’ energy production is heavily based on renewable energy sources, which, besides recognized environmental benefits, entails energy management challenges. For instance, energy consumption of appliances in a home can lead to misleading patterns. Another challenge is related to energy costs since inefficient systems or unbalanced energy control may represent economic loss to the prosumer. The so-called home energy management systems (HEMS) emerge as a solution. When well-designed HEMS allow prosumers to reach higher levels of energy management, this ensures optimal management of assets and appliances. This paper aims to present a comprehensive systematic review of the literature on optimization techniques recently used in the development of HEMS, also taking into account the key factors that can influence the development of HEMS at a technical and computational level. The systematic review covers the period 2018–2021. As a result of the review, the major developments in the field of HEMS in recent years are presented in an integrated manner. In addition, the techniques are divided into four broad categories: traditional techniques, model predictive control, heuristics and metaheuristics, and other techniques.

Suggested Citation

  • Isaías Gomes & Karol Bot & Maria Graça Ruano & António Ruano, 2022. "Recent Techniques Used in Home Energy Management Systems: A Review," Energies, MDPI, vol. 15(8), pages 1-41, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:8:p:2866-:d:793662
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    1. Bui, Van-Hai & Hussain, Akhtar & Im, Yong-Hoon & Kim, Hak-Man, 2019. "An internal trading strategy for optimal energy management of combined cooling, heat and power in building microgrids," Applied Energy, Elsevier, vol. 239(C), pages 536-548.
    2. Fontenot, Hannah & Dong, Bing, 2019. "Modeling and control of building-integrated microgrids for optimal energy management – A review," Applied Energy, Elsevier, vol. 254(C).
    3. Lu, Qing & Lü, Shuaikang & Leng, Yajun & Zhang, Zhixin, 2020. "Optimal household energy management based on smart residential energy hub considering uncertain behaviors," Energy, Elsevier, vol. 195(C).
    4. Javadi, Mohammad Sadegh & Gough, Matthew & Lotfi, Mohamed & Esmaeel Nezhad, Ali & Santos, Sérgio F. & Catalão, João P.S., 2020. "Optimal self-scheduling of home energy management system in the presence of photovoltaic power generation and batteries," Energy, Elsevier, vol. 210(C).
    5. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2018. "Optimal operation of an energy management system for a grid-connected smart building considering photovoltaics’ uncertainty and stochastic electric vehicles’ driving schedule," Applied Energy, Elsevier, vol. 210(C), pages 1188-1206.
    6. Lu, Renzhi & Hong, Seung Ho, 2019. "Incentive-based demand response for smart grid with reinforcement learning and deep neural network," Applied Energy, Elsevier, vol. 236(C), pages 937-949.
    7. Younès Dagdougui & Ahmed Ouammi & Rachid Benchrifa, 2020. "Energy Management-Based Predictive Controller for a Smart Building Powered by Renewable Energy," Sustainability, MDPI, vol. 12(10), pages 1-18, May.
    8. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    9. Nikolaos Koltsaklis & Ioannis P. Panapakidis & David Pozo & Georgios C. Christoforidis, 2021. "A Prosumer Model Based on Smart Home Energy Management and Forecasting Techniques," Energies, MDPI, vol. 14(6), pages 1-32, March.
    10. Killian, M. & Zauner, M. & Kozek, M., 2018. "Comprehensive smart home energy management system using mixed-integer quadratic-programming," Applied Energy, Elsevier, vol. 222(C), pages 662-672.
    11. Bharath Varsh Rao & Friederich Kupzog & Martin Kozek, 2018. "Phase Balancing Home Energy Management System Using Model Predictive Control," Energies, MDPI, vol. 11(12), pages 1-19, November.
    12. Zheng, Zhuang & Sun, Zhankun & Pan, Jia & Luo, Xiaowei, 2021. "An integrated smart home energy management model based on a pyramid taxonomy for residential houses with photovoltaic-battery systems," Applied Energy, Elsevier, vol. 298(C).
    13. Parrish, Bryony & Heptonstall, Phil & Gross, Rob & Sovacool, Benjamin K., 2020. "A systematic review of motivations, enablers and barriers for consumer engagement with residential demand response," Energy Policy, Elsevier, vol. 138(C).
    14. Keon Baek & Woong Ko & Jinho Kim, 2019. "Optimal Scheduling of Distributed Energy Resources in Residential Building under the Demand Response Commitment Contract," Energies, MDPI, vol. 12(14), pages 1-19, July.
    15. Makhadmeh, Sharif Naser & Khader, Ahamad Tajudin & Al-Betar, Mohammed Azmi & Naim, Syibrah & Abasi, Ammar Kamal & Alyasseri, Zaid Abdi Alkareem, 2019. "Optimization methods for power scheduling problems in smart home: Survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    16. Karol Bot & Samira Santos & Inoussa Laouali & Antonio Ruano & Maria da Graça Ruano, 2021. "Design of Ensemble Forecasting Models for Home Energy Management Systems," Energies, MDPI, vol. 14(22), pages 1-37, November.
    17. Zafar Iqbal & Nadeem Javaid & Saleem Iqbal & Sheraz Aslam & Zahoor Ali Khan & Wadood Abdul & Ahmad Almogren & Atif Alamri, 2018. "A Domestic Microgrid with Optimized Home Energy Management System," Energies, MDPI, vol. 11(4), pages 1-39, April.
    18. Dimitrios Kontogiannis & Dimitrios Bargiotas & Aspassia Daskalopulu, 2021. "Fuzzy Control System for Smart Energy Management in Residential Buildings Based on Environmental Data," Energies, MDPI, vol. 14(3), pages 1-18, February.
    19. Xin Chen & Melvyn Sim & Peng Sun, 2007. "A Robust Optimization Perspective on Stochastic Programming," Operations Research, INFORMS, vol. 55(6), pages 1058-1071, December.
    20. Victor J. Gutierrez-Martinez & Carlos A. Moreno-Bautista & Jose M. Lozano-Garcia & Alejandro Pizano-Martinez & Enrique A. Zamora-Cardenas & Miguel A. Gomez-Martinez, 2019. "A Heuristic Home Electric Energy Management System Considering Renewable Energy Availability," Energies, MDPI, vol. 12(4), pages 1-20, February.
    21. Muhammad Kashif Rafique & Zunaib Maqsood Haider & Khawaja Khalid Mehmood & Muhammad Saeed Uz Zaman & Muhammad Irfan & Saad Ullah Khan & Chul-Hwan Kim, 2018. "Optimal Scheduling of Hybrid Energy Resources for a Smart Home," Energies, MDPI, vol. 11(11), pages 1-19, November.
    22. Beaudin, Marc & Zareipour, Hamidreza, 2015. "Home energy management systems: A review of modelling and complexity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 318-335.
    23. H. A. Eiselt & C. -L. Sandblom, 2007. "Linear Programming and its Applications," Springer Books, Springer, number 978-3-540-73671-4, October.
    24. Khan, Ahsan Raza & Mahmood, Anzar & Safdar, Awais & Khan, Zafar A. & Khan, Naveed Ahmed, 2016. "Load forecasting, dynamic pricing and DSM in smart grid: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1311-1322.
    25. Ponce, Pedro & Polasko, Kenneth & Molina, Arturo, 2016. "End user perceptions toward smart grid technology: Acceptance, adoption, risks, and trust," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 587-598.
    26. Sadaqat Ali & Zhixue Zheng & Michel Aillerie & Jean-Paul Sawicki & Marie-Cécile Péra & Daniel Hissel, 2021. "A Review of DC Microgrid Energy Management Systems Dedicated to Residential Applications," Energies, MDPI, vol. 14(14), pages 1-26, July.
    27. Mehrjerdi, Hasan & Hemmati, Reza, 2020. "Coordination of vehicle-to-home and renewable capacity resources for energy management in resilience and self-healing building," Renewable Energy, Elsevier, vol. 146(C), pages 568-579.
    28. Nikos Kampelis & Elisavet Tsekeri & Dionysia Kolokotsa & Kostas Kalaitzakis & Daniela Isidori & Cristina Cristalli, 2018. "Development of Demand Response Energy Management Optimization at Building and District Levels Using Genetic Algorithm and Artificial Neural Network Modelling Power Predictions," Energies, MDPI, vol. 11(11), pages 1-22, November.
    29. Karol Bot & Inoussa Laouali & António Ruano & Maria da Graça Ruano, 2021. "Home Energy Management Systems with Branch-and-Bound Model-Based Predictive Control Techniques," Energies, MDPI, vol. 14(18), pages 1-27, September.
    30. Moyer, Jonathan D. & Hughes, Barry B., 2012. "ICTs: Do they contribute to increased carbon emissions?," Technological Forecasting and Social Change, Elsevier, vol. 79(5), pages 919-931.
    31. Jones, D. F. & Mirrazavi, S. K. & Tamiz, M., 2002. "Multi-objective meta-heuristics: An overview of the current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 137(1), pages 1-9, February.
    32. Aqib Jamil & Turki Ali Alghamdi & Zahoor Ali Khan & Sakeena Javaid & Abdul Haseeb & Zahid Wadud & Nadeem Javaid, 2019. "An Innovative Home Energy Management Model with Coordination among Appliances using Game Theory," Sustainability, MDPI, vol. 11(22), pages 1-23, November.
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    2. Inoussa Laouali & Isaías Gomes & Maria da Graça Ruano & Saad Dosse Bennani & Hakim El Fadili & Antonio Ruano, 2022. "Energy Disaggregation Using Multi-Objective Genetic Algorithm Designed Neural Networks," Energies, MDPI, vol. 15(23), pages 1-29, November.

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