IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i15p5753-d1208612.html
   My bibliography  Save this article

Electric Energy Management in Buildings Based on the Internet of Things: A Systematic Review

Author

Listed:
  • Gleydson de Oliveira Cavalcanti

    (Federal Institute of Education, Science and Technology of Rio Grande do Norte, Campus—Natal Central, Research Centre in Sustainable Enterprise, Av. Sen. Salgado Filho, 1559, Tirol, Natal 59015-000, Brazil)

  • Handson Claudio Dias Pimenta

    (Federal Institute of Education, Science and Technology of Rio Grande do Norte, Campus—Natal Central, Research Centre in Sustainable Enterprise, Av. Sen. Salgado Filho, 1559, Tirol, Natal 59015-000, Brazil)

Abstract

The purpose of this paper is to uncover how the process of managing electricity in buildings based on the Internet of Things occurs. In particular, the work seeks to depict the factors affecting electricity consumption and management, as well as the application of the Internet of Things in energy management. A systematic literature review is used to examine the breadth of the electric energy management literature, encompassing bibliometric and thematic analysis based on an established procedure. The findings show the evolution of this field within key research networks with a few papers covering important elements of energy management, such as energy use, consumption and monitoring, assessment, and planning, in an integrative manner. Within this field, lacking in theory and practice, the originality of the work is the assembly of electric energy management into a conceptual framework based on real-time consumption and the Internet of Things (IoT). Indeed, the framework brings together the breadth of factors affecting consumption, energy use, and improvements that have been dispersed across the literature into one place. This framework, therefore, represents a stage towards an integrative view of IoT electric energy management and subsequent enhancement of theory and energy efficiency adoption.

Suggested Citation

  • Gleydson de Oliveira Cavalcanti & Handson Claudio Dias Pimenta, 2023. "Electric Energy Management in Buildings Based on the Internet of Things: A Systematic Review," Energies, MDPI, vol. 16(15), pages 1-29, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:15:p:5753-:d:1208612
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/15/5753/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/15/5753/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    2. Małgorzata Cygańska & Magdalena Kludacz-Alessandri, 2021. "Determinants of Electrical and Thermal Energy Consumption in Hospitals According to Climate Zones in Poland," Energies, MDPI, vol. 14(22), pages 1-24, November.
    3. Bilal Naji Alhasnawi & Basil H. Jasim & Maria Dolores Esteban & Josep M. Guerrero, 2020. "A Novel Smart Energy Management as a Service over a Cloud Computing Platform for Nanogrid Appliances," Sustainability, MDPI, vol. 12(22), pages 1-47, November.
    4. Joanna Kott & Marek Kott, 2019. "Generic Ontology of Energy Consumption Households," Energies, MDPI, vol. 12(19), pages 1-19, September.
    5. César Benavente-Peces, 2019. "On the Energy Efficiency in the Next Generation of Smart Buildings—Supporting Technologies and Techniques," Energies, MDPI, vol. 12(22), pages 1-25, November.
    6. Capozzoli, Alfonso & Piscitelli, Marco Savino & Brandi, Silvio & Grassi, Daniele & Chicco, Gianfranco, 2018. "Automated load pattern learning and anomaly detection for enhancing energy management in smart buildings," Energy, Elsevier, vol. 157(C), pages 336-352.
    7. Chung, William & Hui, Y.V. & Lam, Y. Miu, 2006. "Benchmarking the energy efficiency of commercial buildings," Applied Energy, Elsevier, vol. 83(1), pages 1-14, January.
    8. Simplice Igor Noubissie Tientcheu & Shyama P. Chowdhury & Thomas O. Olwal, 2019. "Intelligent Energy Management Strategy for Automated Office Buildings," Energies, MDPI, vol. 12(22), pages 1-27, November.
    9. Edwards, Erwin Elliot & Iyare, O.S. & Moseley, L.L., 2012. "Energy consumption in typical Caribbean office buildings: A potential short term solution to energy concerns," Renewable Energy, Elsevier, vol. 39(1), pages 154-161.
    10. Amasyali, Kadir & El-Gohary, Nora M., 2018. "A review of data-driven building energy consumption prediction studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1192-1205.
    11. Xiaolong Xu & Guohui Feng & Dandan Chi & Ming Liu & Baoyue Dou, 2018. "Optimization of Performance Parameter Design and Energy Use Prediction for Nearly Zero Energy Buildings," Energies, MDPI, vol. 11(12), pages 1-23, November.
    12. Fichera, Alberto & Frasca, Mattia & Palermo, Valentina & Volpe, Rosaria, 2018. "An optimization tool for the assessment of urban energy scenarios," Energy, Elsevier, vol. 156(C), pages 418-429.
    13. Liao, Huchang & Tang, Ming & Li, Zongmin & Lev, Benjamin, 2019. "Bibliometric analysis for highly cited papers in operations research and management science from 2008 to 2017 based on Essential Science Indicators," Omega, Elsevier, vol. 88(C), pages 223-236.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dominik Kowal & Małgorzata Radzik & Lucia Domaracká, 2024. "Assessment of the Level of Digitalization of Polish Enterprises in the Context of the Fourth Industrial Revolution," Sustainability, MDPI, vol. 16(13), pages 1-25, July.
    2. Maria G. Ioannides & Anastasios P. Stamelos & Stylianos A. Papazis & Erofili E. Stamataki & Michael E. Stamatakis, 2024. "Internet of Things-Based Control of Induction Machines: Specifics of Electric Drives and Wind Energy Conversion Systems," Energies, MDPI, vol. 17(3), pages 1-28, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pan Zhang & Yongjun Du & Sijie Han & Qingan Qiu, 2022. "Global Progress in Oil and Gas Well Research Using Bibliometric Analysis Based on VOSviewer and CiteSpace," Energies, MDPI, vol. 15(15), pages 1-27, July.
    2. Zhan, Sicheng & Liu, Zhaoru & Chong, Adrian & Yan, Da, 2020. "Building categorization revisited: A clustering-based approach to using smart meter data for building energy benchmarking," Applied Energy, Elsevier, vol. 269(C).
    3. Susie Ruqun WU & Gabriela Shirkey & Ilke Celik & Changliang Shao & Jiquan Chen, 2022. "A Review on the Adoption of AI, BC, and IoT in Sustainability Research," Sustainability, MDPI, vol. 14(13), pages 1-25, June.
    4. Xiao Han & Chu Wei, 2021. "Household energy consumption: state of the art, research gaps, and future prospects," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 12479-12504, August.
    5. Romero-Silva, Rodrigo & de Leeuw, Sander, 2021. "Learning from the past to shape the future: A comprehensive text mining analysis of OR/MS reviews," Omega, Elsevier, vol. 100(C).
    6. Fan, Cheng & Xiao, Fu & Song, Mengjie & Wang, Jiayuan, 2019. "A graph mining-based methodology for discovering and visualizing high-level knowledge for building energy management," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    7. Chen, Yibo & Zhang, Fengyi & Berardi, Umberto, 2020. "Day-ahead prediction of hourly subentry energy consumption in the building sector using pattern recognition algorithms," Energy, Elsevier, vol. 211(C).
    8. Chen, Zhelun & O’Neill, Zheng & Wen, Jin & Pradhan, Ojas & Yang, Tao & Lu, Xing & Lin, Guanjing & Miyata, Shohei & Lee, Seungjae & Shen, Chou & Chiosa, Roberto & Piscitelli, Marco Savino & Capozzoli, , 2023. "A review of data-driven fault detection and diagnostics for building HVAC systems," Applied Energy, Elsevier, vol. 339(C).
    9. Kazimierz Kawa & Rafał Mularczyk & Waldemar Bauer & Katarzyna Grobler-Dębska & Edyta Kucharska, 2024. "Prediction of Energy Consumption on Example of Heterogenic Commercial Buildings," Energies, MDPI, vol. 17(13), pages 1-16, June.
    10. Merve Anaç & Gulden Gumusburun Ayalp & Kamil Erdayandi, 2023. "Prefabricated Construction Risks: A Holistic Exploration through Advanced Bibliometric Tool and Content Analysis," Sustainability, MDPI, vol. 15(15), pages 1-31, August.
    11. Fredrik Skaug Fadnes & Reyhaneh Banihabib & Mohsen Assadi, 2023. "Using Artificial Neural Networks to Gather Intelligence on a Fully Operational Heat Pump System in an Existing Building Cluster," Energies, MDPI, vol. 16(9), pages 1-33, May.
    12. Quan-Hoang Vuong & Huyen Thanh T. Nguyen & Thanh-Hang Pham & Manh-Toan Ho & Minh-Hoang Nguyen, 2021. "Assessing the ideological homogeneity in entrepreneurial finance research by highly cited publications," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-11, December.
    13. Shuangqing Sheng & Wei Song & Hua Lian & Lei Ning, 2022. "Review of Urban Land Management Based on Bibliometrics," Land, MDPI, vol. 11(11), pages 1-25, November.
    14. Maksym Obrizan, 2018. "Economists in Ukraine: who are they and where do they publish?," Working Papers 3181, Research Consulting and Development.
    15. Hongxia Jin & Lu Lu & Haojun Fan, 2022. "Global Trends and Research Hotspots in Long COVID: A Bibliometric Analysis," IJERPH, MDPI, vol. 19(6), pages 1-14, March.
    16. Xavier Serrano-Guerrero & Guillermo Escrivá-Escrivá & Santiago Luna-Romero & Jean-Michel Clairand, 2020. "A Time-Series Treatment Method to Obtain Electrical Consumption Patterns for Anomalies Detection Improvement in Electrical Consumption Profiles," Energies, MDPI, vol. 13(5), pages 1-23, February.
    17. Zoltán Lakner & Brigitta Plasek & Gyula Kasza & Anna Kiss & Sándor Soós & Ágoston Temesi, 2021. "Towards Understanding the Food Consumer Behavior–Food Safety–Sustainability Triangle: A Bibliometric Approach," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    18. Ying Liang & Wei Song, 2022. "Ecological and Environmental Effects of Land Use and Cover Changes on the Qinghai-Tibetan Plateau: A Bibliometric Review," Land, MDPI, vol. 11(12), pages 1-23, November.
    19. Lanzalonga Federico & Chmet Federico & Petrolo Basilio & Brescia Valerio, 2023. "Exploring Diversity Management to Avoid Social Washing and Pinkwashing: Using Bibliometric Analysis to Shape Future Research Directions," Journal of Intercultural Management, Sciendo, vol. 15(1), pages 41-65, March.
    20. Jussi T. S. Heikkila, 2020. "Classifying economics for the common good: Connecting sustainable development goals to JEL codes," Papers 2004.04384, arXiv.org.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:15:p:5753-:d:1208612. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.