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Impacts of home energy management systems on electricity consumption

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  • Tuomela, Sanna
  • de Castro Tomé, Mauricio
  • Iivari, Netta
  • Svento, Rauli

Abstract

Home energy management systems (HEMS) connect homes to a smart grid and may increase the overall use of renewable energy by directing energy demand to off-peak hours and increasing energy conservation. However, the promised changes in electricity consumption have yet to be proven in real-life experiments. We therefore analysed the changes in electricity consumption, daily consumption profiles, and number of low and high consumption hours after installing HEMS in 10 Finnish households. These changes were examined in the context of the values related to energy use in each household, which were derived from semi-structured interviews. In the real-life experiment, we showed that the HEMS reduced the total consumption of electricity in the winter months by up to 30%, shifted the consumption to off-peak hours and decreased the number of high consumption hours. These changes occurred even in the homes that valued comfort over savings or ecological sustainability. Nevertheless, the levels of energy conservation varied greatly between the households and between months in the same homes.

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  • Tuomela, Sanna & de Castro Tomé, Mauricio & Iivari, Netta & Svento, Rauli, 2021. "Impacts of home energy management systems on electricity consumption," Applied Energy, Elsevier, vol. 299(C).
    • Handle: RePEc:eee:appene:v:299:y:2021:i:c:s0306261921007224
    DOI: 10.1016/j.apenergy.2021.117310
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    3. Sayyed Ahmad Ali & Arif Hussain & Waseem Haider & Habib Ur Rehman & Syed Ali Abbas Kazmi, 2023. "Optimal Energy Management System of Isolated Multi-Microgrids with Local Energy Transactive Market with Indigenous PV-, Wind-, and Biomass-Based Resources," Energies, MDPI, vol. 16(4), pages 1-38, February.
    4. Hessam Golmohamadi, 2022. "Demand-Side Flexibility in Power Systems: A Survey of Residential, Industrial, Commercial, and Agricultural Sectors," Sustainability, MDPI, vol. 14(13), pages 1-16, June.
    5. Huang, Zhijia & Wang, Fang & Lu, Yuehong & Chen, Xiaofeng & Wu, Qiqi, 2023. "Optimization model for home energy management system of rural dwellings," Energy, Elsevier, vol. 283(C).
    6. Palaniappan, Somasundaram & Karuppannan, Sundararaju & Velusamy, Durgadevi, 2024. "Categorization of Indian residential consumers electrical energy consumption pattern using clustering and classification techniques," Energy, Elsevier, vol. 289(C).
    7. Minkyu Kim & Chankook Park, 2021. "Academic Topics Related to Household Energy Consumption Using the Future Sign Detection Technique," Energies, MDPI, vol. 14(24), pages 1-24, December.
    8. Youssef, Heba & Kamel, Salah & Hassan, Mohamed H. & Nasrat, Loai, 2023. "Optimizing energy consumption patterns of smart home using a developed elite evolutionary strategy artificial ecosystem optimization algorithm," Energy, Elsevier, vol. 278(C).

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