Modeling and managing residential energy demand for a low-carbon future
Achieving a decarbonized society requires balancing two critical and seemingly conflicting objectives: reducing energy consumption and ensuring energy demand flexibility to adapt to the variability of renewable energy production. This study introduces ''energy demand science'' as...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Energy Strategy Reviews |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211467X24003195 |
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| author | Chang Zhang Mirzat Ullah Hind Alofaysan Hakimjon Hakimov Sophia Audrey |
| author_facet | Chang Zhang Mirzat Ullah Hind Alofaysan Hakimjon Hakimov Sophia Audrey |
| author_sort | Chang Zhang |
| collection | DOAJ |
| description | Achieving a decarbonized society requires balancing two critical and seemingly conflicting objectives: reducing energy consumption and ensuring energy demand flexibility to adapt to the variability of renewable energy production. This study introduces ''energy demand science'' as a multidisciplinary field to address these challenges, focusing on the residential sector, which significantly impacts energy use due to occupant behavior and lifestyle. Using a comprehensive review of literature and advanced modeling techniques, this research explores mechanisms driving energy demand. Key results show that energy demand can be reduced by up to 40 % by 2050 through lifestyle adjustments, urbanization, and innovative technologies, aligning with global warming targets below 1.5 °C. Advanced modeling techniques and high-resolution data analyses were employed to explore mechanisms driving energy demand, supported by historical data from 1970 to present, incorporating advancements in IoT and smart metering technologies. The results highlight the importance of integrating technological, human, natural, and socio-economic factors to achieve a sustainable reduction in energy use while maintaining flexibility. Policy implications emphasize the need for holistic, interdisciplinary strategies to enable efficient demand-side management, enhance renewable energy integration, and align energy consumption with decarbonization goals. |
| format | Article |
| id | doaj-art-543c8033117a4e51bc897c10759cd80c |
| institution | OA Journals |
| issn | 2211-467X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Strategy Reviews |
| spelling | doaj-art-543c8033117a4e51bc897c10759cd80c2025-08-20T02:37:04ZengElsevierEnergy Strategy Reviews2211-467X2025-01-015710161010.1016/j.esr.2024.101610Modeling and managing residential energy demand for a low-carbon futureChang Zhang0Mirzat Ullah1Hind Alofaysan2Hakimjon Hakimov3Sophia Audrey4School of Public Administration, Northwest University, Shaanxi, 710127, China; Corresponding author. School of Public Administration, Northwest University, Shaanxi, 710127, China.Graduate School of Economics and Management Ural Federal University, Yekaterinburg, 62002, RussiaDepartment of Economics, College of Business Administration, Princes, Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi ArabiaDeputy Head of Academic Affairs Department, Tashkent State University of Economics, UzbekistanYanshan University, ChinaAchieving a decarbonized society requires balancing two critical and seemingly conflicting objectives: reducing energy consumption and ensuring energy demand flexibility to adapt to the variability of renewable energy production. This study introduces ''energy demand science'' as a multidisciplinary field to address these challenges, focusing on the residential sector, which significantly impacts energy use due to occupant behavior and lifestyle. Using a comprehensive review of literature and advanced modeling techniques, this research explores mechanisms driving energy demand. Key results show that energy demand can be reduced by up to 40 % by 2050 through lifestyle adjustments, urbanization, and innovative technologies, aligning with global warming targets below 1.5 °C. Advanced modeling techniques and high-resolution data analyses were employed to explore mechanisms driving energy demand, supported by historical data from 1970 to present, incorporating advancements in IoT and smart metering technologies. The results highlight the importance of integrating technological, human, natural, and socio-economic factors to achieve a sustainable reduction in energy use while maintaining flexibility. Policy implications emphasize the need for holistic, interdisciplinary strategies to enable efficient demand-side management, enhance renewable energy integration, and align energy consumption with decarbonization goals.http://www.sciencedirect.com/science/article/pii/S2211467X24003195Energy demand modelingHigh spatiotemporal resolutionSocio-demographic factorsEnergy conservation behaviorsTheory-driven methods |
| spellingShingle | Chang Zhang Mirzat Ullah Hind Alofaysan Hakimjon Hakimov Sophia Audrey Modeling and managing residential energy demand for a low-carbon future Energy Strategy Reviews Energy demand modeling High spatiotemporal resolution Socio-demographic factors Energy conservation behaviors Theory-driven methods |
| title | Modeling and managing residential energy demand for a low-carbon future |
| title_full | Modeling and managing residential energy demand for a low-carbon future |
| title_fullStr | Modeling and managing residential energy demand for a low-carbon future |
| title_full_unstemmed | Modeling and managing residential energy demand for a low-carbon future |
| title_short | Modeling and managing residential energy demand for a low-carbon future |
| title_sort | modeling and managing residential energy demand for a low carbon future |
| topic | Energy demand modeling High spatiotemporal resolution Socio-demographic factors Energy conservation behaviors Theory-driven methods |
| url | http://www.sciencedirect.com/science/article/pii/S2211467X24003195 |
| work_keys_str_mv | AT changzhang modelingandmanagingresidentialenergydemandforalowcarbonfuture AT mirzatullah modelingandmanagingresidentialenergydemandforalowcarbonfuture AT hindalofaysan modelingandmanagingresidentialenergydemandforalowcarbonfuture AT hakimjonhakimov modelingandmanagingresidentialenergydemandforalowcarbonfuture AT sophiaaudrey modelingandmanagingresidentialenergydemandforalowcarbonfuture |