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Social impact of decarbonization objectives through smart homes: Survey and analysis

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  • Lazaroiu, Alexandra Catalina
  • Roscia, Mariacristina
  • Dancu, Vasile Sebastian
  • Balaban, Georgiana

Abstract

The technological development and economic growth of renewable energy are the key solution for almost full decarbonization of the energy systems. The sustainability and energy efficiency, artificial intelligence and connectivity will be the determining elements towards reaching this ambitious goal. Household appliances and tools for controlling energy consumption, temperature, lighting, etc. In the smart home will play a key role to increase awareness of families' energy consumption. IoT (Internet of Things) devices for the smart home allow us to monitor consumption and pay attention to efficiently energy use. However, savings are not the only important element of the smart home. Together with the digital control of the home these are elements that include a fundamental dimension: decarbonization, which is the cornerstone of the energy transition, which must involve an epochal change of mentality to our society where digitalization and people's well-being meet. The paper deals with social analysis of large cities population perception on integrating renewable energy sources and necessary devices to transform existing houses in smart homes towards economic wellbeing and decarbonization of the energy sector. Different classes of respondents were interviewed – owned and rented fome, rural and urban inhabitants, different segments of age, various number of inhabitants in urban areas and the capital, women and men, high-income and low-income, different levels of education – to support or disregard smart home technological development and reveal the different perception towards further usage of smart devices for daily benefits.

Suggested Citation

  • Lazaroiu, Alexandra Catalina & Roscia, Mariacristina & Dancu, Vasile Sebastian & Balaban, Georgiana, 2024. "Social impact of decarbonization objectives through smart homes: Survey and analysis," Renewable Energy, Elsevier, vol. 230(C).
    • Handle: RePEc:eee:renene:v:230:y:2024:i:c:s0960148124009406
    DOI: 10.1016/j.renene.2024.120872
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    References listed on IDEAS

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    1. Li, Zhen & Niu, Shuwen & Halleck Vega, Sol Maria & Wang, Jinnian & Wang, Dakang & Yang, Xiankun, 2024. "Electrification and residential well-being in China," Energy, Elsevier, vol. 294(C).
    2. Li, Hui & Li, Yue & Zheng, Guoliang & Zhou, You, 2024. "Interaction between household energy consumption and health: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    3. Jiao, Jianling & Song, Jiangfeng & Ding, Tao, 2024. "The impact of synergistic development of renewable energy and digital economy on energy intensity: Evidence from 33 countries," Energy, Elsevier, vol. 295(C).
    4. Sima, Catalina Alexandra & Roscia, Mariacristina & Dancu, Vasile Sebastian, 2022. "Social behavior analysis for improving the positive energy transition," Renewable Energy, Elsevier, vol. 196(C), pages 1325-1344.
    5. Tostado-Véliz, Marcos & Icaza-Alvarez, Daniel & Jurado, Francisco, 2021. "A novel methodology for optimal sizing photovoltaic-battery systems in smart homes considering grid outages and demand response," Renewable Energy, Elsevier, vol. 170(C), pages 884-896.
    6. Chen, Xiaoling & Miller, Cory & Goutham, Mithun & Hanumalagutti, Prasad Dev & Blaser, Rachel & Stockar, Stephanie, 2024. "Development and evaluation of an online home energy management strategy for load coordination in smart homes with renewable energy sources," Energy, Elsevier, vol. 290(C).
    7. Ferreira, Laura & Oliveira, Tiago & Neves, Catarina, 2023. "Consumer's intention to use and recommend smart home technologies: The role of environmental awareness," Energy, Elsevier, vol. 263(PC).
    8. Ryu, Do-Hyeon & Kim, Kwang-Jae, 2024. "The influence of information privacy concerns and perceived electricity usage habits on the usage intention of advanced metering infrastructure," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    9. Sovacool, Benjamin K. & Martiskainen, Mari & Furszyfer Del Rio, Dylan D., 2021. "Knowledge, energy sustainability, and vulnerability in the demographics of smart home technology diffusion," Energy Policy, Elsevier, vol. 153(C).
    10. Shakeri, Mohammad & Shayestegan, Mohsen & Reza, S.M. Salim & Yahya, Iskandar & Bais, Badariah & Akhtaruzzaman, Md & Sopian, Kamaruzzaman & Amin, Nowshad, 2018. "Implementation of a novel home energy management system (HEMS) architecture with solar photovoltaic system as supplementary source," Renewable Energy, Elsevier, vol. 125(C), pages 108-120.
    11. Balta-Ozkan, Nazmiye & Davidson, Rosemary & Bicket, Martha & Whitmarsh, Lorraine, 2013. "The development of smart homes market in the UK," Energy, Elsevier, vol. 60(C), pages 361-372.
    12. Ma, Jinjin & Yang, Lin & Wang, Donghan & Li, Yiming & Xie, Zuomiao & Lv, Haodong & Woo, Donghyup, 2024. "Digitalization in response to carbon neutrality: Mechanisms, effects and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    13. Han, Yawen & Du, Xin & Zhang, Hengming & Ni, Jinfeng & Fan, Fengyan, 2024. "Does smart home adoption reduce household electricity-related CO2 emissions? ——Evidence from Hangzhou city, China," Energy, Elsevier, vol. 289(C).
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