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Assessment of Energy Customer Perception, Willingness, and Acceptance to Participate in Smart Grids—A Portuguese Survey

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  • Luis Gomes

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto, 4200-072 Porto, Portugal
    LASI—Intelligent Systems Associate Laboratory, 4800-058 Guimarães, Portugal)

  • António Coelho

    (Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
    INESC TEC—Institute for Systems and Computer Engineering, Technology and Science, 4200-465 Porto, Portugal)

  • Zita Vale

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto, 4200-072 Porto, Portugal
    LASI—Intelligent Systems Associate Laboratory, 4800-058 Guimarães, Portugal)

Abstract

The adoption of smart grids is becoming a common reality worldwide. This new reality is starting to impact energy customers as they face a dynamic grid in which they can actively participate. However, if energy customers are not prepared to participate actively, they can have their energy costs increased. This paper provides a review of acceptance models and customer surveys around the world made to assess the customers’ perception and willingness to participate in smart grids. Contributing to this assessment, this paper presents a survey undertaken in Portugal. The survey results demonstrate a willingness, from the customer’s end, to actively participate in smart grid initiatives. It was found that 92.9% of participants are willing to plan their energy usage to face hourly energy prices and that 95.0% of participants are willing to accept an external control of at least one appliance, enabling direct load control demand response programs. Also, the results identified two cognitive tendencies, negativity bias, and loss aversion, which can impact how customers participate in smart grids. These cognitive tendencies and the literature acceptance models demonstrate the importance of conducting social science studies targeting smart grids to fully achieve the efficient participation of end customers.

Suggested Citation

  • Luis Gomes & António Coelho & Zita Vale, 2022. "Assessment of Energy Customer Perception, Willingness, and Acceptance to Participate in Smart Grids—A Portuguese Survey," Energies, MDPI, vol. 16(1), pages 1-16, December.
  • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:270-:d:1015937
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    References listed on IDEAS

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    1. Yonghong Ma & Baixuan Li, 2020. "Hybridized Intelligent Home Renewable Energy Management System for Smart Grids," Sustainability, MDPI, vol. 12(5), pages 1-14, March.
    2. Alexa Spence & Christina Demski & Catherine Butler & Karen Parkhill & Nick Pidgeon, 2015. "Public perceptions of demand-side management and a smarter energy future," Nature Climate Change, Nature, vol. 5(6), pages 550-554, June.
    3. Amasyali, Kadir & El-Gohary, Nora M., 2021. "Real data-driven occupant-behavior optimization for reduced energy consumption and improved comfort," Applied Energy, Elsevier, vol. 302(C).
    4. Düştegör, Dilek & Sultana, Nahid & Felemban, Noor & Al Qahtani, Deemah, 2018. "A smarter electricity grid for the Eastern Province of Saudi Arabia: Perceptions and policy implications," Utilities Policy, Elsevier, vol. 50(C), pages 26-39.
    5. Janne Suhonen & Juha Jokisalo & Risto Kosonen & Ville Kauppi & Yuchen Ju & Philipp Janßen, 2020. "Demand Response Control of Space Heating in Three Different Building Types in Finland and Germany," Energies, MDPI, vol. 13(23), pages 1-35, November.
    6. Michael von Bonin & Elias Dörre & Hadi Al-Khzouz & Martin Braun & Xian Zhou, 2022. "Impact of Dynamic Electricity Tariff and Home PV System Incentives on Electric Vehicle Charging Behavior: Study on Potential Grid Implications and Economic Effects for Households," Energies, MDPI, vol. 15(3), pages 1-28, February.
    7. Yilmaz, Selin & Xu, Xiaojing & Cabrera, Daniel & Chanez, Cédric & Cuony, Peter & Patel, Martin K., 2020. "Analysis of demand-side response preferences regarding electricity tariffs and direct load control: Key findings from a Swiss survey," Energy, Elsevier, vol. 212(C).
    8. Tania Ouariachi & Chih-Yen Li & Wim J. L. Elving, 2020. "Gamification Approaches for Education and Engagement on Pro-Environmental Behaviors: Searching for Best Practices," Sustainability, MDPI, vol. 12(11), pages 1-14, June.
    9. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    10. Broman Toft, Madeleine & Schuitema, Geertje & Thøgersen, John, 2014. "Responsible technology acceptance: Model development and application to consumer acceptance of Smart Grid technology," Applied Energy, Elsevier, vol. 134(C), pages 392-400.
    11. Amit Shewale & Anil Mokhade & Nitesh Funde & Neeraj Dhanraj Bokde, 2020. "An Overview of Demand Response in Smart Grid and Optimization Techniques for Efficient Residential Appliance Scheduling Problem," Energies, MDPI, vol. 13(16), pages 1-31, August.
    12. Zhang, Yue-Jun & Peng, Hua-Rong & Su, Bin, 2017. "Energy rebound effect in China's Industry: An aggregate and disaggregate analysis," Energy Economics, Elsevier, vol. 61(C), pages 199-208.
    13. Colak, Ilhami & Sagiroglu, Seref & Fulli, Gianluca & Yesilbudak, Mehmet & Covrig, Catalin-Felix, 2016. "A survey on the critical issues in smart grid technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 396-405.
    14. Faria, P. & Vale, Z., 2011. "Demand response in electrical energy supply: An optimal real time pricing approach," Energy, Elsevier, vol. 36(8), pages 5374-5384.
    15. Ellabban, Omar & Abu-Rub, Haitham, 2016. "Smart grid customers' acceptance and engagement: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1285-1298.
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