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Evaluation of Energy-Production Preferences Using ANP Methodology Based on a Comprehensive Residential Survey

Author

Listed:
  • Veronika Groma

    (HUN-REN Centre for Energy Research, 1121 Budapest, Hungary)

  • Endre Börcsök

    (HUN-REN Centre for Energy Research, 1121 Budapest, Hungary)

  • Christian Oltra

    (Socio-Technical Research Centre, CIEMAT, 08007 Barcelona, Spain)

  • Chiara Bustreo

    (Consorzio RFX, 35127 Padova, Italy)

  • Adrián T. Terjék

    (HUN-REN Centre for Energy Research, 1121 Budapest, Hungary)

  • János Osán

    (HUN-REN Centre for Energy Research, 1121 Budapest, Hungary)

Abstract

Public opinion significantly influences discussions on the selection of technologies for future energy systems. Our goal was to support the development of energy scenarios by evaluating decision-making criteria and energy-production alternatives at a national level. The importance of the criteria and the determination of energy-production preferences were based on a social survey conducted in European countries. However, public opinions on specific technologies are frequently based on limited knowledge and can vary depending on the context. In our study, we analyzed the comparative data sets from an international survey on energy sources using three approaches: direct ranking, a comparison using various criteria, and classifying the knowledge of technologies. The evaluated results not only provide an excellent opportunity for the development of energy scenarios but also enable policymakers to develop more effective communication strategies to inform the public about technological choices and raise awareness of the need for modifications to the energy system.

Suggested Citation

  • Veronika Groma & Endre Börcsök & Christian Oltra & Chiara Bustreo & Adrián T. Terjék & János Osán, 2024. "Evaluation of Energy-Production Preferences Using ANP Methodology Based on a Comprehensive Residential Survey," Energies, MDPI, vol. 17(15), pages 1-15, July.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:15:p:3608-:d:1440734
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    References listed on IDEAS

    as
    1. Sen, Doruk & Tunç, K.M. Murat & Günay, M. Erdem, 2021. "Forecasting electricity consumption of OECD countries: A global machine learning modeling approach," Utilities Policy, Elsevier, vol. 70(C).
    2. Christina Demski & Wouter Poortinga & Lorraine Whitmarsh & Gisela Böhm & Stephen Fisher & Linda Steg & Resul Umit & Pekka Jokinen & Pasi Pohjolainen, 2018. "National context is a key determinant of energy security concerns across Europe," Nature Energy, Nature, vol. 3(10), pages 882-888, October.
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