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Barriers to Peer-to-Peer Energy Trading Networks: A Multi-Dimensional PESTLE Analysis

Author

Listed:
  • Zheyuan Sun

    (Faculty of Engineering & IT, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Sara Tavakoli

    (Faculty of Engineering & IT, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Kaveh Khalilpour

    (Faculty of Engineering & IT, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Alexey Voinov

    (Faculty of Engineering Technology, University of Twente, 7500 AE Enschede, The Netherlands)

  • Jonathan Paul Marshall

    (Faculty of Art and Social Sciences, University of Technology Sydney, Sydney, NSW 2007, Australia)

Abstract

The growing adoption of distributed energy production technologies and the potential for energy underutilisation when the energy is produced by non-connected groups has raised interest in developing ‘sharing economy’ concepts in the electricity sector. We suggest that mechanisms, such as peer-to-peer (P2P) energy trading, will allow users to exchange their surplus energy for mutual benefits, stimulate the adoption of renewable energy, encourage communities to ‘democratically’ control their own energy supplies for local development, improve energy efficiency, and create many other benefits This approach is receiving increasing attention across the world, particularly in Germany, the Netherlands and Australia. Nevertheless, the actual development and implementation of these platforms are slow and mostly limited to trial activities. This study investigates the challenges and barriers facing P2P energy trading developments based on previous academic and industry studies. We provide a comprehensive multidimensional barrier analysis through a PESTLE approach to assess the barriers from a variety of perspectives, including the political (P), economic (E), social (S), technological (T), legal (L), and environmental (E) aspects. This approach clarifies the many intersecting problem fields for P2P trading in renewable energy, and the paper identifies a list of such barriers and discusses the prospects for addressing these issues. We also elaborate on the importance of incentive-based P2P market design.

Suggested Citation

  • Zheyuan Sun & Sara Tavakoli & Kaveh Khalilpour & Alexey Voinov & Jonathan Paul Marshall, 2024. "Barriers to Peer-to-Peer Energy Trading Networks: A Multi-Dimensional PESTLE Analysis," Sustainability, MDPI, vol. 16(4), pages 1-23, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:4:p:1517-:d:1337253
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    References listed on IDEAS

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    1. Han, Dong & Zhang, Chengzhenghao & Ping, Jian & Yan, Zheng, 2020. "Smart contract architecture for decentralized energy trading and management based on blockchains," Energy, Elsevier, vol. 199(C).
    2. Ableitner, Liliane & Tiefenbeck, Verena & Meeuw, Arne & Wörner, Anselma & Fleisch, Elgar & Wortmann, Felix, 2020. "User behavior in a real-world peer-to-peer electricity market," Applied Energy, Elsevier, vol. 270(C).
    3. Tushar, Wayes & Yuen, Chau & Saha, Tapan K. & Morstyn, Thomas & Chapman, Archie C. & Alam, M. Jan E. & Hanif, Sarmad & Poor, H. Vincent, 2021. "Peer-to-peer energy systems for connected communities: A review of recent advances and emerging challenges," Applied Energy, Elsevier, vol. 282(PA).
    4. Spiliopoulos, Nikolas & Sarantakos, Ilias & Nikkhah, Saman & Gkizas, George & Giaouris, Damian & Taylor, Phil & Rajarathnam, Uma & Wade, Neal, 2022. "Peer-to-peer energy trading for improving economic and resilient operation of microgrids," Renewable Energy, Elsevier, vol. 199(C), pages 517-535.
    5. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K., 2020. "Investigating the impact of P2P trading on power losses in grid-connected networks with prosumers," Applied Energy, Elsevier, vol. 263(C).
    6. Zhou, Yue & Wu, Jianzhong & Song, Guanyu & Long, Chao, 2020. "Framework design and optimal bidding strategy for ancillary service provision from a peer-to-peer energy trading community," Applied Energy, Elsevier, vol. 278(C).
    7. Albayati, Hayder & Kim, Suk Kyoung & Rho, Jae Jeung, 2020. "Accepting financial transactions using blockchain technology and cryptocurrency: A customer perspective approach," Technology in Society, Elsevier, vol. 62(C).
    8. Wu W, Wen & Quezada, George & Schleiger, Emma & Bratanova, Alexandra & Graham, Paul & Spak, B, 2019. "The future of peer-to-peer trading of distributed renewable energy," MPRA Paper 113821, University Library of Munich, Germany.
    9. Most Nahida Akter & Md Apel Mahmud & Amanullah Maung Than Oo, 2017. "A Hierarchical Transactive Energy Management System for Energy Sharing in Residential Microgrids," Energies, MDPI, vol. 10(12), pages 1-27, December.
    10. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2021. "Peer-to-peer energy trading: A review of the literature," Applied Energy, Elsevier, vol. 283(C).
    11. Atip Asvanund & Karen Clay & Ramayya Krishnan & Michael D. Smith, 2004. "An Empirical Analysis of Network Externalities in Peer-to-Peer Music-Sharing Networks," Information Systems Research, INFORMS, vol. 15(2), pages 155-174, June.
    12. Hani Muhsen & Adib Allahham & Ala’aldeen Al-Halhouli & Mohammed Al-Mahmodi & Asma Alkhraibat & Musab Hamdan, 2022. "Business Model of Peer-to-Peer Energy Trading: A Review of Literature," Sustainability, MDPI, vol. 14(3), pages 1-22, January.
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