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Evaluation of a Peer-to-Peer Smart Grid Using Digital Twins: A Case Study of a Remote European Island

Author

Listed:
  • Niall Buckley

    (Integrated Environmental Solutions Ltd., Dublin 1, D01 A8N0 Dublin, Ireland)

  • Claudia Bo

    (Integrated Environmental Solutions Ltd., Dublin 1, D01 A8N0 Dublin, Ireland)

  • Faezeh Delkhah

    (Integrated Environmental Solutions Ltd., Dublin 1, D01 A8N0 Dublin, Ireland)

  • Niall Byrne

    (Integrated Environmental Solutions Ltd., Dublin 1, D01 A8N0 Dublin, Ireland)

  • Avril Ní Shearcaigh

    (Comharchumann Fuinnimh Oileáin Árainn Teoranta, H91 WN93 Aran Islands, Ireland)

  • Stephanie Brennan

    (Comharchumann Fuinnimh Oileáin Árainn Teoranta, H91 WN93 Aran Islands, Ireland)

  • Dayanne Peretti Correa

    (Department of Civil Engineering, University of Galway, H91 TK33 Galway, Ireland)

Abstract

Decarbonization of the built environment by electrifying energy systems and decarbonizing the electrical grid coupled with the digitization of these systems is a central strategy implemented by the European Commission (EC) to meet carbon reduction policies. The proliferation of technologies such as renewable energy sources (RES) and demand-side management (DSM) systems can be improved by using digital twins to predict and optimize their integration with existing systems. Digital twins in the built environment have been used for multiple purposes, such as predicting the performance of a system before its inception or optimizing its operation during use. To this end, a novel application of a combination of these technologies towards optimized DSM is peer-to-peer (P2P) energy trading, which can improve the local use of RES in the built environment. This paper investigates the potential of P2P energy trading in optimizing local RES of a remote island, Inishmore, Republic of Ireland, using a combination of data-driven and predictive digital twins towards the island’s journey to net zero. Data-driven digital twins are used to evaluate the current energy use at the pilot site. Predictive digital twins are applied to estimate the impact of applying P2P in the future and its influence on RES consumption at the pilot site. The findings show that in scenarios with limited RES coverage, P2P can significantly increase the local consumption of excess RES energy, reducing the risk of transmission or curtailment losses. However, P2P is limited in scenarios with widespread RES installation without storage or behavioral change to shift energy loads.

Suggested Citation

  • Niall Buckley & Claudia Bo & Faezeh Delkhah & Niall Byrne & Avril Ní Shearcaigh & Stephanie Brennan & Dayanne Peretti Correa, 2024. "Evaluation of a Peer-to-Peer Smart Grid Using Digital Twins: A Case Study of a Remote European Island," Energies, MDPI, vol. 17(22), pages 1-16, November.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:22:p:5541-:d:1515073
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    References listed on IDEAS

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    1. 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.
    2. Klyapovskiy, Sergey & You, Shi & Michiorri, Andrea & Kariniotakis, George & Bindner, Henrik W., 2019. "Incorporating flexibility options into distribution grid reinforcement planning: A techno-economic framework approach," Applied Energy, Elsevier, vol. 254(C).
    3. Johari, F. & Peronato, G. & Sadeghian, P. & Zhao, X. & Widén, J., 2020. "Urban building energy modeling: State of the art and future prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 128(C).
    4. Prataviera, Enrico & Zarrella, Angelo & Morejohn, Joshua & Narayanan, Vinod, 2024. "Exploiting district cooling network and urban building energy modeling for large-scale integrated energy conservation analyses," Applied Energy, Elsevier, vol. 356(C).
    5. Hossain, Eklas & Roy, Shidhartho & Mohammad, Naeem & Nawar, Nafiu & Dipta, Debopriya Roy, 2021. "Metrics and enhancement strategies for grid resilience and reliability during natural disasters," Applied Energy, Elsevier, vol. 290(C).
    6. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    7. João Abel Peças Lopes & André Guimarães Madureira & Manuel Matos & Ricardo Jorge Bessa & Vítor Monteiro & João Luiz Afonso & Sérgio F. Santos & João P. S. Catalão & Carlos Henggeler Antunes & Pedro Ma, 2020. "The future of power systems: Challenges, trends, and upcoming paradigms," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 9(3), May.
    8. Liu, Jia & Yang, Hongxing & Zhou, Yuekuan, 2021. "Peer-to-peer trading optimizations on net-zero energy communities with energy storage of hydrogen and battery vehicles," Applied Energy, Elsevier, vol. 302(C).
    9. Zhang, Chenghua & Wu, Jianzhong & Zhou, Yue & Cheng, Meng & Long, Chao, 2018. "Peer-to-Peer energy trading in a Microgrid," Applied Energy, Elsevier, vol. 220(C), pages 1-12.
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