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Impact of local energy markets integration in power systems layer: A comprehensive review

Author

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  • Dudjak, Viktorija
  • Neves, Diana
  • Alskaif, Tarek
  • Khadem, Shafi
  • Pena-Bello, Alejandro
  • Saggese, Pietro
  • Bowler, Benjamin
  • Andoni, Merlinda
  • Bertolini, Marina
  • Zhou, Yue
  • Lormeteau, Blanche
  • Mustafa, Mustafa A.
  • Wang, Yingjie
  • Francis, Christina
  • Zobiri, Fairouz
  • Parra, David
  • Papaemmanouil, Antonios

Abstract

In recent years extensive research has been conducted on the development of different models that enable energy trading between prosumers and consumers due to expected high integration of distributed energy resources. Some of the most researched mechanisms include Peer-to-Peer energy trading, Community Self-Consumption and Transactive Energy Models. To ensure the stable and reliable delivery of electricity as such markets and models grow, this paper aims to understand the impact of these models on grid infrastructure, including impacts on the control, operation, and planning of power systems, interaction between multiple market models and impact on transmission network. Here, we present a comprehensive review of existing research on impact of Local Energy Market integration in power systems layer. We detect and classify most common issues and benefits that the power grid can expect from integrating these models. We also present a detailed overview of methods that are used to integrate physical network constraints into the market mechanisms, their advantages, drawbacks, and scaling potential. In addition, we present different methods to calculate and allocate network tariffs and power losses. We find that financial energy transactions do not directly reflect the physical energy flows imposed by the constraints of the installed electrical infrastructure. In the end, we identify a number of different challenges and detect research gaps that need to be addressed in order to integrate Local Energy Market models into existing infrastructure.

Suggested Citation

  • Dudjak, Viktorija & Neves, Diana & Alskaif, Tarek & Khadem, Shafi & Pena-Bello, Alejandro & Saggese, Pietro & Bowler, Benjamin & Andoni, Merlinda & Bertolini, Marina & Zhou, Yue & Lormeteau, Blanche &, 2021. "Impact of local energy markets integration in power systems layer: A comprehensive review," Applied Energy, Elsevier, vol. 301(C).
  • Handle: RePEc:eee:appene:v:301:y:2021:i:c:s0306261921008266
    DOI: 10.1016/j.apenergy.2021.117434
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    Cited by:

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    4. Kristie Kaminski Küster & Daniel Gebbran & Alexandre Rasi Aoki & Germano Lambert-Torres & Daniel Navarro-Gevers & Patrício Rodolfo Impinisi & Cleverson Luiz da Silva Pinto, 2023. "Adoption of Local Peer-to-Peer Energy Markets: Technical and Economical Perspectives for Utilities," Energies, MDPI, vol. 16(5), pages 1-24, March.
    5. Dong, Jingya & Song, Chunhe & Liu, Shuo & Yin, Huanhuan & Zheng, Hao & Li, Yuanjian, 2022. "Decentralized peer-to-peer energy trading strategy in energy blockchain environment: A game-theoretic approach," Applied Energy, Elsevier, vol. 325(C).
    6. Schmitt, Carlo & Schumann, Klemens & Kollenda, Katharina & Blank, Andreas & Rebenaque, Olivier & Dronne, Théo & Martin, Arnault & Vassilopoulos, Philippe & Roques, Fabien & Moser, Albert, 2022. "How will local energy markets influence the pan-European day-ahead market and transmission systems? A case study for local markets in France and Germany," Applied Energy, Elsevier, vol. 325(C).
    7. Younes Zahraoui & Tarmo Korõtko & Argo Rosin & Hannes Agabus, 2023. "Market Mechanisms and Trading in Microgrid Local Electricity Markets: A Comprehensive Review," Energies, MDPI, vol. 16(5), pages 1-52, February.
    8. Ahmed, Faraedoon & Al Kez, Dlzar & McLoone, Seán & Best, Robert James & Cameron, Ché & Foley, Aoife, 2023. "Dynamic grid stability in low carbon power systems with minimum inertia," Renewable Energy, Elsevier, vol. 210(C), pages 486-506.
    9. Francesco Gulotta & Edoardo Daccò & Alessandro Bosisio & Davide Falabretti, 2023. "Opening of Ancillary Service Markets to Distributed Energy Resources: A Review," Energies, MDPI, vol. 16(6), pages 1-25, March.
    10. Wadim Strielkowski & Andrey Vlasov & Kirill Selivanov & Konstantin Muraviev & Vadim Shakhnov, 2023. "Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review," Energies, MDPI, vol. 16(10), pages 1-31, May.
    11. Yuly V. Garcia & Oscar Garzon & Carlos J. Delgado & Jan L. Diaz & Cesar A. Vega Penagos & Fabio Andrade & Adriana C. Luna & J. C. Hernandez, 2023. "Overview on Transactive Energy—Advantages and Challenges for Weak Power Grids," Energies, MDPI, vol. 16(12), pages 1-19, June.
    12. Schwidtal, J.M. & Piccini, P. & Troncia, M. & Chitchyan, R. & Montakhabi, M. & Francis, C. & Gorbatcheva, A. & Capper, T. & Mustafa, M.A. & Andoni, M. & Robu, V. & Bahloul, M. & Scott, I.J. & Mbavarir, 2023. "Emerging business models in local energy markets: A systematic review of peer-to-peer, community self-consumption, and transactive energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
    13. Ajla Mehinovic & Matej Zajc & Nermin Suljanovic, 2023. "Interpretation and Quantification of the Flexibility Sources Location on the Flexibility Service in the Distribution Grid," Energies, MDPI, vol. 16(2), pages 1-18, January.
    14. Capper, Timothy & Gorbatcheva, Anna & Mustafa, Mustafa A. & Bahloul, Mohamed & Schwidtal, Jan Marc & Chitchyan, Ruzanna & Andoni, Merlinda & Robu, Valentin & Montakhabi, Mehdi & Scott, Ian J. & Franci, 2022. "Peer-to-peer, community self-consumption, and transactive energy: A systematic literature review of local energy market models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).

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