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Automated energy sharing in MV and LV distribution grids within an energy community: A case for Croatian city of Križevci with a hybrid renewable system

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  • Herenčić, Lin
  • Kirac, Mislav
  • Keko, Hrvoje
  • Kuzle, Igor
  • Rajšl, Ivan

Abstract

Local energy sharing (LES) is a concept that enables sharing between distribution system participants such as consumers, producers, and prosumers at the local level in a transparent and cooperative manner. It can improve local supply-demand balancing, reduce voltage deviations, and improve social welfare. However, the feasibility of such an approach is highly dependent on the regulatory framework and implementation requires investment in an adequate information and communication infrastructure. This paper examines components for the implementation of LES within energy communities in the EU, with a focus on price-forming methods that can be integrated into a net-billing system and adopted for different regulatory set-ups. Further, a method for the assessment of impacts on market participants is provided. The approach is applied for the assessment of the opportunities for LES in the city of Križevci, considering local generation, flexibility options, and real-life regulatory requirements. It is shown that LES under appropriate regulatory provisions can be an effective market-based mechanism for stimulating local generation and flexibility activation, and that way support decarbonization and local self-sufficiency. All members can benefit from participating in the energy community, but the distribution of the benefits notably depends on the applied LES price-forming method. On the other hand, subject to regulatory setup, the trade-offs are reflected on reduced revenues for market participants that generate income based on transmission fees, taxes, and/or surcharges.

Suggested Citation

  • Herenčić, Lin & Kirac, Mislav & Keko, Hrvoje & Kuzle, Igor & Rajšl, Ivan, 2022. "Automated energy sharing in MV and LV distribution grids within an energy community: A case for Croatian city of Križevci with a hybrid renewable system," Renewable Energy, Elsevier, vol. 191(C), pages 176-194.
  • Handle: RePEc:eee:renene:v:191:y:2022:i:c:p:176-194
    DOI: 10.1016/j.renene.2022.04.044
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    2. Barbara Antonioli Mantegazzini & C?dric Clastres & Laura Wangen, 2022. "Energy communities in Europe: An overview of issues and regulatory and economic solutions," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2022(2), pages 5-23.
    3. Shoaib Ahmed & Amjad Ali & Alessandro Ciocia & Antonio D’Angola, 2024. "Technological Elements behind the Renewable Energy Community: Current Status, Existing Gap, Necessity, and Future Perspective—Overview," Energies, MDPI, vol. 17(13), pages 1-40, June.
    4. Ronelly De Souza & Emanuele Nadalon & Melchiorre Casisi & Mauro Reini, 2022. "Optimal Sharing Electricity and Thermal Energy Integration for an Energy Community in the Perspective of 100% RES Scenario," Sustainability, MDPI, vol. 14(16), pages 1-39, August.
    5. Shoaib Ahmed & Amjad Ali & Antonio D’Angola, 2024. "A Review of Renewable Energy Communities: Concepts, Scope, Progress, Challenges, and Recommendations," Sustainability, MDPI, vol. 16(5), pages 1-34, February.
    6. Alexander Micallef & Cyril Spiteri Staines & John Licari, 2022. "Renewable Energy Communities in Islands: A Maltese Case Study," Energies, MDPI, vol. 15(24), pages 1-21, December.
    7. Heilmann, Jakob & Wensaas, Marthe & Crespo del Granado, Pedro & Hashemipour, Naser, 2022. "Trading algorithms to represent the wholesale market of energy communities in Norway and England," Renewable Energy, Elsevier, vol. 200(C), pages 1426-1437.
    8. Negri, Simone & Giani, Federico & Blasuttigh, Nicola & Massi Pavan, Alessandro & Mellit, Adel & Tironi, Enrico, 2022. "Combined model predictive control and ANN-based forecasters for jointly acting renewable self-consumers: An environmental and economical evaluation," Renewable Energy, Elsevier, vol. 198(C), pages 440-454.
    9. Simoiu, Mircea Stefan & Fagarasan, Ioana & Ploix, Stéphane & Calofir, Vasile, 2022. "Modeling the energy community members’ willingness to change their behaviour with multi-agent systems: A stochastic approach," Renewable Energy, Elsevier, vol. 194(C), pages 1233-1246.

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