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Designing aggregation criteria for end-users integration in energy communities: Energy and economic optimisation based on hybrid neural networks models

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  • Barone, G.
  • Buonomano, A.
  • Cipolla, G.
  • Forzano, C.
  • Giuzio, G.F.
  • Russo, G.

Abstract

This study presents innovative methodologies addressing critical challenges in energy community real-cases implementation. The investigation is conducted by exploring and enhancing the concept of Peer-to-Peer energy community, where prosumers interact with consumers by sharing surplus energy to meet their electricity demands. The end-users' connections are optimised by maximizing their energy interactions and the proposed pricing strategies are based on balancing the supply and demand curves for tailored unit costs.

Suggested Citation

  • Barone, G. & Buonomano, A. & Cipolla, G. & Forzano, C. & Giuzio, G.F. & Russo, G., 2024. "Designing aggregation criteria for end-users integration in energy communities: Energy and economic optimisation based on hybrid neural networks models," Applied Energy, Elsevier, vol. 371(C).
    • Handle: RePEc:eee:appene:v:371:y:2024:i:c:s0306261924009267
    DOI: 10.1016/j.apenergy.2024.123543
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