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From Local Energy Communities towards National Energy System: A Grid-Aware Techno-Economic Analysis

Author

Listed:
  • Cédric Terrier

    (Department of Industrial Processes and Energy Systems Engineering, Institute of Mechanical Engineering, École Polytechnique Fédérale de Lausanne, Rue de l’Industrie 17, 1950 Sion, Switzerland)

  • Joseph René Hubert Loustau

    (Department of Industrial Processes and Energy Systems Engineering, Institute of Mechanical Engineering, École Polytechnique Fédérale de Lausanne, Rue de l’Industrie 17, 1950 Sion, Switzerland)

  • Dorsan Lepour

    (Department of Industrial Processes and Energy Systems Engineering, Institute of Mechanical Engineering, École Polytechnique Fédérale de Lausanne, Rue de l’Industrie 17, 1950 Sion, Switzerland)

  • François Maréchal

    (Department of Industrial Processes and Energy Systems Engineering, Institute of Mechanical Engineering, École Polytechnique Fédérale de Lausanne, Rue de l’Industrie 17, 1950 Sion, Switzerland)

Abstract

Energy communities are key actors in the energy transition since they optimally interconnect renewable energy capacities with the consumers. Despite versatile objectives, they usually aim at improving the self-consumption of renewable electricity within low-voltage grids to maximize revenues. In addition, energy communities are an excellent opportunity to supply renewable electricity to regional and national energy systems. However, effective price signals have to be designed to coordinate the needs of the energy infrastructure with the interests of these local stakeholders. The aim of this paper is to demonstrate the integration of energy communities at the national level with a bottom–up approach. District energy systems with a building scale resolution are modeled in a mixed-integer linear programming problem. The Dantzig–Wolfe decomposition is applied to reduce the computational time. The methodology lies within the framework of a renewable energy hub, characterized by a high share of photovoltaic capacities. Both investments into equipment and its operation are considered. The model is applied on a set of five typical districts and weather locations representative of the Swiss building stock. The extrapolation to the national scale reveals a heterogeneous photovoltaic potential throughout the country. Present electricity tariffs promote a maximal investment into photovoltaic panels in every region, reaching an installed capacity of 67.2 GW and generating 80 TWh per year. Placed in perspective with the optimal PV capacity forecast at 15.4 GW p e a k at the national level, coordinated investment between local and national actors is needed to prevent dispensable expenses. An uncoordinated design is expected to increase the total costs for residential energy systems from 12% to 83% and curtails 48% of local renewable electricity.

Suggested Citation

  • Cédric Terrier & Joseph René Hubert Loustau & Dorsan Lepour & François Maréchal, 2024. "From Local Energy Communities towards National Energy System: A Grid-Aware Techno-Economic Analysis," Energies, MDPI, vol. 17(4), pages 1-16, February.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:4:p:910-:d:1339401
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    References listed on IDEAS

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    1. Reynolds, Jonathan & Ahmad, Muhammad Waseem & Rezgui, Yacine & Hippolyte, Jean-Laurent, 2019. "Operational supply and demand optimisation of a multi-vector district energy system using artificial neural networks and a genetic algorithm," Applied Energy, Elsevier, vol. 235(C), pages 699-713.
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    Cited by:

    1. Chuat, Arthur & Terrier, Cédric & Schnidrig, Jonas & Maréchal, François, 2024. "Identification of typical district configurations: A two-step global sensitivity analysis framework," Energy, Elsevier, vol. 296(C).
    2. Lazzaretto, Andrea & Masi, Massimo & Rech, Sergio & Carraro, Gianluca & Danieli, Piero & Volpato, Gabriele & Dal Cin, Enrico, 2024. "From exergoeconomics to Thermo-X Optimization in the transition to sustainable energy systems," Energy, Elsevier, vol. 304(C).
    3. Dardor, Dareen & Flórez-Orrego, Daniel & Terrier, Cédric & Ribeiro Domingos, Meire Ellen & Platteau, Cyrille & da Silva, Joao Carlos & Lopez, Michel & Maréchal, François, 2024. "ROSMOSE: A web-based decision support tool for the design and optimization of industrial and urban energy systems," Energy, Elsevier, vol. 304(C).

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