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Impact of Non-Residential Users on the Energy Performance of Renewable Energy Communities Considering Clusterization of Consumptions

Author

Listed:
  • Elisa Veronese

    (Institute for Renewable Energy, Eurac Research, Viale Druso 1, 39100 Bolzano, Italy)

  • Luca Lauton

    (Institute for Renewable Energy, Eurac Research, Viale Druso 1, 39100 Bolzano, Italy
    Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123 Trento, Italy)

  • Grazia Barchi

    (Institute for Renewable Energy, Eurac Research, Viale Druso 1, 39100 Bolzano, Italy)

  • Alessandro Prada

    (Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123 Trento, Italy)

  • Vincenzo Trovato

    (Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123 Trento, Italy
    Department of Electric and Electronic Engineering, Imperial College London, Exhibition Rd., South Kensington, London SW7 2AZ, UK)

Abstract

Renewable energy communities foster the users’ engagement in the energy transition, paving the way to the integration of distributed renewable energy sources. So far, the scientific literature has focused on residential users in energy communities, thus overlooking the opportunities for industrial and commercial members. This paper seeks to bridge this gap by extending the analysis to the role of non-residential users. The proposed methodology develops an effective clustering approach targeted to actual non-residential consumption profiles. It is based on the k-means algorithm and statistical characterization based on relevant probability density function curves. The employed clusterization procedure allows for effectively reducing a sample of 49 real industrial load profiles up to 11 typical consumption curves, whilst capturing all the relevant characteristics of the initial population. Furthermore, a peer-to-peer sharing strategy is developed accounting for distributed and shared storage. Three scenarios are considered to validate the model with different shares of non-residential users, and the results are then evaluated by means of shared energy, self-consumption, and self-sufficiency indices. Moreover, the results show that the integration of a large non-residential prosumer in a REC may increase the self-sufficiency of residential members by 8.2%, self-consumption by 4.4%, and the overall shared energy by 37.3%. Therefore, the residential community consistently benefits from the presence of non-residential users, with larger users inducing more pronounced effects.

Suggested Citation

  • Elisa Veronese & Luca Lauton & Grazia Barchi & Alessandro Prada & Vincenzo Trovato, 2024. "Impact of Non-Residential Users on the Energy Performance of Renewable Energy Communities Considering Clusterization of Consumptions," Energies, MDPI, vol. 17(16), pages 1-18, August.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:16:p:3984-:d:1454475
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    References listed on IDEAS

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    1. Rodrigues, Daniel L. & Ye, Xianming & Xia, Xiaohua & Zhu, Bing, 2020. "Battery energy storage sizing optimisation for different ownership structures in a peer-to-peer energy sharing community," Applied Energy, Elsevier, vol. 262(C).
    2. Margherita Povolato & Alessandro Prada & Sara Verones & Silvia Debiasi & Paolo Baggio, 2023. "The Impact of Energy Community Composition on Its Technical and Economic Performance," Energies, MDPI, vol. 16(14), pages 1-15, July.
    3. Secchi, Mattia & Barchi, Grazia & Macii, David & Moser, David & Petri, Dario, 2021. "Multi-objective battery sizing optimisation for renewable energy communities with distribution-level constraints: A prosumer-driven perspective," Applied Energy, Elsevier, vol. 297(C).
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