IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i2p600-d1566779.html
   My bibliography  Save this article

Renewable Energy Community Sizing Based on Stochastic Optimization and Unsupervised Clustering

Author

Listed:
  • Luka Budin

    (University of Zagreb Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia)

  • Marko Delimar

    (University of Zagreb Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia)

Abstract

Renewable Energy Communities (RECs) are emerging as significant in the global paradigm shift towards a smart and sustainable energy environment. By empowering energy consumers to actively participate in local energy generation, and sharing, using renewable energy sources, energy storage, and flexible loads, REC participants can reduce costs, and also contribute to low-carbon objectives, providing the flexibility needed to address modern smart grid challenges. This article presents a mixed integer linear programming model for optimal sizing of the solar PVs and battery energy storage systems (BESS) of REC participants who engage in P2P energy exchange. The model is formulated using a two-stage stochastic optimization to address load and PV uncertainty, and unsupervised clustering to structure the data for the stochastic optimization process. The model enables sizing solar PVs for different rooftop geometries and the objective function includes comprehensively defined electricity, operational, and scaled investment costs for solar PV and BESS, where economic fairness constraints are analyzed and implemented. The model is validated on real solar and atmospheric measured data from Zagreb, Croatia, and publicly available household consumption data from Northern Germany. The article also analyzes how tariff models, and electricity prices affect PV and BESS sizes, cost reductions, and P2P energy exchange for different REC participants with varying consumption and production profiles.

Suggested Citation

  • Luka Budin & Marko Delimar, 2025. "Renewable Energy Community Sizing Based on Stochastic Optimization and Unsupervised Clustering," Sustainability, MDPI, vol. 17(2), pages 1-25, January.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:2:p:600-:d:1566779
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/2/600/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/2/600/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gjorgievski, Vladimir Z. & Velkovski, Bodan & Francesco Demetrio, Minuto & Cundeva, Snezana & Markovska, Natasa, 2023. "Energy sharing in European renewable energy communities: Impact of regulated charges," Energy, Elsevier, vol. 281(C).
    2. van der Stelt, Sander & AlSkaif, Tarek & van Sark, Wilfried, 2018. "Techno-economic analysis of household and community energy storage for residential prosumers with smart appliances," Applied Energy, Elsevier, vol. 209(C), pages 266-276.
    3. Norbu, Sonam & Couraud, Benoit & Robu, Valentin & Andoni, Merlinda & Flynn, David, 2021. "Modelling the redistribution of benefits from joint investments in community energy projects," Applied Energy, Elsevier, vol. 287(C).
    4. Cosic, Armin & Stadler, Michael & Mansoor, Muhammad & Zellinger, Michael, 2021. "Mixed-integer linear programming based optimization strategies for renewable energy communities," Energy, Elsevier, vol. 237(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ioanna-Mirto Chatzigeorgiou & Dimitrios Kitsikopoulos & Dimitrios A. Papadaskalopoulos & Alexandros-Georgios Chronis & Argyro Xenaki & Georgios T. Andreou, 2025. "Optimal PV Sizing and Demand Response in Greek Energy Communities Under the New Virtual Net-Billing Scheme," Energies, MDPI, vol. 18(19), pages 1-24, September.
    2. Shoaib Ahmed & Antonio D’Angola, 2025. "Energy Storage Systems: Scope, Technologies, Characteristics, Progress, Challenges, and Future Suggestions—Renewable Energy Community Perspectives," Energies, MDPI, vol. 18(11), pages 1-32, May.
    3. Andrzej Marciniak & Arkadiusz Małek, 2025. "Determining Energy Production and Consumption Signatures Using Unsupervised Clustering," Energies, MDPI, vol. 18(10), pages 1-29, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Emanuele Guerrazzi & Dimitri Thomopulos & Davide Fioriti & Ivan Mariuzzo & Eva Schito & Davide Poli & Marco Raugi, 2023. "Design of Energy Communities and Data-Sharing: Format and Open Data," Energies, MDPI, vol. 16(17), pages 1-26, August.
    2. Mariuzzo, Ivan & Fina, Bernadette & Stroemer, Stefan & Corinaldesi, Carlo & Raugi, Marco, 2025. "Grid-friendly optimization of energy communities through enhanced multiple participation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 208(C).
    3. 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.
    4. Sandra Corasaniti & Paolo Coppa & Dario Atzori & Ateeq Ur Rehman, 2025. "Renewable Energy Communities (RECs): European and Worldwide Distribution, Different Technologies, Management, and Modeling," Energies, MDPI, vol. 18(15), pages 1-60, July.
    5. 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.
    6. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    7. Félix González & Paul Arévalo & Luis Ramirez, 2025. "Game Theory and Robust Predictive Control for Peer-to-Peer Energy Management: A Pathway to a Low-Carbon Economy," Sustainability, MDPI, vol. 17(5), pages 1-23, February.
    8. Hafiz, Faeza & Rodrigo de Queiroz, Anderson & Fajri, Poria & Husain, Iqbal, 2019. "Energy management and optimal storage sizing for a shared community: A multi-stage stochastic programming approach," Applied Energy, Elsevier, vol. 236(C), pages 42-54.
    9. Luthander, Rasmus & Nilsson, Annica M. & Widén, Joakim & Åberg, Magnus, 2019. "Graphical analysis of photovoltaic generation and load matching in buildings: A novel way of studying self-consumption and self-sufficiency," Applied Energy, Elsevier, vol. 250(C), pages 748-759.
    10. Jiyoung Eum & Yongki Kim, 2020. "Analysis on Operation Modes of Residential BESS with Balcony-PV for Apartment Houses in Korea," Sustainability, MDPI, vol. 13(1), pages 1-9, December.
    11. Kang, Hyuna & Jung, Seunghoon & Kim, Hakpyeong & Jeoung, Jaewon & Hong, Taehoon, 2024. "Reinforcement learning-based optimal scheduling model of battery energy storage system at the building level," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
    12. Henni, Sarah & Staudt, Philipp & Weinhardt, Christof, 2021. "A sharing economy for residential communities with PV-coupled battery storage: Benefits, pricing and participant matching," Applied Energy, Elsevier, vol. 301(C).
    13. Fan, Feilong & Huang, Wentao & Tai, Nengling & Zheng, Xiaodong & Hu, Yan & Ma, Zhoujun, 2018. "A conditional depreciation balancing strategy for the equitable operation of extended hybrid energy storage systems," Applied Energy, Elsevier, vol. 228(C), pages 1937-1952.
    14. Prakhar Prakhar & Rachana Jaiswal & Shashank Gupta & Syed Zamberi Ahmad & Patrice Piccardi & Gabriele Santoro, 2025. "How can we improve entrepreneurial dynamics in electric vehicle manufacturing for a sustainable future: insights using a deep learning-based hybrid PLS-SEM-ANN approach," International Entrepreneurship and Management Journal, Springer, vol. 21(1), pages 1-45, December.
    15. Misconel, Steffi & Zöphel, Christoph & Möst, Dominik, 2021. "Assessing the value of demand response in a decarbonized energy system – A large-scale model application," Applied Energy, Elsevier, vol. 299(C).
    16. Semmelmann, Leo & Hertel, Matthias & Kircher, Kevin J. & Mikut, Ralf & Hagenmeyer, Veit & Weinhardt, Christof, 2024. "The impact of heat pumps on day-ahead energy community load forecasting," Applied Energy, Elsevier, vol. 368(C).
    17. Bruck, Axel & Díaz Ruano, Santiago & Auer, Hans, 2022. "One piece of the puzzle towards 100 Positive Energy Districts (PEDs) across Europe by 2025: An open-source approach to unveil favourable locations of PV-based PEDs from a techno-economic perspective," Energy, Elsevier, vol. 254(PA).
    18. Koskela, Juha & Rautiainen, Antti & Järventausta, Pertti, 2019. "Using electrical energy storage in residential buildings – Sizing of battery and photovoltaic panels based on electricity cost optimization," Applied Energy, Elsevier, vol. 239(C), pages 1175-1189.
    19. de Souza Dutra, Michael David & da Conceição Júnior, Gerson & de Paula Ferreira, William & Campos Chaves, Matheus Roberto, 2020. "A customized transition towards smart homes: A fast framework for economic analyses," Applied Energy, Elsevier, vol. 262(C).
    20. Couraud, Benoit & Andoni, Merlinda & Robu, Valentin & Norbu, Sonam & Chen, Si & Flynn, David, 2023. "Responsive FLEXibility: A smart local energy system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:2:p:600-:d:1566779. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.