IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v185y2023ics1364032123005129.html
   My bibliography  Save this article

Multi-objective sizing and real-time scheduling of battery energy storage in energy-sharing community based on reinforcement learning

Author

Listed:
  • Kang, Hyuna
  • Jung, Seunghoon
  • Kim, Hakpyeong
  • Hong, Juwon
  • Jeoung, Jaewon
  • Hong, Taehoon

Abstract

Reducing peak demand and enhancing self-sufficiency have made the battery energy storage system (BESS) essential in microgrids when combined with photovoltaic (PV) systems. Previous studies have shown that BESS usage remains expensive, and it is more practical to share it within a community rather than installing individual systems. Therefore, this study aimed to propose a framework for BESS sizing and scheduling in an energy-sharing community based on reinforcement learning. To validate the proposed framework, a case study was conducted based on the BESS ownership scenarios (i.e., individual-owned BESS (IOB) and community-shared BESS (CSB)) considering the following purposes of potential stakeholders: (i) enhancing SSR; (ii) reducing peak demand; and (iii) increasing economic profit. The maximum SSR of CSB was 12.4% higher than IOB, while the peak load of CSB was 0.07% lower than IOB. As the BESS size increased, the total cost of BESS increased, and the total profits on electricity decreased. The economic profit increased by about 38% when CSB was used compared to IOBs. The proposed framework offers more promise for a broader range of building loads and PV generation within the energy-sharing community. Ultimately, this study would allow prosumers, community practitioners, and policymakers to better understand the sharing mechanisms in the community and provide decision guidelines for ownership types, operational strategies, and sizing of BESS and PV systems.

Suggested Citation

  • Kang, Hyuna & Jung, Seunghoon & Kim, Hakpyeong & Hong, Juwon & Jeoung, Jaewon & Hong, Taehoon, 2023. "Multi-objective sizing and real-time scheduling of battery energy storage in energy-sharing community based on reinforcement learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    • Handle: RePEc:eee:rensus:v:185:y:2023:i:c:s1364032123005129
    DOI: 10.1016/j.rser.2023.113655
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032123005129
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2023.113655?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lombardi, P. & Schwabe, F., 2017. "Sharing economy as a new business model for energy storage systems," Applied Energy, Elsevier, vol. 188(C), pages 485-496.
    2. Kang, Hyuna & Jung, Seunghoon & Lee, Minhyun & Hong, Taehoon, 2022. "How to better share energy towards a carbon-neutral city? A review on application strategies of battery energy storage system in city," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    3. Wu, Xiaohua & Hu, Xiaosong & Yin, Xiaofeng & Zhang, Caiping & Qian, Shide, 2017. "Optimal battery sizing of smart home via convex programming," Energy, Elsevier, vol. 140(P1), pages 444-453.
    4. Umar, Muhammad & Riaz, Yasir & Yousaf, Imran, 2022. "Impact of Russian-Ukraine war on clean energy, conventional energy, and metal markets: Evidence from event study approach," Resources Policy, Elsevier, vol. 79(C).
    5. Zhang, Yijie & Ma, Tao & Elia Campana, Pietro & Yamaguchi, Yohei & Dai, Yanjun, 2020. "A techno-economic sizing method for grid-connected household photovoltaic battery systems," Applied Energy, Elsevier, vol. 269(C).
    6. Ren, Hongbo & Wu, Qiong & Li, Qifen & Yang, Yongwen, 2020. "Optimal design and management of distributed energy network considering both efficiency and fairness," Energy, Elsevier, vol. 213(C).
    7. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2018. "Battery energy storage system size determination in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 109-125.
    8. 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).
    9. Long, Chao & Wu, Jianzhong & Zhou, Yue & Jenkins, Nick, 2018. "Peer-to-peer energy sharing through a two-stage aggregated battery control in a community Microgrid," Applied Energy, Elsevier, vol. 226(C), pages 261-276.
    10. Lorenzi, Guido & Silva, Carlos Augusto Santos, 2016. "Comparing demand response and battery storage to optimize self-consumption in PV systems," Applied Energy, Elsevier, vol. 180(C), pages 524-535.
    11. Huang, Pei & Sun, Yongjun & Lovati, Marco & Zhang, Xingxing, 2021. "Solar-photovoltaic-power-sharing-based design optimization of distributed energy storage systems for performance improvements," Energy, Elsevier, vol. 222(C).
    12. Sharma, Vanika & Haque, Mohammed H. & Aziz, Syed Mahfuzul, 2019. "Energy cost minimization for net zero energy homes through optimal sizing of battery storage system," Renewable Energy, Elsevier, vol. 141(C), pages 278-286.
    13. Müller, Simon C. & Welpe, Isabell M., 2018. "Sharing electricity storage at the community level: An empirical analysis of potential business models and barriers," Energy Policy, Elsevier, vol. 118(C), pages 492-503.
    14. Li, Jiaming, 2019. "Optimal sizing of grid-connected photovoltaic battery systems for residential houses in Australia," Renewable Energy, Elsevier, vol. 136(C), pages 1245-1254.
    15. Roberts, Mike B. & Bruce, Anna & MacGill, Iain, 2019. "Impact of shared battery energy storage systems on photovoltaic self-consumption and electricity bills in apartment buildings," Applied Energy, Elsevier, vol. 245(C), pages 78-95.
    16. Jung, Seunghoon & Jeoung, Jaewon & Kang, Hyuna & Hong, Taehoon, 2021. "Optimal planning of a rooftop PV system using GIS-based reinforcement learning," Applied Energy, Elsevier, vol. 298(C).
    17. Chatzivasileiadi, Aikaterini & Ampatzi, Eleni & Knight, Ian, 2013. "Characteristics of electrical energy storage technologies and their applications in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 814-830.
    18. Marike Schiffer, 2022. "A war running on fossil fuels," Nature Human Behaviour, Nature, vol. 6(6), pages 771-773, June.
    19. Ibrahim, Nur Atirah & Wan Alwi, Sharifah Rafidah & Manan, Zainuddin Abdul & Mustaffa, Azizul Azri & Kidam, Kamarizan, 2022. "Risk matrix approach of extreme temperature and precipitation for renewable energy systems in Malaysia," Energy, Elsevier, vol. 254(PC).
    20. Cremi, Maurizio R. & Pantaleo, Antonio Marco & van Dam, Koen H. & Shah, Nilay, 2020. "Optimal design and operation of an urban energy system applied to the Fiera Del Levante exhibition centre," Applied Energy, Elsevier, vol. 275(C).
    21. Lüth, Alexandra & Zepter, Jan Martin & Crespo del Granado, Pedro & Egging, Ruud, 2018. "Local electricity market designs for peer-to-peer trading: The role of battery flexibility," Applied Energy, Elsevier, vol. 229(C), pages 1233-1243.
    22. Koirala, Binod Prasad & Koliou, Elta & Friege, Jonas & Hakvoort, Rudi A. & Herder, Paulien M., 2016. "Energetic communities for community energy: A review of key issues and trends shaping integrated community energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 722-744.
    Full references (including those not matched with items on IDEAS)

    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. Àlex Alonso & Jordi de la Hoz & Helena Martín & Sergio Coronas & José Matas, 2021. "Individual vs. Community: Economic Assessment of Energy Management Systems under Different Regulatory Frameworks," Energies, MDPI, vol. 14(3), pages 1-27, January.
    2. Kang, Hyuna & Jung, Seunghoon & Lee, Minhyun & Hong, Taehoon, 2022. "How to better share energy towards a carbon-neutral city? A review on application strategies of battery energy storage system in city," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    3. Mulleriyawage, U.G.K. & Shen, W.X., 2021. "Impact of demand side management on optimal sizing of residential battery energy storage system," Renewable Energy, Elsevier, vol. 172(C), pages 1250-1266.
    4. Andreolli, Francesca & D'Alpaos, Chiara & Kort, Peter, 2023. "Does P2P Trading Favor Investments in PV-Battery Systems?," FEEM Working Papers 330498, Fondazione Eni Enrico Mattei (FEEM).
    5. 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).
    6. Zhang, Wen-Yi & Chen, Yue & Wang, Yi & Xu, Yunjian, 2023. "Equilibrium analysis of a peer-to-peer energy trading market with shared energy storage in a power transmission grid," Energy, Elsevier, vol. 274(C).
    7. Schwidtal, J.M. & Piccini, P. & Troncia, M. & Chitchyan, R. & Montakhabi, M. & Francis, C. & Gorbatcheva, A. & Capper, T. & Mustafa, M.A. & Andoni, M. & Robu, V. & Bahloul, M. & Scott, I.J. & Mbavarir, 2023. "Emerging business models in local energy markets: A systematic review of peer-to-peer, community self-consumption, and transactive energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
    8. Francesca Andreolli & Chiara D'Alpaos & Peter Kort, 2023. "Does P2P Trading Favor Investments in PV-Battery Systems?," Working Papers 2023.02, Fondazione Eni Enrico Mattei.
    9. Moiz Masood Syed & Gregory M. Morrison & James Darbyshire, 2020. "Shared Solar and Battery Storage Configuration Effectiveness for Reducing the Grid Reliance of Apartment Complexes," Energies, MDPI, vol. 13(18), pages 1-23, September.
    10. Scheller, Fabian & Burkhardt, Robert & Schwarzeit, Robert & McKenna, Russell & Bruckner, Thomas, 2020. "Competition between simultaneous demand-side flexibility options: the case of community electricity storage systems," Applied Energy, Elsevier, vol. 269(C).
    11. Zheng, Boshen & Wei, Wei & Chen, Yue & Wu, Qiuwei & Mei, Shengwei, 2022. "A peer-to-peer energy trading market embedded with residential shared energy storage units," Applied Energy, Elsevier, vol. 308(C).
    12. Keck, Felix & Lenzen, Manfred, 2021. "Drivers and benefits of shared demand-side battery storage – an Australian case study," Energy Policy, Elsevier, vol. 149(C).
    13. Zheng, Siqian & Huang, Gongsheng & Lai, Alvin CK., 2021. "Techno-economic performance analysis of synergistic energy sharing strategies for grid-connected prosumers with distributed battery storages," Renewable Energy, Elsevier, vol. 178(C), pages 1261-1278.
    14. Pepa Ambrosio-Albalá & Catherine S. E. Bale & Andrew J. Pimm & Peter G. Taylor, 2020. "What Makes Decentralised Energy Storage Schemes Successful? An Assessment Incorporating Stakeholder Perspectives," Energies, MDPI, vol. 13(24), pages 1-22, December.
    15. Song, Xiaoling & Zhang, Huqing & Fan, Lurong & Zhang, Zhe & Peña-Mora, Feniosky, 2023. "Planning shared energy storage systems for the spatio-temporal coordination of multi-site renewable energy sources on the power generation side," Energy, Elsevier, vol. 282(C).
    16. Fabian Scheller & Robert Burkhardt & Robert Schwarzeit & Russell McKenna & Thomas Bruckner, 2020. "Competition between simultaneous demand-side flexibility options: The case of community electricity storage systems," Papers 2011.05809, arXiv.org.
    17. Mulleriyawage, U.G.K. & Shen, W.X., 2020. "Optimally sizing of battery energy storage capacity by operational optimization of residential PV-Battery systems: An Australian household case study," Renewable Energy, Elsevier, vol. 160(C), pages 852-864.
    18. Woon, Kok Sin & Phuang, Zhen Xin & Taler, Jan & Varbanov, Petar Sabev & Chong, Cheng Tung & Klemeš, Jiří Jaromír & Lee, Chew Tin, 2023. "Recent advances in urban green energy development towards carbon emissions neutrality," Energy, Elsevier, vol. 267(C).
    19. Zhou, Yuekuan & Lund, Peter D., 2023. "Peer-to-peer energy sharing and trading of renewable energy in smart communities ─ trading pricing models, decision-making and agent-based collaboration," Renewable Energy, Elsevier, vol. 207(C), pages 177-193.
    20. Avilés A., Camilo & Oliva H., Sebastian & Watts, David, 2019. "Single-dwelling and community renewable microgrids: Optimal sizing and energy management for new business models," Applied Energy, Elsevier, vol. 254(C).

    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:eee:rensus:v:185:y:2023:i:c:s1364032123005129. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.