IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v318y2022ics0306261922005323.html
   My bibliography  Save this article

Shared community energy storage allocation and optimization

Author

Listed:
  • Chang, Hsiu-Chuan
  • Ghaddar, Bissan
  • Nathwani, Jatin

Abstract

Distributed Energy Resources have been playing an increasingly important role in smart grids. Distributed Energy Resources consist primarily of energy generation and storage systems utilized by individual households or shared among them as a community. In contrast to individual energy storage, the field of community energy storage is now gaining more attention in various countries. However, existing models are either tailored towards optimizing the operations of individual energy storage or do not consider the notion of sharing energy storage within a community. This paper proposes a framework to allocate shared energy storage within a community and to then optimize the operational cost of electricity using a mixed integer linear programming formulation. The allocation options of energy storage include private energy storage and three options of community energy storage: random, diverse, and homogeneous allocation. With various load options of appliances, photovoltaic generation and energy storage set-ups, the operational cost of electricity for the households is minimized to provide the optimal operation scheduling. Computational results are presented on two real use cases in the cities of Ennis, Ireland and Waterloo, Canada, to show the advantage of using community energy storage as opposed to private energy storage and to evaluate the cost savings which can facilitate future deployment of community energy storage. In addition to the electricity operational cost, energy storage utilization and operation fairness are used to compare different allocation options of storage systems.

Suggested Citation

  • Chang, Hsiu-Chuan & Ghaddar, Bissan & Nathwani, Jatin, 2022. "Shared community energy storage allocation and optimization," Applied Energy, Elsevier, vol. 318(C).
    • Handle: RePEc:eee:appene:v:318:y:2022:i:c:s0306261922005323
    DOI: 10.1016/j.apenergy.2022.119160
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922005323
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.119160?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. 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.
    2. Owen Q. Wu & Derek D. Wang & Zhenwei Qin, 2012. "Seasonal Energy Storage Operations with Limited Flexibility: The Price-Adjusted Rolling Intrinsic Policy," Manufacturing & Service Operations Management, INFORMS, vol. 14(3), pages 455-471, July.
    3. 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.
    4. Weitzel, Timm & Glock, Christoph H., 2018. "Energy management for stationary electric energy storage systems: A systematic literature review," European Journal of Operational Research, Elsevier, vol. 264(2), pages 582-606.
    5. Sardi, Junainah & Mithulananthan, N. & Gallagher, M. & Hung, Duong Quoc, 2017. "Multiple community energy storage planning in distribution networks using a cost-benefit analysis," Applied Energy, Elsevier, vol. 190(C), pages 453-463.
    6. Parra, David & Gillott, Mark & Norman, Stuart A. & Walker, Gavin S., 2015. "Optimum community energy storage system for PV energy time-shift," Applied Energy, Elsevier, vol. 137(C), pages 576-587.
    7. Fthenakis, Vasilis & Mason, James E. & Zweibel, Ken, 2009. "The technical, geographical, and economic feasibility for solar energy to supply the energy needs of the US," Energy Policy, Elsevier, vol. 37(2), pages 387-399, February.
    8. Barbry, Adrien & Anjos, Miguel F. & Delage, Erick & Schell, Kristen R., 2019. "Robust self-scheduling of a price-maker energy storage facility in the New York electricity market," Energy Economics, Elsevier, vol. 78(C), pages 629-646.
    9. Warren B. Powell & Abraham George & Hugo Simão & Warren Scott & Alan Lamont & Jeffrey Stewart, 2012. "SMART: A Stochastic Multiscale Model for the Analysis of Energy Resources, Technology, and Policy," INFORMS Journal on Computing, INFORMS, vol. 24(4), pages 665-682, November.
    10. Koirala, Binod Prasad & van Oost, Ellen & van der Windt, Henny, 2018. "Community energy storage: A responsible innovation towards a sustainable energy system?," Applied Energy, Elsevier, vol. 231(C), pages 570-585.
    11. Omowunmi Mary Longe & Khmaies Ouahada & Suvendi Rimer & Ashot N. Harutyunyan & Hendrik C. Ferreira, 2017. "Distributed Demand Side Management with Battery Storage for Smart Home Energy Scheduling," Sustainability, MDPI, vol. 9(1), pages 1-13, January.
    12. de Souza Dutra, Michael David & Anjos, Miguel F. & Le Digabel, Sébastien, 2019. "A general framework for customized transition to smart homes," Energy, Elsevier, vol. 189(C).
    13. Anvari-Moghaddam, Amjad & Rahimi-Kian, Ashkan & Mirian, Maryam S. & Guerrero, Josep M., 2017. "A multi-agent based energy management solution for integrated buildings and microgrid system," Applied Energy, Elsevier, vol. 203(C), pages 41-56.
    14. Nan, Sibo & Zhou, Ming & Li, Gengyin, 2018. "Optimal residential community demand response scheduling in smart grid," Applied Energy, Elsevier, vol. 210(C), pages 1280-1289.
    15. Javadi, Mohammad Sadegh & Gough, Matthew & Lotfi, Mohamed & Esmaeel Nezhad, Ali & Santos, Sérgio F. & Catalão, João P.S., 2020. "Optimal self-scheduling of home energy management system in the presence of photovoltaic power generation and batteries," Energy, Elsevier, vol. 210(C).
    16. Pierre-Louis Poirion, 2016. "Robust linear programming; optimal sizing of an hybrid energy stand-alone system," 4OR, Springer, vol. 14(1), pages 103-104, March.
    17. Shanshan Hu & Gilvan C. Souza & Mark E. Ferguson & Wenbin Wang, 2015. "Capacity Investment in Renewable Energy Technology with Supply Intermittency: Data Granularity Matters!," Manufacturing & Service Operations Management, INFORMS, vol. 17(4), pages 480-494, October.
    18. 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.
    19. Sardi, Junainah & Mithulananthan, N. & Hung, Duong Quoc, 2017. "Strategic allocation of community energy storage in a residential system with rooftop PV units," Applied Energy, Elsevier, vol. 206(C), pages 159-171.
    20. Weitzel, Timm & Glock, C. H., 2018. "Energy Management for Stationary Electric Energy Storage Systems: A Systematic Literature Review," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 88880, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    21. Barbour, Edward & Parra, David & Awwad, Zeyad & González, Marta C., 2018. "Community energy storage: A smart choice for the smart grid?," Applied Energy, Elsevier, vol. 212(C), pages 489-497.
    22. Daniel Adelman & Canan Uçkun, 2019. "Dynamic Electricity Pricing to Smart Homes," Operations Research, INFORMS, vol. 67(6), pages 1520-1542, November.
    23. Billionnet, Alain & Costa, Marie-Christine & Poirion, Pierre-Louis, 2016. "Robust optimal sizing of a hybrid energy stand-alone system," European Journal of Operational Research, Elsevier, vol. 254(2), pages 565-575.
    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. Zhao, Bingxu & Duan, Pengfei & Fen, Mengdan & Xue, Qingwen & Hua, Jing & Yang, Zhuoqiang, 2023. "Optimal operation of distribution networks and multiple community energy prosumers based on mixed game theory," Energy, Elsevier, vol. 278(PB).
    2. Barone, G. & Buonomano, A. & Forzano, C. & Palombo, A. & Russo, G., 2023. "The role of energy communities in electricity grid balancing: A flexible tool for smart grid power distribution optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    3. Li, Qiang & Zhou, Yongcheng & Wei, Fanchao & Li, Shuangxiu & Wang, Zhonghao & Li, Jiajia & Zhou, Guowen & Liu, Jinfu & Yan, Peigang & Yu, Daren, 2024. "Multi-time scale scheduling for virtual power plants: Integrating the flexibility of power generation and multi-user loads while considering the capacity degradation of energy storage systems," Applied Energy, Elsevier, vol. 362(C).
    4. Cui, Shiting & Wu, Jun & Gao, Yao & Zhu, Ruijin, 2023. "A high altitude prosumer energy cooperation framework considering composite energy storage sharing and electric‑oxygen‑hydrogen flexible supply," Applied Energy, Elsevier, vol. 349(C).
    5. Cui, Shiting & Zhu, Ruijin & Wu, Jun, 2024. "A double layer energy cooperation framework for prosumer groups in high altitude areas," Renewable Energy, Elsevier, vol. 224(C).
    6. Jing Yu & Jicheng Liu & Jiakang Sun & Mengyu Shi, 2023. "Evolutionary Game of Digital-Driven Photovoltaic–Storage–Use Value Chain Collaboration: A Value Intelligence Creation Perspective," Sustainability, MDPI, vol. 15(4), pages 1-30, February.
    7. Wentao Huang & Qingqing Zheng & Ying Hu & Yalan Huang & Shasha Zhou, 2024. "Optimization of Frequency Modulation Energy Storage Configuration in Power Grid Based on Equivalent Full Cycle Model," Energies, MDPI, vol. 17(9), pages 1-15, April.
    8. Jing Yu & Jicheng Liu & Yajing Wen & Xue Yu, 2023. "Economic Optimal Coordinated Dispatch of Power for Community Users Considering Shared Energy Storage and Demand Response under Blockchain," Sustainability, MDPI, vol. 15(8), pages 1-26, April.
    9. Weiqiang Qiu & Sheng Zhou & Yang Yang & Xiaoying Lv & Ting Lv & Yuge Chen & Ying Huang & Kunming Zhang & Hongfei Yu & Yunchu Wang & Yuanqian Ma & Zhenzhi Lin, 2023. "Application Prospect, Development Status and Key Technologies of Shared Energy Storage toward Renewable Energy Accommodation Scenario in the Context of China," Energies, MDPI, vol. 16(2), pages 1-21, January.
    10. Jiahao Chen & Bing Sun & Yuan Zeng & Ruipeng Jing & Shimeng Dong & Jingran Wang, 2023. "An Optimal Scheduling Method of Shared Energy Storage System Considering Distribution Network Operation Risk," Energies, MDPI, vol. 16(5), pages 1-24, March.
    11. He, Ye & Wu, Hongbin & Wu, Andrew Y. & Li, Peng & Ding, Ming, 2024. "Optimized shared energy storage in a peer-to-peer energy trading market: Two-stage strategic model regards bargaining and evolutionary game theory," Renewable Energy, Elsevier, vol. 224(C).
    12. Li, Canbing & Chen, Dawei & Liu, Xubin & Shahidehpour, Mohammad & Yang, Hanyu & Liu, Hui & Huang, Wentao & Wang, Jianxiao & Deng, Xiang & Zhang, Qiying, 2024. "Fault mitigation mechanism to pave the way to accommodate over 90% renewable energy in electric power systems," Applied Energy, Elsevier, vol. 359(C).
    13. Kerscher, Selina & Koirala, Arpan & Arboleya, Pablo, 2024. "Grid-optimal energy community planning from a systems perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).

    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. 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).
    2. 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.
    3. Christian van Someren & Martien Visser & Han Slootweg, 2023. "Sizing Batteries for Power Flow Management in Distribution Grids: A Method to Compare Battery Capacities for Different Siting Configurations and Variable Power Flow Simultaneity," Energies, MDPI, vol. 16(22), pages 1-19, November.
    4. Zhang, Yijie & Ma, Tao & Yang, Hongxing, 2022. "Grid-connected photovoltaic battery systems: A comprehensive review and perspectives," Applied Energy, Elsevier, vol. 328(C).
    5. Walker, Awnalisa & Kwon, Soongeol, 2021. "Design of structured control policy for shared energy storage in residential community: A stochastic optimization approach," Applied Energy, Elsevier, vol. 298(C).
    6. Walker, Awnalisa & Kwon, Soongeol, 2021. "Analysis on impact of shared energy storage in residential community: Individual versus shared energy storage," Applied Energy, Elsevier, vol. 282(PA).
    7. 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.
    8. Das, Choton K. & Bass, Octavian & Kothapalli, Ganesh & Mahmoud, Thair S. & Habibi, Daryoush, 2018. "Optimal placement of distributed energy storage systems in distribution networks using artificial bee colony algorithm," Applied Energy, Elsevier, vol. 232(C), pages 212-228.
    9. Sturmberg, B.C.P. & Shaw, M.E. & Mediwaththe, C.P. & Ransan-Cooper, H. & Weise, B. & Thomas, M. & Blackhall, L., 2021. "A mutually beneficial approach to electricity network pricing in the presence of large amounts of solar power and community-scale energy storage," Energy Policy, Elsevier, vol. 159(C).
    10. Adefarati, T. & Bansal, R.C., 2019. "Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources," Applied Energy, Elsevier, vol. 236(C), pages 1089-1114.
    11. 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.
    12. Koirala, Binod Prasad & van Oost, Ellen & van der Windt, Henny, 2018. "Community energy storage: A responsible innovation towards a sustainable energy system?," Applied Energy, Elsevier, vol. 231(C), pages 570-585.
    13. Nazari, AmirAli & Keypour, Reza & Amjady, Nima, 2021. "Joint investment of community energy storage systems in distribution networks using modified Nash bargaining theory," Applied Energy, Elsevier, vol. 301(C).
    14. Golpîra, Hêriş & Khan, Syed Abdul Rehman, 2019. "A multi-objective risk-based robust optimization approach to energy management in smart residential buildings under combined demand and supply uncertainty," Energy, Elsevier, vol. 170(C), pages 1113-1129.
    15. Cai, Qiran & Xu, Qingyang & Qing, Jing & Shi, Gang & Liang, Qiao-Mei, 2022. "Promoting wind and photovoltaics renewable energy integration through demand response: Dynamic pricing mechanism design and economic analysis for smart residential communities," Energy, Elsevier, vol. 261(PB).
    16. Obara, Shin'ya & Hamanaka, Ryo & El-Sayed, Abeer Galal, 2019. "Design methods for microgrids to address seasonal energy availability – A case study of proposed Showa Antarctic Station retrofits," Applied Energy, Elsevier, vol. 236(C), pages 711-727.
    17. Gährs, Swantje & Knoefel, Jan, 2020. "Stakeholder demands and regulatory framework for community energy storage with a focus on Germany," Energy Policy, Elsevier, vol. 144(C).
    18. Rodrigues, Stefane Dias & Garcia, Vinicius Jacques, 2023. "Transactive energy in microgrid communities: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    19. Gerlach, Lisa & Bocklisch, Thilo & Verweij, Marco, 2023. "Selfish batteries vs. benevolent optimizers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 177(C).
    20. Tushar, Wayes & Yuen, Chau & Saha, Tapan K. & Morstyn, Thomas & Chapman, Archie C. & Alam, M. Jan E. & Hanif, Sarmad & Poor, H. Vincent, 2021. "Peer-to-peer energy systems for connected communities: A review of recent advances and emerging challenges," Applied Energy, Elsevier, vol. 282(PA).

    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:appene:v:318:y:2022:i:c:s0306261922005323. 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/405891/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.