IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v298y2021ics0306261921005432.html
   My bibliography  Save this article

Energy Storage as a Service: Optimal sizing for Transmission Congestion Relief

Author

Listed:
  • Arteaga, Juan
  • Zareipour, Hamidreza
  • Amjady, Nima

Abstract

In this paper, we propose a risk-based optimal sizing model for Storage as Transmission Alternative (SATA) intended for Transmission Congestion Relief (TCR) services. The storage system is sized from the perspective of the regulator/network operator with the ultimate goal of minimizing the cost of TCR to the ratepayers. The concept of Energy Storage as a Service (ESaaS) is considered when developing the models assuming that SATA’s idle capacity is rented out for a fee to third parties who would participate in energy and ancillary services markets. The fees collected through market participation services are assumed to be credited back to the ratepayers to offset the overall costs of removing network congestion. The presented simulation results provide insights into the financial benefits and risks associated with allowing SATA to share its excess capacity for additional revenues.

Suggested Citation

  • Arteaga, Juan & Zareipour, Hamidreza & Amjady, Nima, 2021. "Energy Storage as a Service: Optimal sizing for Transmission Congestion Relief," Applied Energy, Elsevier, vol. 298(C).
    • Handle: RePEc:eee:appene:v:298:y:2021:i:c:s0306261921005432
    DOI: 10.1016/j.apenergy.2021.117095
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921005432
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.117095?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. He, Xian & Delarue, Erik & D'haeseleer, William & Glachant, Jean-Michel, 2011. "A novel business model for aggregating the values of electricity storage," Energy Policy, Elsevier, vol. 39(3), pages 1575-1585, March.
    2. 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.
    3. Canizes, Bruno & Soares, João & Lezama, Fernando & Silva, Cátia & Vale, Zita & Corchado, Juan M., 2019. "Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation," Renewable Energy, Elsevier, vol. 138(C), pages 937-954.
    4. Brown, David P. & Sappington, David E.M., 2020. "Motivating the optimal procurement and deployment of electric storage as a transmission asset," Energy Policy, Elsevier, vol. 138(C).
    5. Sousa, Tiago & Soares, Tiago & Pinson, Pierre & Moret, Fabio & Baroche, Thomas & Sorin, Etienne, 2019. "Peer-to-peer and community-based markets: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 367-378.
    6. 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.
    7. Martin, Chris J., 2016. "The sharing economy: A pathway to sustainability or a nightmarish form of neoliberal capitalism?," Ecological Economics, Elsevier, vol. 121(C), pages 149-159.
    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. Li, Yanxue & Xie, Yun & Zhang, Xiaoyi & Xiao, Fu & Gao, Weijun, 2024. "Grid variability and value assessment of long-duration energy storage under rising photovoltaic penetration: Evidence from Japan," Energy, Elsevier, vol. 307(C).
    2. Kim, Yong Soon & Park, Gye Hyun & Kim, Seung Wan & Kim, Dam, 2024. "Incentive design for hybrid energy storage system investment to PV owners considering value of grid services," Applied Energy, Elsevier, vol. 373(C).
    3. Qiu, Rui & Zhang, Haoran & Wang, Guotao & Liang, Yongtu & Yan, Jinyue, 2023. "Green hydrogen-based energy storage service via power-to-gas technologies integrated with multi-energy microgrid," Applied Energy, Elsevier, vol. 350(C).
    4. Bartosz Uniejewski, 2023. "Smoothing Quantile Regression Averaging: A new approach to probabilistic forecasting of electricity prices," Papers 2302.00411, arXiv.org, revised Nov 2024.
    5. Li, Jiaxin & Xu, Zhanbo & Zhou, Yuzhou & Li, Yuting & Wu, Jiang & Guan, Xiaohong, 2024. "Optimal scheduling method and fast-solving algorithm for large-scale virtual power plants communication networks," Applied Energy, Elsevier, vol. 371(C).
    6. Emrani, Anisa & Berrada, Asmae & Bakhouya, Mohamed, 2022. "Optimal sizing and deployment of gravity energy storage system in hybrid PV-Wind power plant," Renewable Energy, Elsevier, vol. 183(C), pages 12-27.
    7. Smolenski, Robert & Szczesniak, Pawel & Drozdz, Wojciech & Kasperski, Lukasz, 2022. "Advanced metering infrastructure and energy storage for location and mitigation of power quality disturbances in the utility grid with high penetration of renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    8. Vykhodtsev, Anton V. & Jang, Darren & Wang, Qianpu & Rosehart, William & Zareipour, Hamidreza, 2022. "A review of modelling approaches to characterize lithium-ion battery energy storage systems in techno-economic analyses of power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(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. 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).
    4. 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.
    5. 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).
    6. Zakeri, Behnam & Gissey, Giorgio Castagneto & Dodds, Paul E. & Subkhankulova, Dina, 2021. "Centralized vs. distributed energy storage – Benefits for residential users," Energy, Elsevier, vol. 236(C).
    7. Ableitner, Liliane & Tiefenbeck, Verena & Meeuw, Arne & Wörner, Anselma & Fleisch, Elgar & Wortmann, Felix, 2020. "User behavior in a real-world peer-to-peer electricity market," Applied Energy, Elsevier, vol. 270(C).
    8. Gomez-Gonzalez, M. & Hernandez, J.C. & Vera, D. & Jurado, F., 2020. "Optimal sizing and power schedule in PV household-prosumers for improving PV self-consumption and providing frequency containment reserve," Energy, Elsevier, vol. 191(C).
    9. Zhang, Ziyu & Ding, Tao & Zhou, Quan & Sun, Yuge & Qu, Ming & Zeng, Ziyu & Ju, Yuntao & Li, Li & Wang, Kang & Chi, Fangde, 2021. "A review of technologies and applications on versatile energy storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    10. Hernández, J.C. & Sanchez-Sutil, F. & Muñoz-Rodríguez, F.J. & Baier, C.R., 2020. "Optimal sizing and management strategy for PV household-prosumers with self-consumption/sufficiency enhancement and provision of frequency containment reserve," Applied Energy, Elsevier, vol. 277(C).
    11. Küper, Inken & Edinger-Schons, Laura Marie, 2020. "Is sharing up for sale? Monetary exchanges in the sharing economy," Journal of Business Research, Elsevier, vol. 121(C), pages 223-234.
    12. Carattini, Stefano & Gillingham, Kenneth & Meng, Xiangyu & Yoeli, Erez, 2024. "Peer-to-peer solar and social rewards: Evidence from a field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 219(C), pages 340-370.
    13. Zhang, Chenxi & Yang, Yi & Wang, Yunqi & Qiu, Jing & Zhao, Junhua, 2024. "Auction-based peer-to-peer energy trading considering echelon utilization of retired electric vehicle second-life batteries," Applied Energy, Elsevier, vol. 358(C).
    14. Xiulan Jiang & Yukun Li & Jun Yang & Sen Wang & Chunjia Han, 2024. "Host–Guest Interaction and Sustainable Consumption Behaviour on Sharing-Accommodation Platforms: Using a Big Data Analytic Approach," Sustainability, MDPI, vol. 16(13), pages 1-22, June.
    15. Emmanuelle Reuter, 2022. "Hybrid business models in the sharing economy: The role of business model design for managing the environmental paradox," Business Strategy and the Environment, Wiley Blackwell, vol. 31(2), pages 603-618, February.
    16. Isabel Miralles & Domenico Dentoni & Stefano Pascucci, 2017. "Understanding the organization of sharing economy in agri-food systems: evidence from alternative food networks in Valencia," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 34(4), pages 833-854, December.
    17. Tom Brijs & Daniel Huppmann & Sauleh Siddiqui & Ronnie Belmans, 2016. "Auction-Based Allocation of Shared Electricity Storage Resources through Physical Storage Rights," Discussion Papers of DIW Berlin 1566, DIW Berlin, German Institute for Economic Research.
    18. Pies, Ingo & Hielscher, Stefan & Everding, Sebastian, 2020. "Do hybrids impede sustainability? How semantic reorientations and governance reforms can produce and preserve sustainability in sharing business models," Journal of Business Research, Elsevier, vol. 115(C), pages 174-185.
    19. Kirchhoff, Hannes & Strunz, Kai, 2019. "Key drivers for successful development of peer-to-peer microgrids for swarm electrification," Applied Energy, Elsevier, vol. 244(C), pages 46-62.
    20. Valeria Andreoni, 2020. "The Trap of Success: A Paradox of Scale for Sharing Economy and Degrowth," Sustainability, MDPI, vol. 12(8), pages 1-17, April.

    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:298:y:2021:i:c:s0306261921005432. 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.