IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v242y2022ics0360544221032114.html
   My bibliography  Save this article

MV-LV network-secure bidding optimisation of an aggregator of prosumers in real-time energy and reserve markets

Author

Listed:
  • Iria, José
  • Scott, Paul
  • Attarha, Ahmad
  • Gordon, Dan
  • Franklin, Evan

Abstract

The large-scale adoption of commercial and residential distributed energy resources (DER) is transforming passive consumers into active prosumers. This new paradigm opens a door for aggregators to transform DER flexibility into electricity market services. However, it also brings new challenges for the distribution system operator (DSO) since aggregator actions may cause voltage and congestion problems in medium voltage (MV) and low voltage (LV) distribution networks. This paper addresses these challenges by proposing a new bidding optimisation strategy for an aggregator of prosumers to make network-secure bidding decisions in real-time energy and reserve markets. The bidding strategy uses the alternating direction method of multipliers on a rolling horizon framework to negotiate MV-LV network-secure bids between the aggregator and DSO, without jeopardizing the data privacy of either agent. The experiments run on a real-world case study show that the proposed bidding strategy outperforms state-of-the-art strategies, by computing MV-LV network-secure bids in fast execution times. Furthermore, the experiments also show that most of the DER value can reach the market with the proposed bidding strategy, even in heavily network-constrained scenarios of DER (up to 87% of the potential value in the most extreme DER scenario).

Suggested Citation

  • Iria, José & Scott, Paul & Attarha, Ahmad & Gordon, Dan & Franklin, Evan, 2022. "MV-LV network-secure bidding optimisation of an aggregator of prosumers in real-time energy and reserve markets," Energy, Elsevier, vol. 242(C).
    • Handle: RePEc:eee:energy:v:242:y:2022:i:c:s0360544221032114
    DOI: 10.1016/j.energy.2021.122962
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221032114
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.122962?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. Das, Saborni & Basu, Mousumi, 2020. "Day-ahead optimal bidding strategy of microgrid with demand response program considering uncertainties and outages of renewable energy resources," Energy, Elsevier, vol. 190(C).
    2. Iria, José & Soares, Filipe & Matos, Manuel, 2019. "Optimal bidding strategy for an aggregator of prosumers in energy and secondary reserve markets," Applied Energy, Elsevier, vol. 238(C), pages 1361-1372.
    3. Lu, Xiaoxing & Li, Kangping & Xu, Hanchen & Wang, Fei & Zhou, Zhenyu & Zhang, Yagang, 2020. "Fundamentals and business model for resource aggregator of demand response in electricity markets," Energy, Elsevier, vol. 204(C).
    4. Iria, José & Scott, Paul & Attarha, Ahmad, 2020. "Network-constrained bidding optimization strategy for aggregators of prosumers," Energy, Elsevier, vol. 207(C).
    5. Wang, Fei & Ge, Xinxin & Yang, Peng & Li, Kangping & Mi, Zengqiang & Siano, Pierluigi & Duić, Neven, 2020. "Day-ahead optimal bidding and scheduling strategies for DER aggregator considering responsive uncertainty under real-time pricing," Energy, Elsevier, vol. 213(C).
    6. Coelho, António & Iria, José & Soares, Filipe, 2021. "Network-secure bidding optimization of aggregators of multi-energy systems in electricity, gas, and carbon markets," Applied Energy, Elsevier, vol. 301(C).
    7. Ottesen, Stig Ødegaard & Tomasgard, Asgeir & Fleten, Stein-Erik, 2016. "Prosumer bidding and scheduling in electricity markets," Energy, Elsevier, vol. 94(C), pages 828-843.
    8. Correa-Florez, Carlos Adrian & Michiorri, Andrea & Kariniotakis, Georges, 2018. "Robust optimization for day-ahead market participation of smart-home aggregators," Applied Energy, Elsevier, vol. 229(C), pages 433-445.
    9. Gomes, I.L.R. & Melicio, R. & Mendes, V.M.F., 2021. "A novel microgrid support management system based on stochastic mixed-integer linear programming," Energy, Elsevier, vol. 223(C).
    10. Moghaddam, Saeed Zolfaghari & Akbari, Tohid, 2018. "Network-constrained optimal bidding strategy of a plug-in electric vehicle aggregator: A stochastic/robust game theoretic approach," Energy, Elsevier, vol. 151(C), pages 478-489.
    11. Jafari, Amirreza & Ganjeh Ganjehlou, Hamed & Khalili, Tohid & Bidram, Ali, 2020. "A fair electricity market strategy for energy management and reliability enhancement of islanded multi-microgrids," Applied Energy, Elsevier, vol. 270(C).
    12. Ottesen, Stig Ødegaard & Tomasgard, Asgeir & Fleten, Stein-Erik, 2018. "Multi market bidding strategies for demand side flexibility aggregators in electricity markets," Energy, Elsevier, vol. 149(C), pages 120-134.
    13. Iria, José & Soares, Filipe, 2019. "Real-time provision of multiple electricity market products by an aggregator of prosumers," Applied Energy, Elsevier, vol. 255(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. Suryakiran, B.V. & Nizami, Sohrab & Verma, Ashu & Saha, Tapan Kumar & Mishra, Sukumar, 2023. "A DSO-based day-ahead market mechanism for optimal operational planning of active distribution network," Energy, Elsevier, vol. 282(C).
    2. Wei Ding & Xuguang Zhao & Weigao Meng & Haichao Wang, 2022. "Smart Evaluation of Sustainability of Photovoltaic Projects in the Context of Carbon Neutrality Target," Sustainability, MDPI, vol. 14(22), pages 1-18, November.
    3. Zabihinia Gerdroodbari, Yasin & Khorasany, Mohsen & Razzaghi, Reza & Heidari, Rahmat, 2024. "Management of prosumers using dynamic export limits and shared Community Energy Storage," Applied Energy, Elsevier, vol. 355(C).
    4. Sun, Guoqiang & Shen, Sichen & Chen, Sheng & Zhou, Yizhou & Wei, Zhinong, 2022. "Bidding strategy for a prosumer aggregator with stochastic renewable energy production in energy and reserve markets," Renewable Energy, Elsevier, vol. 191(C), pages 278-290.
    5. Seyedhossein, Seyed Saeed & Moeini-Aghtaie, Moein, 2022. "Risk management framework of peer-to-peer electricity markets," Energy, Elsevier, vol. 261(PB).
    6. Zabihinia Gerdroodbari, Yasin & Khorasany, Mohsen & Razzaghi, Reza, 2022. "Dynamic PQ Operating Envelopes for prosumers in distribution networks," Applied Energy, Elsevier, vol. 325(C).
    7. Meng, Anbo & Xu, Xuancong & Zhang, Zhan & Zeng, Cong & Liang, Ruduo & Zhang, Zheng & Wang, Xiaolin & Yan, Baiping & Yin, Hao & Luo, Jianqiang, 2022. "Solving high-dimensional multi-area economic dispatch problem by decoupled distributed crisscross optimization algorithm with population cross generation strategy," Energy, Elsevier, vol. 258(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. Iria, José & Scott, Paul & Attarha, Ahmad, 2020. "Network-constrained bidding optimization strategy for aggregators of prosumers," Energy, Elsevier, vol. 207(C).
    2. Xiao, Xiangsheng & Wang, Jianxiao & Lin, Rui & Hill, David J. & Kang, Chongqing, 2020. "Large-scale aggregation of prosumers toward strategic bidding in joint energy and regulation markets," Applied Energy, Elsevier, vol. 271(C).
    3. Khojasteh, Meysam & Faria, Pedro & Lezama, Fernando & Vale, Zita, 2022. "Optimal strategy of electricity and natural gas aggregators in the energy and balance markets," Energy, Elsevier, vol. 257(C).
    4. Okur, Özge & Heijnen, Petra & Lukszo, Zofia, 2021. "Aggregator’s business models in residential and service sectors: A review of operational and financial aspects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    5. Tang, Hong & Wang, Shengwei, 2022. "Multi-level optimal dispatch strategy and profit-sharing mechanism for unlocking energy flexibilities of non-residential building clusters in electricity markets of multiple flexibility services," Renewable Energy, Elsevier, vol. 201(P1), pages 35-45.
    6. Bohlayer, Markus & Fleschutz, Markus & Braun, Marco & Zöttl, Gregor, 2020. "Energy-intense production-inventory planning with participation in sequential energy markets," Applied Energy, Elsevier, vol. 258(C).
    7. Sun, Guoqiang & Shen, Sichen & Chen, Sheng & Zhou, Yizhou & Wei, Zhinong, 2022. "Bidding strategy for a prosumer aggregator with stochastic renewable energy production in energy and reserve markets," Renewable Energy, Elsevier, vol. 191(C), pages 278-290.
    8. Piao, Longjian & de Vries, Laurens & de Weerdt, Mathijs & Yorke-Smith, Neil, 2021. "Electricity markets for DC distribution systems: Locational pricing trumps wholesale pricing," Energy, Elsevier, vol. 214(C).
    9. Liu, Xin & Li, Yang & Lin, Xueshan & Guo, Jiqun & Shi, Yunpeng & Shen, Yunwei, 2022. "Dynamic bidding strategy for a demand response aggregator in the frequency regulation market," Applied Energy, Elsevier, vol. 314(C).
    10. Alexandra Lüth & Jens Weibezahn & Jan Martin Zepter, 2020. "On Distributional Effects in Local Electricity Market Designs—Evidence from a German Case Study," Energies, MDPI, vol. 13(8), pages 1-26, April.
    11. Herding, Robert & Ross, Emma & Jones, Wayne R. & Charitopoulos, Vassilis M. & Papageorgiou, Lazaros G., 2023. "Stochastic programming approach for optimal day-ahead market bidding curves of a microgrid," Applied Energy, Elsevier, vol. 336(C).
    12. Héctor Marañón-Ledesma & Asgeir Tomasgard, 2019. "Analyzing Demand Response in a Dynamic Capacity Expansion Model for the European Power Market," Energies, MDPI, vol. 12(15), pages 1-24, August.
    13. Lu, Xiaoxing & Li, Kangping & Xu, Hanchen & Wang, Fei & Zhou, Zhenyu & Zhang, Yagang, 2020. "Fundamentals and business model for resource aggregator of demand response in electricity markets," Energy, Elsevier, vol. 204(C).
    14. Đorđe Lazović & Željko Đurišić, 2023. "Advanced Flexibility Support through DSO-Coordinated Participation of DER Aggregators in the Balancing Market," Energies, MDPI, vol. 16(8), pages 1-26, April.
    15. Stig Ødegaard Ottesen & Martin Haug & Heidi S. Nygård, 2020. "A Framework for Offering Short-Term Demand-Side Flexibility to a Flexibility Marketplace," Energies, MDPI, vol. 13(14), pages 1-17, July.
    16. Vinicius Braga Ferreira da Costa & Gabriel Nasser Doyle de Doile & Gustavo Troiano & Bruno Henriques Dias & Benedito Donizeti Bonatto & Tiago Soares & Walmir de Freitas Filho, 2022. "Electricity Markets in the Context of Distributed Energy Resources and Demand Response Programs: Main Developments and Challenges Based on a Systematic Literature Review," Energies, MDPI, vol. 15(20), pages 1-43, October.
    17. Wang, Yubin & Zheng, Yanchong & Yang, Qiang, 2023. "Nash bargaining based collaborative energy management for regional integrated energy systems in uncertain electricity markets," Energy, Elsevier, vol. 269(C).
    18. Jun Dong & Yuanyuan Wang & Xihao Dou & Zhengpeng Chen & Yaoyu Zhang & Yao Liu, 2021. "Research on Decision Optimization Model of Microgrid Participating in Spot Market Transaction," Sustainability, MDPI, vol. 13(12), pages 1-26, June.
    19. Nemanja Mišljenović & Matej Žnidarec & Goran Knežević & Damir Šljivac & Andreas Sumper, 2023. "A Review of Energy Management Systems and Organizational Structures of Prosumers," Energies, MDPI, vol. 16(7), pages 1-32, March.
    20. Wang, Fei & Ge, Xinxin & Yang, Peng & Li, Kangping & Mi, Zengqiang & Siano, Pierluigi & Duić, Neven, 2020. "Day-ahead optimal bidding and scheduling strategies for DER aggregator considering responsive uncertainty under real-time pricing," Energy, Elsevier, vol. 213(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:energy:v:242:y:2022:i:c:s0360544221032114. 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.journals.elsevier.com/energy .

    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.