IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v327y2022ics0306261922012818.html
   My bibliography  Save this article

Risk-averse TSO-DSOs coordinated distributed dispatching considering renewable energy and demand response uncertainties

Author

Listed:
  • Jiang, Tao
  • Wu, Chenghao
  • Zhang, Rufeng
  • Li, Xue
  • Li, Fangxing

Abstract

The renewable energy generation (REG) integration has introduced a significant amount of uncertainties to power systems. This new trend requires power systems to have sufficient flexibility to mitigate the power imbalance between supply and demand. Demand response (DR), as a potential flexibility resource, has gained widespread attention in recent years. However, communication failures or customers’ unexpected behaviors may result in DR uncertainties, leading to operational risks. To cope with the impacts of DR and REG uncertainties, this work proposes a stochastic programming-based risk-averse optimal dispatch model to reduce both electricity purchasing cost and potential risk cost through transmission network (TN) and active distribution networks (ADNs) coordinations. The risk-averse distributed optimal dispatch problem is formulated as two sub optimization models. One conducts the transmission-level risk-averse generation dispatch, while the other represents the distribution-level ADN market clearings. Moreover, the conditional value at risk (CVaR) is used to measure the potential risk cost caused by DR and REG uncertainties. Finally, the optimization model is solved by a distributed solution algorithm, alternating direction method of multipliers (ADMM), to preserve data privacy between multiple stakeholders and reduce communication requirements. The performance of the proposed approach is evaluated in T30-D2 × 33 and T118-D85 + D2 × 69 test systems, the results validate its effectiveness.

Suggested Citation

  • Jiang, Tao & Wu, Chenghao & Zhang, Rufeng & Li, Xue & Li, Fangxing, 2022. "Risk-averse TSO-DSOs coordinated distributed dispatching considering renewable energy and demand response uncertainties," Applied Energy, Elsevier, vol. 327(C).
    • Handle: RePEc:eee:appene:v:327:y:2022:i:c:s0306261922012818
    DOI: 10.1016/j.apenergy.2022.120024
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922012818
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.120024?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. Yuan, Zhao & Hesamzadeh, Mohammad Reza, 2017. "Hierarchical coordination of TSO-DSO economic dispatch considering large-scale integration of distributed energy resources," Applied Energy, Elsevier, vol. 195(C), pages 600-615.
    2. Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Jiang, Tao & Yu, Xiaodan, 2017. "Dynamic economic dispatch of a hybrid energy microgrid considering building based virtual energy storage system," Applied Energy, Elsevier, vol. 194(C), pages 386-398.
    3. 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.
    4. Mohan, Vivek & Singh, Jai Govind & Ongsakul, Weerakorn, 2015. "An efficient two stage stochastic optimal energy and reserve management in a microgrid," Applied Energy, Elsevier, vol. 160(C), pages 28-38.
    5. Zhang, Chunyu & Wang, Qi & Wang, Jianhui & Korpås, Magnus & Khodayar, Mohammad E., 2016. "Strategy-making for a proactive distribution company in the real-time market with demand response," Applied Energy, Elsevier, vol. 181(C), pages 540-548.
    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. Di Foggia, Giacomo & Beccarello, Massimo, 2024. "Designing New Energy Markets to Promote Renewables," MPRA Paper 121783, University Library of Munich, Germany.
    2. Jiang, Tao & Wu, Chenghao & Huang, Tao & Zhang, Rufeng & Li, Xue, 2024. "Optimal market participation of VPPs in TSO-DSO coordinated energy and flexibility markets," Applied Energy, Elsevier, vol. 360(C).
    3. Liu, Fan & Duan, Jiandong & Wu, Chen & Tian, Qinxing, 2024. "Risk-averse distributed optimization for integrated electricity-gas systems considering uncertainties of Wind-PV and power-to-gas," Renewable Energy, Elsevier, vol. 227(C).
    4. Vijay, Rohit & Mathuria, Parul, 2024. "Common TSO-DSO market framework with no upfront priority to utilize DER flexibility," Energy, Elsevier, vol. 299(C).
    5. Zhu, Peng & Zheng, J.H. & Li, Zhigang & Wu, Q.H. & Wang, Lixiao, 2024. "Optimal operation for district cooling systems coupled with ice storage units based on the per-unit value form," Energy, Elsevier, vol. 302(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. Chen, Houhe & Wang, Di & Zhang, Rufeng & Jiang, Tao & Li, Xue, 2022. "Optimal participation of ADN in energy and reserve markets considering TSO-DSO interface and DERs uncertainties," Applied Energy, Elsevier, vol. 308(C).
    2. Jin, Xiaolong & Wu, Qiuwei & Jia, Hongjie, 2020. "Local flexibility markets: Literature review on concepts, models and clearing methods," Applied Energy, Elsevier, vol. 261(C).
    3. Wang, Zibo & Yu, Xiaodan & Mu, Yunfei & Jia, Hongjie, 2020. "A distributed Peer-to-Peer energy transaction method for diversified prosumers in Urban Community Microgrid System," Applied Energy, Elsevier, vol. 260(C).
    4. Li, Jianwei & Xiong, Rui & Mu, Hao & Cornélusse, Bertrand & Vanderbemden, Philippe & Ernst, Damien & Yuan, Weijia, 2018. "Design and real-time test of a hybrid energy storage system in the microgrid with the benefit of improving the battery lifetime," Applied Energy, Elsevier, vol. 218(C), pages 470-478.
    5. de la Hoz, Jordi & Martín, Helena & Alonso, Alex & Carolina Luna, Adriana & Matas, José & Vasquez, Juan C. & Guerrero, Josep M., 2019. "Regulatory-framework-embedded energy management system for microgrids: The case study of the Spanish self-consumption scheme," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    6. Shahmohammadi, Ali & Sioshansi, Ramteen & Conejo, Antonio J. & Afsharnia, Saeed, 2018. "Market equilibria and interactions between strategic generation, wind, and storage," Applied Energy, Elsevier, vol. 220(C), pages 876-892.
    7. 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.
    8. 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).
    9. Jiang, Tao & Wu, Chenghao & Huang, Tao & Zhang, Rufeng & Li, Xue, 2024. "Optimal market participation of VPPs in TSO-DSO coordinated energy and flexibility markets," Applied Energy, Elsevier, vol. 360(C).
    10. Park, Sung-Won & Zhang, Zhong & Li, Furong & Son, Sung-Yong, 2021. "Peer-to-peer trading-based efficient flexibility securing mechanism to support distribution system stability," Applied Energy, Elsevier, vol. 285(C).
    11. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K., 2021. "Cooperative negawatt P2P energy trading for low-voltage distribution networks," Applied Energy, Elsevier, vol. 299(C).
    12. 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.
    13. Lyu, Cheng & Jia, Youwei & Xu, Zhao, 2021. "Fully decentralized peer-to-peer energy sharing framework for smart buildings with local battery system and aggregated electric vehicles," Applied Energy, Elsevier, vol. 299(C).
    14. Mengelkamp, Esther & Schönland, Thomas & Huber, Julian & Weinhardt, Christof, 2019. "The value of local electricity - A choice experiment among German residential customers," Energy Policy, Elsevier, vol. 130(C), pages 294-303.
    15. Jin, Hongyang & Li, Zhengshuo & Sun, Hongbin & Guo, Qinglai & Chen, Runze & Wang, Bin, 2017. "A robust aggregate model and the two-stage solution method to incorporate energy intensive enterprises in power system unit commitment," Applied Energy, Elsevier, vol. 206(C), pages 1364-1378.
    16. Ning Wang & Weisheng Xu & Weihui Shao & Zhiyu Xu, 2019. "A Q-Cube Framework of Reinforcement Learning Algorithm for Continuous Double Auction among Microgrids," Energies, MDPI, vol. 12(15), pages 1-26, July.
    17. Morshed, Mohammad Javad & Hmida, Jalel Ben & Fekih, Afef, 2018. "A probabilistic multi-objective approach for power flow optimization in hybrid wind-PV-PEV systems," Applied Energy, Elsevier, vol. 211(C), pages 1136-1149.
    18. João Mello & Cristina de Lorenzo & Fco. Alberto Campos & José Villar, 2023. "Pricing and Simulating Energy Transactions in Energy Communities," Energies, MDPI, vol. 16(4), pages 1-22, February.
    19. Pearson, Simon & Wellnitz, Sonja & Crespo del Granado, Pedro & Hashemipour, Naser, 2022. "The value of TSO-DSO coordination in re-dispatch with flexible decentralized energy sources: Insights for Germany in 2030," Applied Energy, Elsevier, vol. 326(C).
    20. Tsao, Yu-Chung & Thanh, Vo-Van, 2021. "Toward sustainable microgrids with blockchain technology-based peer-to-peer energy trading mechanism: A fuzzy meta-heuristic approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(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:appene:v:327:y:2022:i:c:s0306261922012818. 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.