IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i19p4890-d1488831.html
   My bibliography  Save this article

Real-Time Power Regulation of Flexible User-Side Resources in Distribution Networks via Dual Ascent Method

Author

Listed:
  • Yu Yang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Fushuan Wen

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Jiajia Yang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
    College of Science and Engineering, James Cook University, Townsville 4811, Australia)

  • Hangyue Liu

    (Sungrow Australia Group Pty. Ltd., Sydney 2060, Australia)

  • Dazheng Liu

    (China Energy Economic and Technological Research Institute Co., Ltd., Beijing 102299, China)

  • Shujun Xin

    (State Grid Corporation of China, Beijing 100031, China)

  • Hao Fan

    (State Grid Corporation of China, Beijing 100031, China)

  • Cong Wu

    (State Grid Energy Research Institute of China, Beijing 102209, China)

Abstract

Flexible user-side resources are of great potential in providing power regulation so as to effectively address the challenges of reverse power flow and overvoltage issues in distribution networks characterized by high photovoltaic (PV) penetration. However, existing distributed algorithms typically implement control signals after the convergence of the algorithms, making it difficult to track frequent and rapid fluctuations in PV power outputs in real time. Given this background, an online-distributed control algorithm for the real-time power regulation of flexible user-side resources is proposed in this paper. The objective of the established control model is to minimize network losses by dynamically adjusting active power outputs of flexible user-side resources and reactive power outputs of PV inverters while respecting branch power flow and voltage magnitude constraints. Furthermore, by deconstructing the centralized problem into a primal–dual one, a distributed control strategy based on the dual ascent method is implemented. With the proposed method, agents can achieve global optimality by exchanging limited information with their neighbors. The simulation results verify the good balance between economic efficiency and voltage control performance of the proposed method.

Suggested Citation

  • Yu Yang & Fushuan Wen & Jiajia Yang & Hangyue Liu & Dazheng Liu & Shujun Xin & Hao Fan & Cong Wu, 2024. "Real-Time Power Regulation of Flexible User-Side Resources in Distribution Networks via Dual Ascent Method," Energies, MDPI, vol. 17(19), pages 1-14, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:19:p:4890-:d:1488831
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/19/4890/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/19/4890/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Jianxiao & Zhong, Haiwang & Tang, Wenyuan & Rajagopal, Ram & Xia, Qing & Kang, Chongqing & Wang, Yi, 2017. "Optimal bidding strategy for microgrids in joint energy and ancillary service markets considering flexible ramping products," Applied Energy, Elsevier, vol. 205(C), pages 294-303.
    2. Tao Xu & He Meng & Jie Zhu & Wei Wei & He Zhao & Han Yang & Zijin Li & Yuhan Wu, 2021. "Optimal Capacity Allocation of Energy Storage in Distribution Networks Considering Active/Reactive Coordination," Energies, MDPI, vol. 14(6), pages 1-24, March.
    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. 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).
    2. Hong, Bowen & Zhang, Weitong & Zhou, Yue & Chen, Jian & Xiang, Yue & Mu, Yunfei, 2018. "Energy-Internet-oriented microgrid energy management system architecture and its application in China," Applied Energy, Elsevier, vol. 228(C), pages 2153-2164.
    3. Cong Liu & Jingyang Zhou & Yi Pan & Zhiyi Li & Yifei Wang & Dan Xu & Qiang Ding & Zhiqiang Luo & Mohammad Shahidehpour, 2019. "Multi-period Market Operation of Transmission-Distribution Systems Based on Heterogeneous Decomposition and Coordination," Energies, MDPI, vol. 12(16), pages 1-20, August.
    4. Erika Kaempf & Bernhard Ernst & Martin Braun, 2019. "Competitive cross‐voltage level procurement of reactive power considering reliable capacity from wind and photovoltaics," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(4), July.
    5. Rezaei, Navid & Pezhmani, Yasin & Khazali, Amirhossein, 2022. "Economic-environmental risk-averse optimal heat and power energy management of a grid-connected multi microgrid system considering demand response and bidding strategy," Energy, Elsevier, vol. 240(C).
    6. Gupta, Aparna & Palepu, Sai, 2024. "Designing risk-free service for renewable wind and solar resources," European Journal of Operational Research, Elsevier, vol. 315(2), pages 715-728.
    7. Yih-Der Lee & Wei-Chen Lin & Jheng-Lun Jiang & Jia-Hao Cai & Wei-Tzer Huang & Kai-Chao Yao, 2021. "Optimal Individual Phase Voltage Regulation Strategies in Active Distribution Networks with High PV Penetration Using the Sparrow Search Algorithm," Energies, MDPI, vol. 14(24), pages 1-22, December.
    8. 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.
    9. 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.
    10. Dranka, Géremi Gilson & Ferreira, Paula & Vaz, A. Ismael F., 2021. "A review of co-optimization approaches for operational and planning problems in the energy sector," Applied Energy, Elsevier, vol. 304(C).
    11. Mehdizadeh, Ali & Taghizadegan, Navid & Salehi, Javad, 2018. "Risk-based energy management of renewable-based microgrid using information gap decision theory in the presence of peak load management," Applied Energy, Elsevier, vol. 211(C), pages 617-630.
    12. 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).
    13. 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.
    14. Schwidtal, Jan Marc & Agostini, Marco & Coppo, Massimiliano & Bignucolo, Fabio & Lorenzoni, Arturo, 2023. "Optimized operation of distributed energy resources: The opportunities of value stacking for Power-to-Gas aggregated with PV," Applied Energy, Elsevier, vol. 334(C).
    15. Cui, Mingjian & Zhang, Jie, 2018. "Estimating ramping requirements with solar-friendly flexible ramping product in multi-timescale power system operations," Applied Energy, Elsevier, vol. 225(C), pages 27-41.
    16. Greve, Thomas & Teng, Fei & Pollitt, Michael G. & Strbac, Goran, 2018. "A system operator’s utility function for the frequency response market," Applied Energy, Elsevier, vol. 231(C), pages 562-569.
    17. Yeh, Wei-Chang & He, Min-Fan & Huang, Chia-Ling & Tan, Shi-Yi & Zhang, Xianyong & Huang, Yaohong & Li, Li, 2020. "New genetic algorithm for economic dispatch of stand-alone three-modular microgrid in DongAo Island," Applied Energy, Elsevier, vol. 263(C).
    18. Meng, He & Jia, Hongjie & Xu, Tao & Wei, Wei & Wu, Yuhan & Liang, Lemeng & Cai, Shuqi & Liu, Zuozheng & Wang, Rujing & Li, Mengchao, 2022. "Optimal configuration of cooperative stationary and mobile energy storage considering ambient temperature: A case for Winter Olympic Game," Applied Energy, Elsevier, vol. 325(C).
    19. Wang, Yubin & Yang, Qiang & Zhou, Yue & Zheng, Yanchong, 2024. "A risk-averse day-ahead bidding strategy of transactive energy sharing microgrids with data-driven chance constraints," Applied Energy, Elsevier, vol. 353(PB).
    20. Nikpour, Ahmad & Nateghi, Abolfazl & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Day-ahead optimal bidding of microgrids considering uncertainties of price and renewable energy resources," Energy, Elsevier, vol. 227(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:gam:jeners:v:17:y:2024:i:19:p:4890-:d:1488831. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.