IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v327y2022ics0306261922013198.html
   My bibliography  Save this article

Optimality-feasibility-aware multistage unit commitment considering nonanticipative realization of uncertainty

Author

Listed:
  • Qiu, Haifeng
  • Sun, Qirun
  • Lu, Xi
  • Beng Gooi, Hoay
  • Zhang, Suhan

Abstract

The intrinsic uncertainty in source-load power and line outage poses huge obstacles to unit commitment (UC) optimization in power grids. To satisfy the practical requests in power grids, this paper exploits a multistage robust UC method to promise both optimality and feasibility in nonanticipative scheduling. Firstly, a multistage robust UC model is established accounting for the sequential realization of uncertainty. This model makes decisions with the goals of economy in the normal condition and power balance in the emergent condition. Secondly, a customized multi-cut decomposition algorithm is offered to address the intractable multistage robust optimization problem. The original multistage problem is decoupled into the form of one master and several slave problems (MP-SPs), where the robust dual dynamic programming (RDDP) solves the resulting multistage max–min SPs, and the column-and-constraint generation (C&CG) algorithm successively constructs multiple cutting planes to ensure the optimality and convergence of the alternative optimizations between the MP and SPs. Computational tests on real-size power grids validate the practicability and superiority of the proposed multistage robust UC method, which is of great significance in guiding system operations.

Suggested Citation

  • Qiu, Haifeng & Sun, Qirun & Lu, Xi & Beng Gooi, Hoay & Zhang, Suhan, 2022. "Optimality-feasibility-aware multistage unit commitment considering nonanticipative realization of uncertainty," Applied Energy, Elsevier, vol. 327(C).
    • Handle: RePEc:eee:appene:v:327:y:2022:i:c:s0306261922013198
    DOI: 10.1016/j.apenergy.2022.120062
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922013198
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.120062?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. Qiu, Haifeng & You, Fengqi, 2020. "Decentralized-distributed robust electric power scheduling for multi-microgrid systems," Applied Energy, Elsevier, vol. 269(C).
    2. Feng, Wei & Feng, Yiping & Zhang, Qi, 2021. "Multistage robust mixed-integer optimization under endogenous uncertainty," European Journal of Operational Research, Elsevier, vol. 294(2), pages 460-475.
    3. Pombo, Daniel Vázquez & Martinez-Rico, Jon & Marczinkowski, Hannah M., 2022. "Towards 100% renewable islands in 2040 via generation expansion planning: The case of São Vicente, Cape Verde," Applied Energy, Elsevier, vol. 315(C).
    4. Rahim, Sahar & Wang, Zhen & Ju, Ping, 2022. "Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review," Applied Energy, Elsevier, vol. 319(C).
    5. Abdin, Adam F. & Caunhye, Aakil & Zio, Enrico & Cardin, Michel-Alexandre, 2022. "Optimizing generation expansion planning with operational uncertainty: A multistage adaptive robust approach," Applied Energy, Elsevier, vol. 306(PA).
    6. Huang, Zhanghao & Zhang, Yachao & Xie, Shiwei, 2022. "Data-adaptive robust coordinated optimization of dynamic active and reactive power flow in active distribution networks," Renewable Energy, Elsevier, vol. 188(C), pages 164-183.
    7. Qiu, Haifeng & Gu, Wei & Liu, Pengxiang & Sun, Qirun & Wu, Zhi & Lu, Xi, 2022. "Application of two-stage robust optimization theory in power system scheduling under uncertainties: A review and perspective," Energy, Elsevier, vol. 251(C).
    8. Gan, Wei & Yan, Mingyu & Yao, Wei & Guo, Jianbo & Ai, Xiaomeng & Fang, Jiakun & Wen, Jinyu, 2021. "Decentralized computation method for robust operation of multi-area joint regional-district integrated energy systems with uncertain wind power," Applied Energy, Elsevier, vol. 298(C).
    9. Zhou, Bo & Ai, Xiaomeng & Fang, Jiakun & Yao, Wei & Zuo, Wenping & Chen, Zhe & Wen, Jinyu, 2019. "Data-adaptive robust unit commitment in the hybrid AC/DC power system," Applied Energy, Elsevier, vol. 254(C).
    10. Álvaro Lorca & X. Andy Sun & Eugene Litvinov & Tongxin Zheng, 2016. "Multistage Adaptive Robust Optimization for the Unit Commitment Problem," Operations Research, INFORMS, vol. 64(1), pages 32-51, February.
    11. Angelos Georghiou & Angelos Tsoukalas & Wolfram Wiesemann, 2019. "Robust Dual Dynamic Programming," Operations Research, INFORMS, vol. 67(3), pages 813-830, May.
    12. Zhou, Yuzhou & Zhai, Qiaozhu & Yuan, Wei & Wu, Jiang, 2021. "Capacity expansion planning for wind power and energy storage considering hourly robust transmission constrained unit commitment," Applied Energy, Elsevier, vol. 302(C).
    13. Yang, Hongming & Liang, Rui & Yuan, Yuan & Chen, Bowen & Xiang, Sheng & Liu, Junpeng & Zhao, Huan & Ackom, Emmanuel, 2022. "Distributionally robust optimal dispatch in the power system with high penetration of wind power based on net load fluctuation data," Applied Energy, Elsevier, vol. 313(C).
    14. Zhang, Yachao & Xie, Shiwei & Shu, Shengwen, 2022. "Multi-stage robust optimization of a multi-energy coupled system considering multiple uncertainties," Energy, Elsevier, vol. 238(PC).
    15. G. Cobos, Noemi & Arroyo, José M. & Alguacil, Natalia & Street, Alexandre, 2018. "Network-constrained unit commitment under significant wind penetration: A multistage robust approach with non-fixed recourse," Applied Energy, Elsevier, vol. 232(C), pages 489-503.
    16. Sun, Peng & Teng, Yun & Chen, Zhe, 2021. "Robust coordinated optimization for multi-energy systems based on multiple thermal inertia numerical simulation and uncertainty analysis," Applied Energy, Elsevier, vol. 296(C).
    17. Silva, Jéssica Alice A. & López, Juan Camilo & Arias, Nataly Bañol & Rider, Marcos J. & da Silva, Luiz C.P., 2021. "An optimal stochastic energy management system for resilient microgrids," Applied Energy, Elsevier, vol. 300(C).
    18. Moretti, Luca & Martelli, Emanuele & Manzolini, Giampaolo, 2020. "An efficient robust optimization model for the unit commitment and dispatch of multi-energy systems and microgrids," Applied Energy, Elsevier, vol. 261(C).
    19. Jiang, Sufan & Wu, Chuanshen & Gao, Shan & Pan, Guangsheng & Liu, Yu & Zhao, Xin & Wang, Sicheng, 2022. "Robust frequency risk-constrained unit commitment model for AC-DC system considering wind uncertainty," Renewable Energy, Elsevier, vol. 195(C), pages 395-406.
    20. Zhou, Yuzhou & Zhao, Jiexing & Zhai, Qiaozhu, 2021. "100% renewable energy: A multi-stage robust scheduling approach for cascade hydropower system with wind and photovoltaic power," Applied Energy, Elsevier, vol. 301(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. Xiong, Houbo & Zhou, Yue & Guo, Chuangxin & Ding, Yi & Luo, Fengji, 2023. "Multi-stage risk-based assessment for wind energy accommodation capability: A robust and non-anticipative method," Applied Energy, Elsevier, vol. 350(C).
    2. Qiu, Haifeng & Vinod, Ashwin & Lu, Shuai & Gooi, Hoay Beng & Pan, Guangsheng & Zhang, Suhan & Veerasamy, Veerapandiyan, 2023. "Decentralized mixed-integer optimization for robust integrated electricity and heat scheduling," Applied Energy, Elsevier, vol. 350(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. Qiu, Haifeng & Gu, Wei & Liu, Pengxiang & Sun, Qirun & Wu, Zhi & Lu, Xi, 2022. "Application of two-stage robust optimization theory in power system scheduling under uncertainties: A review and perspective," Energy, Elsevier, vol. 251(C).
    2. Xiong, Houbo & Yan, Mingyu & Guo, Chuangxin & Ding, Yi & Zhou, Yue, 2023. "DP based multi-stage ARO for coordinated scheduling of CSP and wind energy with tractable storage scheme: Tight formulation and solution technique," Applied Energy, Elsevier, vol. 333(C).
    3. Jiang, Sufan & Gao, Shan & Pan, Guangsheng & Zhao, Xin & Liu, Yu & Guo, Yasen & Wang, Sicheng, 2020. "A novel robust security constrained unit commitment model considering HVDC regulation," Applied Energy, Elsevier, vol. 278(C).
    4. Yıldıran, Uğur, 2023. "Robust multi-stage economic dispatch with renewable generation and storage," European Journal of Operational Research, Elsevier, vol. 309(2), pages 890-909.
    5. Xiong, Houbo & Zhou, Yue & Guo, Chuangxin & Ding, Yi & Luo, Fengji, 2023. "Multi-stage risk-based assessment for wind energy accommodation capability: A robust and non-anticipative method," Applied Energy, Elsevier, vol. 350(C).
    6. Qiu, Haifeng & Vinod, Ashwin & Lu, Shuai & Gooi, Hoay Beng & Pan, Guangsheng & Zhang, Suhan & Veerasamy, Veerapandiyan, 2023. "Decentralized mixed-integer optimization for robust integrated electricity and heat scheduling," Applied Energy, Elsevier, vol. 350(C).
    7. Wang, Yubin & Dong, Wei & Yang, Qiang, 2022. "Multi-stage optimal energy management of multi-energy microgrid in deregulated electricity markets," Applied Energy, Elsevier, vol. 310(C).
    8. Zhao, Shihao & Li, Kang & Yang, Zhile & Xu, Xinzhi & Zhang, Ning, 2022. "A new power system active rescheduling method considering the dispatchable plug-in electric vehicles and intermittent renewable energies," Applied Energy, Elsevier, vol. 314(C).
    9. Ghilardi, Lavinia Marina Paola & Castelli, Alessandro Francesco & Moretti, Luca & Morini, Mirko & Martelli, Emanuele, 2021. "Co-optimization of multi-energy system operation, district heating/cooling network and thermal comfort management for buildings," Applied Energy, Elsevier, vol. 302(C).
    10. Luyu Wang & Houbo Xiong & Yunhui Shi & Chuangxin Guo, 2023. "Rolling Horizon Robust Real-Time Economic Dispatch with Multi-Stage Dynamic Modeling," Mathematics, MDPI, vol. 11(11), pages 1-20, June.
    11. Qiu, Haifeng & You, Fengqi, 2020. "Decentralized-distributed robust electric power scheduling for multi-microgrid systems," Applied Energy, Elsevier, vol. 269(C).
    12. Haiyan Zheng & Liying Huang & Ran Quan, 2023. "Mixed-Integer Conic Formulation of Unit Commitment with Stochastic Wind Power," Mathematics, MDPI, vol. 11(2), pages 1-16, January.
    13. Jiménez, Diego & Angulo, Alejandro & Street, Alexandre & Mancilla-David, Fernando, 2023. "A closed-loop data-driven optimization framework for the unit commitment problem: A Q-learning approach under real-time operation," Applied Energy, Elsevier, vol. 330(PB).
    14. Chaoyang Chen & Hualing Liu & Yong Xiao & Fagen Zhu & Li Ding & Fuwen Yang, 2022. "Power Generation Scheduling for a Hydro-Wind-Solar Hybrid System: A Systematic Survey and Prospect," Energies, MDPI, vol. 15(22), pages 1-31, November.
    15. Abdin, Adam F. & Caunhye, Aakil & Zio, Enrico & Cardin, Michel-Alexandre, 2022. "Optimizing generation expansion planning with operational uncertainty: A multistage adaptive robust approach," Applied Energy, Elsevier, vol. 306(PA).
    16. Polimeni, Simone & Moretti, Luca & Martelli, Emanuele & Leva, Sonia & Manzolini, Giampaolo, 2023. "A novel stochastic model for flexible unit commitment of off-grid microgrids," Applied Energy, Elsevier, vol. 331(C).
    17. Ahmadi, Seyed Ehsan & Sadeghi, Delnia & Marzband, Mousa & Abusorrah, Abdullah & Sedraoui, Khaled, 2022. "Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies," Energy, Elsevier, vol. 245(C).
    18. Gauvin, Charles & Delage, Erick & Gendreau, Michel, 2017. "Decision rule approximations for the risk averse reservoir management problem," European Journal of Operational Research, Elsevier, vol. 261(1), pages 317-336.
    19. Mansour-Saatloo, Amin & Pezhmani, Yasin & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies," Applied Energy, Elsevier, vol. 304(C).
    20. Zhang, Gaohang & Li, Fengting & Wang, Sen & Yin, Chunya, 2023. "Robust low-carbon energy and reserve scheduling considering operational risk and flexibility improvement," Energy, Elsevier, vol. 284(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:s0306261922013198. 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.