IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v262y2023ipas0360544222023167.html
   My bibliography  Save this article

Distributionally robust unit commitment with an adjustable uncertainty set and dynamic demand response

Author

Listed:
  • Qing, Ke
  • Huang, Qi
  • Du, Yuefang
  • Jiang, Lin
  • Bamisile, Olusola
  • Hu, Weihao

Abstract

To address the uncertainty of renewable energy in unit commitment, an adjustable uncertainty set of renewable energy is introduced and unit commitment is scheduled to guarantee the safe operation of the power system in this set. However, the operational risk arises when renewable energy falls out of the adjustable uncertainty set and this risk should be evaluated to determine the adjustable uncertainty set. In this paper, a distributionally robust optimization approach is proposed to calculate the risks of load shedding and renewable energy curtailment at the lower and upper bounds of the adjustable uncertainty set. After the evaluation of the operational risk, the day-ahead unit commitment with the adjustable uncertainty set is determined together with the demand response reserve in the reduction of the operational risk. In real time, the dynamic demand response is proposed to further reduce the operational risk. The proposed distributionally robust method with the dynamic demand response for dealing with the uncertainty of renewable energy is verified on the IEEE 6-bus, 30-bus, and 118-bus systems. Simulation results show that the proposed method reduces the cost of the unit commitment and the operational risk.

Suggested Citation

  • Qing, Ke & Huang, Qi & Du, Yuefang & Jiang, Lin & Bamisile, Olusola & Hu, Weihao, 2023. "Distributionally robust unit commitment with an adjustable uncertainty set and dynamic demand response," Energy, Elsevier, vol. 262(PA).
    • Handle: RePEc:eee:energy:v:262:y:2023:i:pa:s0360544222023167
    DOI: 10.1016/j.energy.2022.125434
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222023167
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.125434?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, Chuan & Wu, Lei & Liu, Tianqi & Wei, Wei & Wang, Cheng, 2018. "Co-optimization scheduling of interdependent power and gas systems with electricity and gas uncertainties," Energy, Elsevier, vol. 159(C), pages 1003-1015.
    2. Shahbazitabar, Maryam & Abdi, Hamdi, 2018. "A novel priority-based stochastic unit commitment considering renewable energy sources and parking lot cooperation," Energy, Elsevier, vol. 161(C), pages 308-324.
    3. Zhang, Yachao & Liu, Yan & Shu, Shengwen & Zheng, Feng & Huang, Zhanghao, 2021. "A data-driven distributionally robust optimization model for multi-energy coupled system considering the temporal-spatial correlation and distribution uncertainty of renewable energy sources," Energy, Elsevier, vol. 216(C).
    4. Razavi, Seyed-Ehsan & Esmaeel Nezhad, Ali & Mavalizadeh, Hani & Raeisi, Fatima & Ahmadi, Abdollah, 2018. "Robust hydrothermal unit commitment: A mixed-integer linear framework," Energy, Elsevier, vol. 165(PB), pages 593-602.
    5. Daraei, Mahsa & Campana, Pietro Elia & Thorin, Eva, 2020. "Power-to-hydrogen storage integrated with rooftop photovoltaic systems and combined heat and power plants," Applied Energy, Elsevier, vol. 276(C).
    6. Shams, Mohammad H. & Shahabi, Majid & MansourLakouraj, Mohammad & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Adjustable robust optimization approach for two-stage operation of energy hub-based microgrids," Energy, Elsevier, vol. 222(C).
    7. Abdi, Hamdi, 2021. "Profit-based unit commitment problem: A review of models, methods, challenges, and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    8. 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.
    9. Vatanpour, Mohsen & Sadeghi Yazdankhah, Ahmad, 2018. "The impact of energy storage modeling in coordination with wind farm and thermal units on security and reliability in a stochastic unit commitment," Energy, Elsevier, vol. 162(C), pages 476-490.
    10. Pinto, Mauro S.S. & Miranda, Vladimiro & Saavedra, Osvaldo R., 2016. "Risk and unit commitment decisions in scenarios of wind power uncertainty," Renewable Energy, Elsevier, vol. 97(C), pages 550-558.
    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. 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).

    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. Dong, Jizhe & Han, Shunjie & Shao, Xiangxin & Tang, Like & Chen, Renhui & Wu, Longfei & Zheng, Cunlong & Li, Zonghao & Li, Haolin, 2021. "Day-ahead wind-thermal unit commitment considering historical virtual wind power data," Energy, Elsevier, vol. 235(C).
    2. Luis Montero & Antonio Bello & Javier Reneses, 2022. "A Review on the Unit Commitment Problem: Approaches, Techniques, and Resolution Methods," Energies, MDPI, vol. 15(4), pages 1-40, February.
    3. 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.
    4. Diaa Salman & Mehmet Kusaf, 2021. "Short-Term Unit Commitment by Using Machine Learning to Cover the Uncertainty of Wind Power Forecasting," Sustainability, MDPI, vol. 13(24), pages 1-22, December.
    5. Wang, Yunqi & Qiu, Jing & Tao, Yuechuan, 2022. "Robust energy systems scheduling considering uncertainties and demand side emission impacts," Energy, Elsevier, vol. 239(PD).
    6. Zhu, Xiaodong & Zhao, Shihao & Yang, Zhile & Zhang, Ning & Xu, Xinzhi, 2022. "A parallel meta-heuristic method for solving large scale unit commitment considering the integration of new energy sectors," Energy, Elsevier, vol. 238(PC).
    7. Wang, Yuwei & Yang, Yuanjuan & Fei, Haoran & Song, Minghao & Jia, Mengyao, 2022. "Wasserstein and multivariate linear affine based distributionally robust optimization for CCHP-P2G scheduling considering multiple uncertainties," Applied Energy, Elsevier, vol. 306(PA).
    8. Harun Or Rashid Howlader & Oludamilare Bode Adewuyi & Ying-Yi Hong & Paras Mandal & Ashraf Mohamed Hemeida & Tomonobu Senjyu, 2019. "Energy Storage System Analysis Review for Optimal Unit Commitment," Energies, MDPI, vol. 13(1), pages 1-21, December.
    9. Zhang, Yachao & Huang, Zhanghao & Zheng, Feng & Zhou, Rongyu & Le, Jian & An, Xueli, 2020. "Cooperative optimization scheduling of the electricity-gas coupled system considering wind power uncertainty via a decomposition-coordination framework," Energy, Elsevier, vol. 194(C).
    10. 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).
    11. Iram Parvez & Jianjian Shen & Ishitaq Hassan & Nannan Zhang, 2021. "Generation of Hydro Energy by Using Data Mining Algorithm for Cascaded Hydropower Plant," Energies, MDPI, vol. 14(2), pages 1-28, January.
    12. 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).
    13. 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).
    14. Ceran, Bartosz, 2019. "The concept of use of PV/WT/FC hybrid power generation system for smoothing the energy profile of the consumer," Energy, Elsevier, vol. 167(C), pages 853-865.
    15. Shi, Mengshu & Wang, Weiye & Han, Yaxuan & Huang, Yuansheng, 2022. "Research on comprehensive benefit of hydrogen storage in microgrid system," Renewable Energy, Elsevier, vol. 194(C), pages 621-635.
    16. Richard P. van Leeuwen & Annelies E. Boerman & Edmund W. Schaefer & Gerwin Hoogsteen & Yashar S. Hajimolana, 2022. "Model Supported Business Case Scenario Analysis for Decentral Hydrogen Conversion, Storage and Consumption within Energy Hubs," Energies, MDPI, vol. 15(6), pages 1-22, March.
    17. Ying-Yi Hong & Gerard Francesco DG. Apolinario, 2021. "Uncertainty in Unit Commitment in Power Systems: A Review of Models, Methods, and Applications," Energies, MDPI, vol. 14(20), pages 1-47, October.
    18. Wilberforce, Tabbi & El Hassan, Zaki & Durrant, A. & Thompson, J. & Soudan, Bassel & Olabi, A.G., 2019. "Overview of ocean power technology," Energy, Elsevier, vol. 175(C), pages 165-181.
    19. Zhang, Tairan & Sobhani, Behrouz, 2023. "Optimal economic programming of an energy hub in the power system while taking into account the uncertainty of renewable resources, risk-taking and electric vehicles using a developed routing method," Energy, Elsevier, vol. 271(C).
    20. Mohammad Hemmati & Mehdi Abapour & Behnam Mohammadi-Ivatloo & Amjad Anvari-Moghaddam, 2020. "Optimal Operation of Integrated Electrical and Natural Gas Networks with a Focus on Distributed Energy Hub Systems," Sustainability, MDPI, vol. 12(20), pages 1-22, October.

    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:262:y:2023:i:pa:s0360544222023167. 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.