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Day-ahead wind-thermal unit commitment considering historical virtual wind power data

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Listed:
  • Dong, Jizhe
  • Han, Shunjie
  • Shao, Xiangxin
  • Tang, Like
  • Chen, Renhui
  • Wu, Longfei
  • Zheng, Cunlong
  • Li, Zonghao
  • Li, Haolin

Abstract

The uncertainty in wind power affects the generation scheduling (unit commitment) of coal-dominated power systems. A reasonable spinning reserve is required to handle this uncertainty. In this study, a method that considers the unique local wind regime into the calculation of spinning reserve requirements and makes the unit commitment more local-adaptive is presented. First, a virtual wind power transfer matrix which displays the probabilities of wind power transferring from one value to another by using the historical wind speed data is formulated. Second, the spinning reserve requirements of the wind-thermal power system are calculated according to the virtual wind power transfer matrix. Finally, the day-ahead unit commitment is conducted based on the spinning reserve calculation. The main advantage of using historical virtual wind power data, instead of historical wind speed data, is the acquisition of real wind power transfer probabilities, which avoids the distortion caused by the nonlinear conversion between wind power and wind speed. Application and comparison studies to demonstrate the effectiveness and cost benefits are performed on two systems. Sensitivity analyses of different parameters used in the method are also investigated.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:energy:v:235:y:2021:i:c:s0360544221015723
    DOI: 10.1016/j.energy.2021.121324
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    References listed on IDEAS

    as
    1. Yang, Zhile & Li, Kang & Guo, Yuanjun & Feng, Shengzhong & Niu, Qun & Xue, Yusheng & Foley, Aoife, 2019. "A binary symmetric based hybrid meta-heuristic method for solving mixed integer unit commitment problem integrating with significant plug-in electric vehicles," Energy, Elsevier, vol. 170(C), pages 889-905.
    2. Zhang, Heng & Hu, Xiao & Cheng, Haozhong & Zhang, Shenxi & Hong, Shaoyun & Gu, Qingfa, 2021. "Coordinated scheduling of generators and tie lines in multi-area power systems under wind energy uncertainty," Energy, Elsevier, vol. 222(C).
    3. Zhou, Min & Wang, Bo & Watada, Junzo, 2019. "Deep learning-based rolling horizon unit commitment under hybrid uncertainties," Energy, Elsevier, vol. 186(C).
    4. Wang, Bo & Zhou, Min & Xin, Bo & Zhao, Xin & Watada, Junzo, 2019. "Analysis of operation cost and wind curtailment using multi-objective unit commitment with battery energy storage," Energy, Elsevier, vol. 178(C), pages 101-114.
    5. 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).
    6. Yin, Yue & Liu, Tianqi & He, Chuan, 2019. "Day-ahead stochastic coordinated scheduling for thermal-hydro-wind-photovoltaic systems," Energy, Elsevier, vol. 187(C).
    7. Deane, J.P. & Drayton, G. & Ó Gallachóir, B.P., 2014. "The impact of sub-hourly modelling in power systems with significant levels of renewable generation," Applied Energy, Elsevier, vol. 113(C), pages 152-158.
    8. Jung, Christopher & Schindler, Dirk, 2021. "A global wind farm potential index to increase energy yields and accessibility," Energy, Elsevier, vol. 231(C).
    9. Ji, Bin & Yuan, Xiaohui & Chen, Zhihuan & Tian, Hao, 2014. "Improved gravitational search algorithm for unit commitment considering uncertainty of wind power," Energy, Elsevier, vol. 67(C), pages 52-62.
    10. 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).
    11. Kwon, Kyung-bin & Kim, Dam, 2020. "Enhanced method for considering energy storage systems as ancillary service resources in stochastic unit commitment," Energy, Elsevier, vol. 213(C).
    12. Zhou, Min & Wang, Bo & Li, Tiantian & Watada, Junzo, 2018. "A data-driven approach for multi-objective unit commitment under hybrid uncertainties," Energy, Elsevier, vol. 164(C), pages 722-733.
    13. 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).
    14. 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.
    15. 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.
    16. Smirnova, Elena & Kot, Sebastian & Kolpak, Eugeny & Shestak, Viktor, 2021. "Governmental support and renewable energy production: A cross-country review," Energy, Elsevier, vol. 230(C).
    17. Liu, Shuangquan & Xie, Mengfei, 2020. "Modeling the daily generation schedules in under-developed electricity markets with high-share renewables: A case study of Yunnan in China," Energy, Elsevier, vol. 201(C).
    18. Li, Chaoshun & Wang, Wenxiao & Wang, Jinwen & Chen, Deshu, 2019. "Network-constrained unit commitment with RE uncertainty and PHES by using a binary artificial sheep algorithm," Energy, Elsevier, vol. 189(C).
    19. 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.
    Full references (including those not matched with items on IDEAS)

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