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Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power

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  • Azizipanah-Abarghooee, Rasoul
  • Golestaneh, Faranak
  • Gooi, Hoay Beng
  • Lin, Jeremy
  • Bavafa, Farhad
  • Terzija, Vladimir

Abstract

We propose a probabilistic unit commitment problem with incentive-based demand response and high level of wind power. Our novel formulation provides an optimal allocation of up/down spinning reserve. A more efficient unit commitment algorithm based on operational cycles is developed. A multi-period elastic residual demand economic model based on the self- and cross-price elasticities and customers’ benefit function is used. In the proposed scheme, the probability of residual demand falling within the up/down spinning reserve imposed by n−1 security criterion is considered as a stochastic constraint. A chance-constrained method, with a new iterative economic dispatch correction, wind power curtailment, and commitment of cheaper units, is applied to guarantee that the probability of loss of load is lower than a pre-defined risk level. The developed architecture builds upon an improved Jaya algorithm to generate feasible, robust and optimal solutions corresponding to the operational cost. The proposed framework is applied to a small test system with 10 units and also to the IEEE 118-bus system to illustrate its advantages in efficient scheduling of generation in the power systems.

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  • Azizipanah-Abarghooee, Rasoul & Golestaneh, Faranak & Gooi, Hoay Beng & Lin, Jeremy & Bavafa, Farhad & Terzija, Vladimir, 2016. "Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power," Applied Energy, Elsevier, vol. 182(C), pages 634-651.
    • Handle: RePEc:eee:appene:v:182:y:2016:i:c:p:634-651
    DOI: 10.1016/j.apenergy.2016.07.117
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    5. Motta, Vinicius N. & Anjos, Miguel F. & Gendreau, Michel, 2024. "Survey of optimization models for power system operation and expansion planning with demand response," European Journal of Operational Research, Elsevier, vol. 312(2), pages 401-412.
    6. 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).
    7. 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).
    8. Xiuyun Wang & Jian Wang & Biyuan Tian & Yang Cui & Yu Zhao, 2018. "Economic Dispatch of the Low-Carbon Green Certificate with Wind Farms Based on Fuzzy Chance Constraints," Energies, MDPI, vol. 11(4), pages 1-19, April.
    9. 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.
    10. Hlalele, Thabo G. & Zhang, Jiangfeng & Naidoo, Raj M. & Bansal, Ramesh C., 2021. "Multi-objective economic dispatch with residential demand response programme under renewable obligation," Energy, Elsevier, vol. 218(C).
    11. Isuru, Mohasha & Hotz, Matthias & Gooi, H.B. & Utschick, Wolfgang, 2020. "Network-constrained thermal unit commitment fortexhybrid AC/DC transmission grids under wind power uncertainty," Applied Energy, Elsevier, vol. 258(C).
    12. Qiao, Zheng & Guo, Qinglai & Sun, Hongbin & Pan, Zhaoguang & Liu, Yuquan & Xiong, Wen, 2017. "An interval gas flow analysis in natural gas and electricity coupled networks considering the uncertainty of wind power," Applied Energy, Elsevier, vol. 201(C), pages 343-353.
    13. Yang, Qingqing & Li, Jianwei & Cao, Wanke & Li, Shuangqi & Lin, Jie & Huo, Da & He, Hongwen, 2020. "An improved vehicle to the grid method with battery longevity management in a microgrid application," Energy, Elsevier, vol. 198(C).
    14. Jiang, Yibo & Xu, Jian & Sun, Yuanzhang & Wei, Congying & Wang, Jing & Ke, Deping & Li, Xiong & Yang, Jun & Peng, Xiaotao & Tang, Bowen, 2017. "Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system," Applied Energy, Elsevier, vol. 190(C), pages 1126-1137.
    15. Lei, Xingyu & Yang, Zhifang & Zhao, Junbo & Yu, Juan, 2022. "Data-driven assisted chance-constrained energy and reserve scheduling with wind curtailment," Applied Energy, Elsevier, vol. 321(C).
    16. Qingshan Xu & Yifan Ding & Aixia Zheng, 2017. "An Optimal Dispatch Model of Wind-Integrated Power System Considering Demand Response and Reliability," Sustainability, MDPI, vol. 9(5), pages 1-20, May.
    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. Wang, Shouxiang & Wang, Kai & Teng, Fei & Strbac, Goran & Wu, Lei, 2018. "An affine arithmetic-based multi-objective optimization method for energy storage systems operating in active distribution networks with uncertainties," Applied Energy, Elsevier, vol. 223(C), pages 215-228.
    19. 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.
    20. Yerzhigit Bapin & Mehdi Bagheri & Vasilios Zarikas, 2019. "Optimal Allocation of Spinning Reserves in Interconnected Energy Systems with Demand Response Using a Bivariate Wind Prediction Model," Energies, MDPI, vol. 12(20), pages 1-21, October.
    21. Ji, Ling & Zhang, Bei-Bei & Huang, Guo-He & Xie, Yu-Lei & Niu, Dong-Xiao, 2018. "Explicit cost-risk tradeoff for optimal energy management in CCHP microgrid system under fuzzy-risk preferences," Energy Economics, Elsevier, vol. 70(C), pages 525-535.
    22. Shabazbegian, Vahid & Ameli, Hossein & Ameli, Mohammad Taghi & Strbac, Goran & Qadrdan, Meysam, 2021. "Co-optimization of resilient gas and electricity networks; a novel possibilistic chance-constrained programming approach," Applied Energy, Elsevier, vol. 284(C).

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