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Estimating ramping requirements with solar-friendly flexible ramping product in multi-timescale power system operations

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  • Cui, Mingjian
  • Zhang, Jie

Abstract

The increasing solar power penetration causes the need of additional flexibility for power system operations. Market-based flexible ramping services have been proposed in several balance authorities to address this issue. However, the ramping requirements in multi-timescale power system operations are not well defined and still challenging to be accurately estimated. To this end, this paper develops a multi-timescale unit commitment and economic dispatch model to estimate the ramping requirements. Furthermore, a solar power ramping product (SPRP) is developed and integrated into the multi-timescale dispatch model that considers new objective functions, ramping capacity limits, active power limits, and flexible ramping requirements. To find the optimal ramping requirement based on the level of uncertainty in netload, a surrogate-based optimization model is developed to approximate the objective function of the multi-timescale dispatch model that considers both economic and reliability benefits of the balancing authorities. Numerical simulations on a modified IEEE 118-bus system show that a better estimation of ramping requirements could enhance both the reliability and economic benefits of the system. The use of SPRP can reduce the flexible ramping reserves provided by conventional generators.

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  • 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.
    • Handle: RePEc:eee:appene:v:225:y:2018:i:c:p:27-41
    DOI: 10.1016/j.apenergy.2018.05.031
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    3. Li, Binghui & Feng, Cong & Siebenschuh, Carlo & Zhang, Rui & Spyrou, Evangelia & Krishnan, Venkat & Hobbs, Benjamin F. & Zhang, Jie, 2022. "Sizing ramping reserve using probabilistic solar forecasts: A data-driven method," Applied Energy, Elsevier, vol. 313(C).
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    5. Abdollahi, Elnaz & Wang, Haichao & Lahdelma, Risto, 2019. "Parametric optimization of long-term multi-area heat and power production with power storage," Applied Energy, Elsevier, vol. 235(C), pages 802-812.
    6. Liu, Yuanzhi & Zhang, Jie, 2019. "Design a J-type air-based battery thermal management system through surrogate-based optimization," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    7. Mirzaei, Mohammad Amin & Sadeghi-Yazdankhah, Ahmad & Mohammadi-Ivatloo, Behnam & Marzband, Mousa & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Integration of emerging resources in IGDT-based robust scheduling of combined power and natural gas systems considering flexible ramping products," Energy, Elsevier, vol. 189(C).
    8. Sreekumar, Sreenu & Yamujala, Sumanth & Sharma, Kailash Chand & Bhakar, Rohit & Simon, Sishaj P. & Rana, Ankur Singh, 2022. "Flexible Ramp Products: A solution to enhance power system flexibility," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    9. Chen, Xiaoyang & Du, Yang & Lim, Enggee & Fang, Lurui & Yan, Ke, 2022. "Towards the applicability of solar nowcasting: A practice on predictive PV power ramp-rate control," Renewable Energy, Elsevier, vol. 195(C), pages 147-166.
    10. Fan, Shuai & Liu, Jiang & Wu, Qing & Cui, Mingjian & Zhou, Huan & He, Guangyu, 2020. "Optimal coordination of virtual power plant with photovoltaics and electric vehicles: A temporally coupled distributed online algorithm," Applied Energy, Elsevier, vol. 277(C).

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