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A Bi-Level Peak Regulation Optimization Model for Power Systems Considering Ramping Capability and Demand Response

Author

Listed:
  • Linbo Fang

    (State Grid Anhui Electric Power Company, Hefei 230061, China)

  • Wei Peng

    (State Grid Anhui Electric Power Company, Hefei 230061, China)

  • Youliang Li

    (State Grid Anhui Electric Power Company, Hefei 230061, China)

  • Zi Yang

    (State Grid Anhui Electric Power Company, Hefei 230061, China)

  • Yi Sun

    (State Grid Anhui Electric Power Company, Hefei 230061, China)

  • Hang Liu

    (State Grid Anhui Electric Power Company, Hefei 230061, China)

  • Lei Xu

    (State Grid Anhui Electric Power Company, Hefei 230061, China)

  • Lei Sun

    (School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China)

  • Weikang Fang

    (School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China)

Abstract

In the context of constructing new power systems, the intermittency and volatility of high-penetration renewable generation pose new challenges to the stability and secure operation of power systems. Enhancing the ramping capability of power systems has become a crucial measure for addressing these challenges. Therefore, this paper proposes a bi-level peak regulation optimization model for power systems considering ramping capability and demand response, aiming to mitigate the challenges that the uncertainty and volatility of renewable energy generation impose on power system operations. Firstly, the upper-level model focuses on minimizing the ramping demand caused by the uncertainty, taking into account concerned constraints such as the constraint of price-guided demand response, the constraint of satisfaction with electricity usage patterns, and the constraint of cost satisfaction. By solving the upper-level model, the ramping demand of the power system can be reduced. Secondly, the lower-level model aims to minimize the overall cost of the power system, considering constraints such as power balance constraints, power flow constraints, ramping capability constraints of thermal power units, stepwise ramp rate calculation constraints, and constraints of carbon capture units. Based on the ramping demand obtained by solving the upper-level model, the outputs of the generation units are optimized to reduce operation cost of power systems. Finally, the proposed peak regulation optimization model is verified through simulation based on the IEEE 39-bus system. The results indicate that the proposed model, which incorporates ramping capability and demand response, effectively reduces the comprehensive operational cost of the power system.

Suggested Citation

  • Linbo Fang & Wei Peng & Youliang Li & Zi Yang & Yi Sun & Hang Liu & Lei Xu & Lei Sun & Weikang Fang, 2024. "A Bi-Level Peak Regulation Optimization Model for Power Systems Considering Ramping Capability and Demand Response," Energies, MDPI, vol. 17(19), pages 1-17, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:19:p:4892-:d:1488940
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    References listed on IDEAS

    as
    1. Hungyu Kwon & Jong-Keun Park & Dam Kim & Jihyun Yi & Hyeongon Park, 2016. "A Flexible Ramping Capacity Model for Generation Scheduling with High Levels of Wind Energy Penetration," Energies, MDPI, vol. 9(12), pages 1-17, December.
    2. Junhui, L.I. & Pan, Yahui & Mu, Gang & Chen, Guohang & Zhu, Xingxu & Yan, Ganggui & Li, Cuiping & Jia, Chen, 2024. "A hierarchical demand assessment methodology of peaking resources in multi-areas interconnected systems with a high percentage of renewables," Applied Energy, Elsevier, vol. 367(C).
    Full references (including those not matched with items on IDEAS)

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