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A dynamic migration route planning optimization strategy based on real-time energy state observation considering flexibility and energy efficiency of thermal power unit

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Listed:
  • Hong, Feng
  • Zhao, Yuzheng
  • Ji, Weiming
  • Hao, Junhong
  • Fang, Fang
  • Liu, Jizhen

Abstract

New energy resources compromising intermittent and fluctuating natures have been integrated into the power grid on a large scale, and thermal power units are obliged to promote the depth of deep peak shaving and flexible response-ability to cope with this new scenario. The safety, flexibility, and high efficiency of coal-fired units are the ultimate goals of its transformation, and there is a mutual influence and mutual restriction relationship among these indicators. To exploit the flexibility of thermal power units, take into account efficiency and safety, and play a supporting role in the new power system, a control strategy that weighs various indicators needs to be developed. Based on heat flow model and dynamic state space model, and updated matrix in real time, the key process parameters affecting the flexibility of heat transfer can be fully characterized. By using the observed state and calculation, the load response index and the energy efficiency index are optimized under the boundary constraint. The results show that the multi-objective optimization methods can avoid over regulation, reduce the flue gas flow by 3.23%–3.59%, and reduce the fluctuation of state quantity under the premise of satisfying the load response rate, about 2.32%–2.52% away from the safety boundary of the design temperature parameter to achieve the flexibility of frequency modulation, high efficiency of energy transmission and operation safety.

Suggested Citation

  • Hong, Feng & Zhao, Yuzheng & Ji, Weiming & Hao, Junhong & Fang, Fang & Liu, Jizhen, 2025. "A dynamic migration route planning optimization strategy based on real-time energy state observation considering flexibility and energy efficiency of thermal power unit," Applied Energy, Elsevier, vol. 377(PB).
  • Handle: RePEc:eee:appene:v:377:y:2025:i:pb:s0306261924019585
    DOI: 10.1016/j.apenergy.2024.124575
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    2. Chen, Yunxiao & Liu, Jinfu & Yu, Daren, 2025. "From baseload to flexibility: A cost-driven evolutionary model for thermal power industry at various stages of the China's “dual carbon” policy," Applied Energy, Elsevier, vol. 401(PB).
    3. Liu, Zefeng & Wang, Chaoyang & Fan, Mengyang & Wang, Zhu & Fang, Fang & Liu, Ming & Yan, Junjie, 2025. "Investigation on the allowable load ramping-up rate and wet-to-dry conversion time of a 660 MW supercritical coal-fired power plant with deep peak-shaving work conditions," Energy, Elsevier, vol. 314(C).
    4. Tao, Qihao & Lei, Xianliang & Hu, Yunsheng & Zhou, Xu, 2025. "Flow instability of 600 MW supercritical boiler water-cooled wall under low-load in deep peak-shaving process," Energy, Elsevier, vol. 333(C).
    5. Cui, Zhipeng & Jiang, Kaijun & Chen, Weixiong & Wang, Jinshi & Niu, Yuguang, 2025. "Digital twin enhanced hybrid modelling for main steam temperature optimization of flexible power plant," Energy, Elsevier, vol. 335(C).
    6. Zhao, Chenyu & Wang, Chaoyang & Liu, Ming & Liu, Jiping & Yan, Junjie, 2025. "Cascade co-optimization of the load ramp-down capability considering the transient stored energy of subcritical CFB power units," Energy, Elsevier, vol. 332(C).

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