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Dynamic modeling and characteristic analysis of dry/wet state transition process for supercritical thermal power unit

Author

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  • Huang, Ting
  • Zhao, Chunhui
  • Zhang, Haoran

Abstract

-To accelerate the construction of low-carbon power system, the supercritical thermal power unit urgently plays an important peaking role to offer consumption for unstable renewable energy sources. Specifically, the dry/wet state transition is inevitable when unit undergoing the extremely deep peaking. However, existing unit models have not fully considered the dynamic characteristics and distributed parameters of dry/wet state transition process, thereby cannot provide reference for peaking controller designing. Thus, to obtain the dry/wet state bidirectional transition process model, a dynamic modeling method integrates the thermodynamics, Takagi-Sugeno fuzzy modeling and simulated annealing-white shark optimizer is proposed. First, the comprehensive mechanism model of supercritical thermal power unit is structured by analyzing the steam-water flow characteristics at both wet and dry state. Mechanism model effectively exhibits the key dynamic characteristic of unit during the peaking process. Second, the improved simulated annealing-white shark optimizer is proposed to collaborate with the Takagi-Sugeno fuzzy modeling to gain the optimal parameters in mechanism model. Then, model structure changes and distributed parameters in the dry/wet state bidirectional transition process are directly revealed. Finally, the prominent modeling performance of the proposed dynamic modeling method is validated on an actual 600 MW thermal power unit. The proposed dynamic model is more suitable for the designing of dry/wet state transition control strategy and its parameters tuning compared to the existing pure-mechanistic and data-driven model.

Suggested Citation

  • Huang, Ting & Zhao, Chunhui & Zhang, Haoran, 2025. "Dynamic modeling and characteristic analysis of dry/wet state transition process for supercritical thermal power unit," Energy, Elsevier, vol. 336(C).
  • Handle: RePEc:eee:energy:v:336:y:2025:i:c:s036054422504085x
    DOI: 10.1016/j.energy.2025.138443
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