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Parameter identification of condenser heat transfer model based on improved flower pollination algorithm.

Guodong Wang1, Min Zhang1, Jiayu Huang1

  • 1Guoneng (Zhaoqing) Thermal Power Co., Ltd., Zhaoqing, 526238, Guangdong, People's Republic of China.

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|November 10, 2025
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Summary
This summary is machine-generated.

This study introduces an improved flower pollination algorithm (FPA) for accurately identifying condenser heat transfer parameters. The enhanced method overcomes limitations of the classical FPA, improving condenser performance monitoring.

Keywords:
CondenserFlower pollination algorithmHeat transfer modelParameter identification

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Area of Science:

  • Thermodynamics
  • Mechanical Engineering
  • Optimization Algorithms

Background:

  • Condenser heat transfer parameters are vital for operational status assessment but are difficult to measure directly.
  • Current methods lack practical applicability for real-time performance monitoring due to measurement limitations.

Purpose of the Study:

  • To develop a novel parameter identification method for condenser heat transfer models.
  • To enhance the Flower Pollination Algorithm (FPA) for improved accuracy and fitting performance.

Main Methods:

  • Formulated a condenser heat transfer model and a guiding fitness function.
  • Introduced three enhancement strategies to the Flower Pollination Algorithm (FPA): dynamic pollination probability, chaotic initialization, and elite pollen mutation-crossover.
  • Conducted comparative experiments using real operational datasets.

Main Results:

  • The improved FPA demonstrated significantly higher parameter identification accuracy.
  • The enhanced algorithm exhibited superior model fitting performance compared to the classical FPA.
  • Effectively addressed premature convergence and limited fitting issues of the standard FPA.

Conclusions:

  • The developed improved FPA offers a more accurate and reliable method for identifying condenser heat transfer parameters.
  • This advancement enhances the practical applicability of condenser performance monitoring.
  • The optimized algorithm provides a robust solution for complex thermodynamic system modeling.