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Improving the Flexibility of Coal-Fired Power Units by Dynamic Cold-End Optimization

Author

Listed:
  • Yanpeng Zhang

    (Shandong Zhongshi Yitong Group Co., Ltd., 2010 Wangyue Road, Jinan 250002, China)

  • Xinzhen Fang

    (Shandong Zhengyuan Industrial Development Co., Ltd., 150 Jing’er Road, Jinan 250000, China)

  • Zihan Kong

    (Shandong Wangrui Materials Co., Ltd., No. 17 Jingsan Road, Jinan 250000, China)

  • Zijiang Yang

    (Shandong Zhengyuan Industrial Development Co., Ltd., 150 Jing’er Road, Jinan 250000, China)

  • Jinxu Lao

    (Shandong Zhongshi Yitong Group Co., Ltd., 2010 Wangyue Road, Jinan 250002, China)

  • Wei Zheng

    (State Grid Shandong Electric Power Research Institute, 2000 Wangyue Road, Jinan 250003, China)

  • Lingkai Zhu

    (State Grid Shandong Electric Power Research Institute, 2000 Wangyue Road, Jinan 250003, China)

  • Jiwei Song

    (Institute of Thermal Science and Technology, Shandong University, Jinan 250061, China)

Abstract

Traditional coal-fired power units are required to improve their operational flexibility to accommodate increasing renewable energy. In this paper, an optimized operation approach of the cold-end system is proposed to improve the flexibility of coal-fired power units. The dynamic models of the cold-end system of a 330 MW coal-fired power unit are developed. The model validation results show that the error between the simulated results and measured values is <3% at the common load range and <5% at the low load range. The applications of cold-end optimization in the load-variation processes with ±3% Pe/min ramps and actual automatic generation control (AGC) response are then studied. The results show that when the back pressure of the unit is relatively low, the cold-end optimization is more effective in improving the ramp-down rate. On the contrary, when the unit operates with relatively high back pressure, this approach is more suitable for improving the ramp-up rate. Moreover, the AGC response quality is noticeably enhanced, which improves the phenomenon of overshooting and reverse regulation. The comprehensive performance indicator K P increased from 2.27 to 4.63 in the summer scenario, while it increased from 2.08 to 4.34 in the winter scenario. Moreover, the profits under the two scenarios are raised by 39.2% and 42.5%, respectively. The findings of this study are also applicable to supercritical units or other power units with the cold end adopting similar water cooling systems. Future work will incorporate advanced control theories to enhance control robustness, which is critical for the practical implementation of the proposed cold-end optimization approach.

Suggested Citation

  • Yanpeng Zhang & Xinzhen Fang & Zihan Kong & Zijiang Yang & Jinxu Lao & Wei Zheng & Lingkai Zhu & Jiwei Song, 2025. "Improving the Flexibility of Coal-Fired Power Units by Dynamic Cold-End Optimization," Energies, MDPI, vol. 18(13), pages 1-21, June.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:13:p:3375-:d:1688746
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    References listed on IDEAS

    as
    1. Wang, Runchen & Du, Xiaonan & Shi, Yuetao & Deng, Weipeng & Wang, Yuhao & Sun, Fengzhong, 2024. "A novel system for reducing power plant electricity consumption and enhancing deep peak-load capability," Energy, Elsevier, vol. 295(C).
    2. Wang, Wei & Liu, Jizhen & Zeng, Deliang & Niu, Yuguang & Cui, Can, 2015. "An improved coordinated control strategy for boiler-turbine units supplemented by cold source flow adjustment," Energy, Elsevier, vol. 88(C), pages 927-934.
    3. Yao, Lingxiang & Xiao, Xianyong & Wang, Yang & Yao, Xiaoming & Ma, Zhicheng, 2022. "Dynamic modeling and hierarchical control of a concentrated solar power plant with direct molten salt storage," Energy, Elsevier, vol. 252(C).
    4. Wang, Congyu & Chen, Fangfang & Xu, Pengjiang & Cao, Hongmei & Wang, Wei & Sun, Qie, 2025. "Dynamic simulation of a subcritical coal-fired power plant with the emphasis on flexibility," Applied Energy, Elsevier, vol. 392(C).
    5. Yang, Tingting & Liu, Ziyuan & Zeng, Deliang & Zhu, Yansong, 2023. "Simulation and evaluation of flexible enhancement of thermal power unit coupled with flywheel energy storage array," Energy, Elsevier, vol. 281(C).
    6. Wang, Huijie & Qiu, Baoyun & Zhao, Fangling & Yan, Tianxu, 2023. "Method for increasing net power of power plant based on operation optimization of circulating cooling water system," Energy, Elsevier, vol. 282(C).
    7. Wang, Wei & Liu, Jizhen & Zeng, Deliang & Lin, Zhongwei & Cui, Can, 2012. "Variable-speed technology used in power plants for better plant economics and grid stability," Energy, Elsevier, vol. 45(1), pages 588-594.
    8. Han, Zhonghe & Xiang, Peng, 2020. "Modeling condensate throttling to improve the load change performance of cogeneration units," Energy, Elsevier, vol. 192(C).
    9. Wang, Wei & Zeng, Deliang & Liu, Jizhen & Niu, Yuguang & Cui, Can, 2014. "Feasibility analysis of changing turbine load in power plants using continuous condenser pressure adjustment," Energy, Elsevier, vol. 64(C), pages 533-540.
    10. Zhang, Kezhen & Zhao, Yongliang & Liu, Ming & Gao, Lin & Fu, Yue & Yan, Junjie, 2021. "Flexibility enhancement versus thermal efficiency of coal-fired power units during the condensate throttling processes," Energy, Elsevier, vol. 218(C).
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