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Backstepping-based nonlinear adaptive control for coal-fired utility boiler-turbine units

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  • Fang, Fang
  • Wei, Le

Abstract

The control system of boiler-turbine unit plays an important role in improving efficiency and reducing emissions of power generation unit. The nonlinear, coupling and uncertainty of the unit caused by varying working conditions should be fully considered during the control system design. This paper presents an efficient control scheme based on backstepping theory for improving load adaptability of boiler-turbines in wide operation range. The design process of the scheme includes model preprocessing, control Lyapunov functions selection, interlaced computation of adaptive control laws, etc. For simplification and accuracy, differential of steam pipe inlet pressure and integral terms of target errors are adopted. Also, to enhance practicality, implementation steps of the scheme are proposed. A practical nonlinear model of a 500Â MW coal-fired boiler-turbine unit is used to test the efficiency of the proposed scheme in different conditions.

Suggested Citation

  • Fang, Fang & Wei, Le, 2011. "Backstepping-based nonlinear adaptive control for coal-fired utility boiler-turbine units," Applied Energy, Elsevier, vol. 88(3), pages 814-824, March.
    • Handle: RePEc:eee:appene:v:88:y:2011:i:3:p:814-824
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    1. Huang, Bin & Xu, Shisen & Gao, Shiwang & Liu, Lianbo & Tao, Jiye & Niu, Hongwei & Cai, Ming & Cheng, Jian, 2010. "Industrial test and techno-economic analysis of CO2 capture in Huaneng Beijing coal-fired power station," Applied Energy, Elsevier, vol. 87(11), pages 3347-3354, November.
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    Cited by:

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    2. Hong, Feng & Ji, Weiming & Pang, Yalei & Hao, Junhong & Du, Ming & Fang, Fang & Liu, Jizhen, 2023. "A new energy state-based modeling and performance assessment method for primary frequency control of thermal power plants," Energy, Elsevier, vol. 276(C).
    3. Shi, Yan & Zhong, Wenqi & Chen, Xi & Yu, A.B. & Li, Jie, 2019. "Combustion optimization of ultra supercritical boiler based on artificial intelligence," Energy, Elsevier, vol. 170(C), pages 804-817.
    4. Ghabraei, Soheil & Moradi, Hamed & Vossoughi, Gholamreza, 2018. "Design & application of adaptive variable structure &H∞ robust optimal schemes in nonlinear control of boiler-turbine unit in the presence of various uncertainties," Energy, Elsevier, vol. 142(C), pages 1040-1056.
    5. Zhang, Jianhua & Zhou, Yeli & Li, Ying & Hou, Guolian & Fang, Fang, 2013. "Generalized predictive control applied in waste heat recovery power plants," Applied Energy, Elsevier, vol. 102(C), pages 320-326.
    6. Sun, Li & Hua, Qingsong & Shen, Jiong & Xue, Yali & Li, Donghai & Lee, Kwang Y., 2017. "Multi-objective optimization for advanced superheater steam temperature control in a 300MW power plant," Applied Energy, Elsevier, vol. 208(C), pages 592-606.
    7. Gang Zhao & Yuge Sun & Zhi-Gang Su & Yongsheng Hao, 2023. "Receding Galerkin Optimal Control with High-Order Sliding Mode Disturbance Observer for a Boiler-Turbine Unit," Sustainability, MDPI, vol. 15(13), pages 1-19, June.
    8. Yong-Sheng Hao & Zhuo Chen & Li Sun & Junyu Liang & Hongxia Zhu, 2020. "Multi-Objective Intelligent Optimization of Superheated Steam Temperature Control Based on Cascaded Disturbance Observer," Sustainability, MDPI, vol. 12(19), pages 1-24, October.

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