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Tempospacial energy-saving effect-based diagnosis in large coal-fired power units: Energy-saving benchmark state

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Abstract

The energy-saving analytics of coal-fired power units in China is confronting new challenges especially with even more complicated system structure, higher working medium parameters, time-dependent varying operation conditions and boundaries such as load rate, coal quality, ambient temperature and humidity. Compared with the traditional optimization of specific operating parameters, the idea of the energy-consumption benchmark state was proposed. The equivalent specific fuel consumption (ESFC) analytics was introduced to determine the energy-consumption benchmark state, with the minimum ESFC under varying operation boundaries. Models for the energy-consumption benchmark state were established, and the endogenous additional specific consumption (ASFC) and exogenous ASFC were calculated. By comparing the benchmark state with the actual state, the energy-saving tempospacial effect can be quantified. As a case study, the energy consumption model of a 1000 MW ultra supercritical power unit was built. The results show that system energy consumption can be mainly reduced by improving the performance of turbine subsystem. This nearly doubles the resultant by improving the boiler system. The energy saving effect of each component increases with the decrease of load and has a greater influence under a lower load rate. The heat and mass transfer process takes priority in energy saving diagnosis of related components and processes. This makes great reference for the design and operation optimization of coal-fired power units.

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Authors and Affiliations

  1. National Thermal Power Engineering and Technology Research Center, North China Electric Power University, Beijing, 102206, China

    Peng Fu, NingLing Wang, YongPing Yang, Han Xu, XiaoEn Li & YuMeng Zhang

Authors
  1. Peng Fu
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  2. NingLing Wang
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  3. YongPing Yang
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  4. Han Xu
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  5. XiaoEn Li
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  6. YuMeng Zhang
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Correspondence to YongPing Yang.

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Fu, P., Wang, N., Yang, Y. et al. Tempospacial energy-saving effect-based diagnosis in large coal-fired power units: Energy-saving benchmark state. Sci. China Technol. Sci. 58, 2025–2037 (2015). https://doi.org/10.1007/s11431-015-5879-z

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