Prediction of Superheater Tube Wall Temperature in Supercritical/Ultra-Supercritical Boilers for Different Loading

doi:10.11930/j.issn.1004-9649.201711189

Abstract

Abstract: In this paper, the influencing factors of the superheater wall temperature in supercritical/ultra-supercritical boilers are analyzed. By using the real-time operation data acquired from the DCS system in a power plant,the grey relational analysis on the measured temperature of the superheater tubes is conducted to determine the input variables of the prediction model. The results show that the influencing factors, such as the outlet steam temperature of both the primary and secondary superheaters, the main steam temperature,the layer E opening of secondary air throttles and the active power are vital to the tube wall temperature. Then by using the BP neural network algorithm, 14 main influencing factors with the threshold of more than 0.70 are used to predict the tube wall temperature at the scenario of up loading, steady loading and down loading,which concludes that the development trend of the prediction results is consistent with that of the measured results, and the largest relative error is about 1.42%. The prediction results can provide good guideline to avoid overheating.

Key words: supercritical/ultral-supercritical boiler, superheater, tube wall temperature, grey relational analysis, BP neural network

CLC Number:

TP391.9

DENG Bo, XU Hong, GUO Peng, ZHANG Naiqiang, NI Yongzhong. Prediction of Superheater Tube Wall Temperature in Supercritical/Ultra-Supercritical Boilers for Different Loading[J]. Electric Power, 2018, 51(3): 13-20.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.201711189

https://www.electricpower.com.cn/EN/Y2018/V51/I3/13

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