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《Proceedings of the CSEE》 2006-07
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Modeling Research of the Reheat Steam Temperature of 300 MW Boiler Based on Support Vector Regression

HUANG Jing-tao1, MA Long-hua1, MAO Jian-bo2, QIAN Ji-xin1 (1. National Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, Zhejiang Province, China; 2. Zhejiang Electric Power Test & Research Institute, Hangzhou 310014, Zhejiang Province, China)  
To solve the problem of reheat steam temperature (RST) abnormal of the 300MW power station boiler unit, a method based on support vector regression (SVR) was presented to model RST. Based on the data sampled on spot, RST was analyzed using support vector regression method. RST model is based on the statistical characteristics of the operating parameters and can reflect the potential relationship between RST and the operating parameters. For the units considered here, the RST is low and the temperature of reheater tube wall is high, tilt angles and desupreheater spray, etc. were taken as the tuning parameters and as the features of SVR model. The prediction results on test data with SVR-RST show high regression coefficient with low complexity, which means SVR-RST model has excellent robustness, which is important to further optimize the operating parameters for higher efficiency and security.
【Fund】: 国家自然科学基金项目(60474064);; 国家“973”重点基础研究发展规划项目(2002CB312200)。~~
【CateGory Index】: TM621.2
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