Research on boiler combustion optimization based on CSVR algorithm

Changhuan Tu

doi:10.1117/12.2653170

20 October 2022 Research on boiler combustion optimization based on CSVR algorithm

Changhuan Tu

Proceedings Volume 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022); 123500F (2022) https://doi.org/10.1117/12.2653170
Event: 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 2022, Qingdao, China

Abstract

With the increasing demand for electricity and more stringent requirements for electrical protection and environmental protection, the overall efficiency of coal-fired units needs to be improved rapidly. The pan optimization technology can be divided into two parts: the establishment of an accurate pan prediction model and the multi-objective optimization method. According to the speed and accuracy of data modeling and optimization method results, and based on the prepared samples, the design of the CSVR (Constraint Support Vector Regression) algorithm for high NO2 emission atomization and NO2 extraction efficiency optimization can obtain the optimal solution. The experimental method is mainly to preprocess the input data, then model and set the parameters. Finally, the CSVR algorithm is compared with the LSSVR algorithm, and it is concluded that the CSVR algorithm has the highest modeling accuracy, and at the same time, it can further improve the efficiency of boiler combustion. But the CSVR algorithm can extract as many possible solutions as possible in one operation. It can reflect the different changes of the same degradation corresponding to the difference of NOx observed after optimization, and provide different optimization references for operators.

Citation Download Citation

Changhuan Tu "Research on boiler combustion optimization based on CSVR algorithm", Proc. SPIE 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 123500F (20 October 2022); https://doi.org/10.1117/12.2653170

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KEYWORDS

Data modeling

NOx

Optimization (mathematics)

Combustion

Error analysis

Atmospheric modeling

Nitrogen dioxide

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