Soft-Sensing Technology in the Combustion Optimization for Power Plant

Bao Ling Liu; Zeng Xuan

doi:10.4028/www.scientific.net/AMR.179-180.859

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 179-180Soft-Sensing Technology in the Combustion...

Soft-Sensing Technology in the Combustion Optimization for Power Plant

Abstract:

Aiming at the requirements of saving energy and reducing emission on power plant, NOx emission model was built by SVM ,an effective learning tool, based on the analysis of the emission characteristics, and ACO was applied to optimize the model parameters. The model was tested on a 660MW power plant ,and the result indicated that SVM was a good tool for building emission model and had better generalization ability and higher calculation speed comparing with BP modeling approaches.

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Periodical:

Advanced Materials Research (Volumes 179-180)

Pages:

859-864

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.179-180.859

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Online since:

January 2011

Authors:

Bao Ling Liu, Zeng Xuan

Keywords:

Ant Colony Optimization (ACO), NO_x Emission, Soft-Sensing, Support Vector Machine (SVM)

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References

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