Load Forecasting of Coal-Fired Unit Based on SVM Model

Wei Liang Liu; Yong Guang Ma; Liang Yu Ma; Yong Jun Lin; Shuang Sai Liu

doi:10.4028/www.scientific.net/AMR.466-467.1015

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 466-467Load Forecasting of Coal-Fired Unit Based on SVM...

Load Forecasting of Coal-Fired Unit Based on SVM Model

Abstract:

In order to obtain accurate load forecasting of coal-fired unit, a new algorithm based on Support Vector Machine (SVM) method is presented. This algorithm establishes a model to reflect the complicated relation between the load of coal-fired unit and the furnace flame Images. The trained SVM model is applied to a 660MW coal-fired unit to forecast the load with two groups of test samples. The results are compared with that of BP neural network model. It is shown the SVM model is more accurate than the BP NN model. The SVM method can satisfy the demand of engineering applications with the advantages of high forecasting accuracy and more generalized performance.

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Periodical:

Advanced Materials Research (Volumes 466-467)

Pages:

1015-1019

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.466-467.1015

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Online since:

February 2012

Authors:

Wei Liang Liu, Yong Guang Ma, Liang Yu Ma, Yong Jun Lin, Shuang Sai Liu

Keywords:

Flame Images, Load Forecasting, Support Vector Machine (SVM)

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