Application of Prediction Algorithm of Photovoltaic Power in Distributed Photovoltaic Volatility Control

Abstract:

For the uncertain characteristics of output power of distributed Photovoltaic (PV), the energy storage device is used to make up the error, between the predicted output and the actual output, to achieve the volatility control of PV power system. This paper presents that the application of support vector machine (SVM) in the power output forecasting of PV volatility control. Based on the complex and non-linear of the factor affecting the PV output, it points the non-linear relationship between the influencing factors and predicted values, and it establishes the SVM regression model of the PV system. Meanwhile, combined with the historical data of the PV operation, it gives the predictive values. Both theoretical analyses and calculation examples show that this method is simple, with high precision, and it is more suitable to the PV output volatility control.

• Periodical: Advanced Materials Research (Volumes 724-725)
• Pages: 22-26
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.724-725.22
• Online since: August 2013
• Authors: Hong Xia Xiao, Hong Chen, Hua Mo
• Keywords: Fluctuation, Photovoltaic Generation, Predictive Algorithm, Support Vector Machine (SVM)

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