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      • An Output Power Prediction Method for Multiple Wind Farms under Energy Internet Environment

        Jianlou Lou,Hui Cao,Bin Song,Jizhe Xiao 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.11

        Traditional wind power prediction is only applicable to a single wind farm. Aim at this isolated prediction method. In this paper, combing with the information sharing and Interconnection mechanism of energy Internet, we propose an output power prediction method for multiple wind farms based on DBPSO-LSSVM model. Firstly, collect SCADA data of multiple wind farms in different areas. Secondly, delete outliers of different farms based on DBSCAN algorithm and select multiple wind fields training samples. And searching the optimal input parameters of LSSVM based on particle swarm algorithm to construct every wind farm model. Thirdly, predict multiple wind fields power combined with numerical weather prediction system. The method we propose can be used to make the scheduling plan in advance to solve a large number of abandoned wind power rationing problem every year. In experiment, the method we propose has the lowest error rate compares to LSSVM and BP-neural network. It’s more suitable to predict wind fields in different areas.

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