基于沿海风力发电场风机输出功率预测的分类算法对比

Comparative Study of Coastal Wind Farm Wind Turbine Output Power Prediction Classification Algorithm

介绍了风力发电场风机输出功率预测的相关背景和研究意义,应用数据挖掘中的经典M5P算法和改进的M5P分类算法对风力发电机输出功率预测进行归纳、对比和分析.首先,对原始数据进行预处理,去除无效数据,以提高实验精确度和效率;然后,采用上述两种算法进行数据处理;最后,验证了改进的M5P算法对风机输出功率预测的高效性和准确性.

The background and significance of the research of wind load forecasting are introduced, the main application of data mining in the typical MSP and the modified MSP classification algorithm on the wind field of short-term load forecasting are summarized, compared and analyzed. After pretreatment of the original data are removed, the invalid data are removed so as to improve the accuracy and efficiency. Then,two kinds of algorithms are used for data processing,the load forecasting of load forecasting. Finally, it is verified that the improved algorithm MSP has more efficiency and accuracy in predicting wind turbine output power.