基于数据分层预处理的LSSVM模型风电功率预测

Zhang Wei, Deng Yuan-chang, Wei Zhen
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引用次数: 2

摘要

风速和风电功率预测是解决风电并网问题的关键。无效的样本数据影响风电模型。为了得到风速与风力的关系,采用分层统计的方法对风力曲线进行修正。本文采用最小二乘支持向量机模型对修改后的数据进行预测。为了验证预测效果,采用经验功率曲线法进行比较。结果表明,分层统计方法可以有效地剔除无效数据,提高预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wind power prediction with LSSVM model based on data stratification pretreatment
Wind speed and wind power prediction are the keys to solve the wind power with grid problems. The invalid sample data affects the wind power model. To get the relationships of wind speed and wind power, layered statistics method is used to modify the wind power curve. This paper uses least square support vector machine model to predict the modified data. In order to verify the predicted effect, experienced power curve method is used for comparison. The results show that layered statistics method can eliminate the invalid data effectively and improve the accuracy of the prediction.
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