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USING A NONPARAMETRIC PV MODEL TO FORECAST AC POWER OUTPUT OF PV PLANTS

机译:使用非参数PV模型来预测PV工厂的交流电源输出

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In this paper, a methodology using a nonparametric model is used to forecast AC power output of PV plants using as inputs several forecasts of meteorological variables from a Numerical Weather Prediction (NWP) model and actual AC power measurements of PV plants. The methodology was built upon the R environment and uses Quantile Regression Forests as machine learning tool to forecast the AC power with a confidence interval. Real data from five PV plants was used to validate the methodology, and results show that the daily production of individual plants can be predicted with a skill score up to 0.361.
机译:本文使用非参数模型的方法用于预测PV工厂的AC电力输出,用来自数值天气预报(NWP)模型的多个气象变量预测和PV工厂的实际交流电力测量。该方法建立在R环境之上,并使用量子回归林作为机器学习工具,以预测具有置信区间的交流电源。来自五种光伏植物的真实数据用于验证方法论,结果表明,可以预测各个植物的日常生产,技能得分高达0.361。

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