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Demand and residual demand modelling using quantile regression

机译:使用分位数回归的需求和剩余需求建模

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Residual demand, the difference between demand and solar and wind production, is an important variable in predicting the future price and storage requirements. However, little is known about predicting the residual demand itself as well as its quantiles. Therefore, we model both demand and residual demand using both ordinary and quantile regression and compare the results for the hourly electricity consumption in Germany. We find that the residual demand is less predictable than demand. The effect is visible for all hours, and is higher for the lower than the upper quantiles.
机译:剩余需求(需求与太阳能和风能生产之间的差异)是预测未来价格和存储需求的重要变量。但是,对于预测剩余需求本身及其分位数的了解很少。因此,我们使用普通回归和分位数回归对需求和剩余需求建模,并比较德国每小时的用电量结果。我们发现剩余需求比需求难以预测。该效果在所有小时内都是可见的,对于较低的分位数比较高的分位数更高。

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