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Comments on: Space-time wind speed forecasting for improved power system dispatch

机译:评论:时空风速预测,以改善电力系统调度

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This paper contains a number of interesting ideas and we are grateful for the opportunity to comment on it. It is particularly pleasing to see that the authors have included a comparison of the forecasting methods under a realistic power system economic dispatch model. As the authors discuss, the loss function associated with the economic dispatch model is asymmetric, in that over-forecasting the realized wind power production requires deployment of additional reserve capacity, while the consequences of under-forecasting are minimal for the overall power system. The rotating regime-switching space-time diurnal (RRSTD) model and the autoregressive reference model are both inherently probabilistic in nature and can return full predictive distributions. Given the asymmetry of the loss function, it is likely that the optimal point forecast derived from a predictive distribution diverges from the center of the distribution (Gneiting, 2011). The authors partially account for this by employing the over-forecasting errors only in the reserve requirement component of the economic dispatch model. Furthermore, an inflation factor of 1.2 is used as a reliability margin. While this solution appears to work well in practice, we wonder if an additional economic gain could be achieved by fully utilizing the probabilistic properties of the RRSTD model in conjunction with the statistical properties of the loss function under the economic dispatch model.
机译:本文包含许多有趣的想法,我们很高兴有机会对此发表评论。特别令人高兴的是,作者对现实的电力系统经济调度模型下的预测方法进行了比较。正如作者所讨论的那样,与经济调度模型相关的损失函数是不对称的,因为过度预测已实现的风力发电需要部署额外的备用容量,而对于整个电力系统而言,预测不足的后果则很小。旋转政权切换时空模型(RRSTD)和自回归参考模型本质上都是内在的概率,并且可以返回完整的预测分布。考虑到损失函数的不对称性,从预测分布得出的最优点预测可能会偏离分布中心(Gneiting,2011)。作者仅通过在经济调度模型的准备金要求部分中采用了过度预测的错误来部分解决此问题。此外,将膨胀系数1.2用作可靠性裕度。尽管此解决方案在实践中似乎运作良好,但我们想知道是否可以通过充分利用RRSTD模型的概率属性以及经济调度模型下的损失函数的统计属性来实现额外的经济收益。

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