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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. The RRSTD method predicts the wind speed at the turbine location, which is then subsequently transformed to wind power using the power curve provided by the turbine manufacturer. In a recent paper, Messner et al. (2013) apply wind speed

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