Post-processing in solar forecasting: Ten overarching thinking tools
D Yang, D van der Meer - Renewable and Sustainable Energy Reviews, 2021 - Elsevier
Forecasts are always wrong, otherwise, they are merely deterministic calculations. Besides
leveraging advanced forecasting methods, post-processing has become a standard practice …
leveraging advanced forecasting methods, post-processing has become a standard practice …
Operational solar forecasting for grid integration: Standards, challenges, and outlook
The interactions between solar forecasting strategies and grid codes have a profound
impact on grid integration. In order to develop grid-integration standards, such as the …
impact on grid integration. In order to develop grid-integration standards, such as the …
[HTML][HTML] Probabilistic solar forecasting: Benchmarks, post-processing, verification
Probabilistic solar forecasts may take the form of predictive probability distributions,
ensembles, quantiles, or interval forecasts. State-of-the-art approaches build on input from …
ensembles, quantiles, or interval forecasts. State-of-the-art approaches build on input from …
An archived dataset from the ECMWF Ensemble Prediction System for probabilistic solar power forecasting
Ensemble numerical weather prediction (NWP) is the backbone of the state-of-the-art solar
forecasting for horizons ranging between a few hours and a few days. Dynamical ensemble …
forecasting for horizons ranging between a few hours and a few days. Dynamical ensemble …
Verifying operational intra-day solar forecasts from ECMWF and NOAA
Global horizontal irradiance (GHI) forecasting at intra-day horizons of up to 12-h ahead is
vital to grid integration of solar photovoltaics, but has been fundamentally difficult for all …
vital to grid integration of solar photovoltaics, but has been fundamentally difficult for all …
[HTML][HTML] Post-processing numerical weather prediction ensembles for probabilistic solar irradiance forecasting
In order to enable the transition towards renewable energy sources, probabilistic energy
forecasting is of critical importance for incorporating volatile power sources such as solar …
forecasting is of critical importance for incorporating volatile power sources such as solar …
Ensemble solar forecasting and post-processing using dropout neural network and information from neighboring satellite pixels
Ensemble weather forecasts are often found to be under-dispersed and biased. Post-
processing using spatio-temporal information is, therefore, required if one wishes to improve …
processing using spatio-temporal information is, therefore, required if one wishes to improve …
Parametric probabilistic forecasting of solar power with fat-tailed distributions and deep neural networks
F Lin, Y Zhang, K Wang, J Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The need of solar power uncertainty quantification in the power system has inspired
probabilistic solar power forecasting. This paper proposes a novel multi-step parametric …
probabilistic solar power forecasting. This paper proposes a novel multi-step parametric …
Non-crossing quantile regression neural network as a calibration tool for ensemble weather forecasts
Despite the maturity of ensemble numerical weather prediction (NWP), the resulting
forecasts are still, more often than not, under-dispersed. As such, forecast calibration tools …
forecasts are still, more often than not, under-dispersed. As such, forecast calibration tools …
Forecasting high penetration of solar and wind power in the smart grid environment using robust ensemble learning approach for large-dimensional data
Forecasting enables the cost-effective integration of renewable energy sources such as
solar and wind. Forecasting daily, monthly, seasonal, and annual data for different locations …
solar and wind. Forecasting daily, monthly, seasonal, and annual data for different locations …