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 …
Review on photovoltaic power and solar resource forecasting: current status and trends
TC Carneiro, PCM de Carvalho… - Journal of Solar …, 2022 - asmedigitalcollection.asme.org
Photovoltaic (PV) power intermittence impacts electrical grid security and operation. Precise
PV power and solar irradiation forecasts have been investigated as significant reducers of …
PV power and solar irradiation forecasts have been investigated as significant reducers of …
Short-term wind power prediction based on EEMD–LASSO–QRNN model
Y He, Y Wang - Applied Soft Computing, 2021 - Elsevier
With the increasing utilization of wind generation in power system, the improvement of wind
power forecasting precision is attached vital importance. Owing to the stochastic and …
power forecasting precision is attached vital importance. Owing to the stochastic and …
Design and simulation of the PV/PEM fuel cell based hybrid energy system using MATLAB/Simulink for greenhouse application
C Ceylan, Y Devrim - International Journal of Hydrogen Energy, 2021 - Elsevier
In this study, design and optimization of the hybrid renewable energy system consisting of
Photovoltaic (PV)/Electrolyzer/Proton Exchange Membrane Fuel Cell (PEMFC) was …
Photovoltaic (PV)/Electrolyzer/Proton Exchange Membrane Fuel Cell (PEMFC) was …
A guideline to solar forecasting research practice: Reproducible, operational, probabilistic or physically-based, ensemble, and skill (ROPES)
D Yang - Journal of Renewable and Sustainable Energy, 2019 - pubs.aip.org
Over the past decade, significant progress in solar forecasting has been made.
Nevertheless, there are concerns about duplication, long-term value, and reproducibility; this …
Nevertheless, there are concerns about duplication, long-term value, and reproducibility; this …
A multi-step probability density prediction model based on gaussian approximation of quantiles for offshore wind power
W Zhang, Y He, S Yang - Renewable Energy, 2023 - Elsevier
With the increasing utilization of offshore wind power, accurate prediction of offshore wind
power is crucial for preventive control and scheduling. In this paper, a new hybrid probability …
power is crucial for preventive control and scheduling. In this paper, a new hybrid probability …
[HTML][HTML] Comparison of statistical post-processing methods for probabilistic NWP forecasts of solar radiation
The increased usage of solar energy places additional importance on forecasts of solar
radiation. Solar panel power production is primarily driven by the amount of solar radiation …
radiation. Solar panel power production is primarily driven by the amount of solar radiation …
Short-term power load probability density forecasting based on GLRQ-Stacking ensemble learning method
Y He, J Xiao, X An, C Cao, J Xiao - … Journal of Electrical Power & Energy …, 2022 - Elsevier
The high penetration rate of distributed energy brings severe challenges to the dispatch and
operation of power systems. Improving the accuracy of short-term power load forecasting …
operation of power systems. Improving the accuracy of short-term power load forecasting …
Multi-distribution ensemble probabilistic wind power forecasting
Ensemble methods have shown to be able to improve the performance of deterministic wind
forecasting. In this paper, an improved multi-distribution ensemble (MDE) probabilistic wind …
forecasting. In this paper, an improved multi-distribution ensemble (MDE) probabilistic wind …
Forecasting COVID-19 recovered cases with Artificial Neural Networks to enable designing an effective blood supply chain
This study introduces a forecasting model to help design an effective blood supply chain
mechanism for tackling the COVID-19 pandemic. In doing so, first, the number of people …
mechanism for tackling the COVID-19 pandemic. In doing so, first, the number of people …