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 …

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 …

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 …

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 …

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 …

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 …

[HTML][HTML] Comparison of statistical post-processing methods for probabilistic NWP forecasts of solar radiation

K Bakker, K Whan, W Knap, M Schmeits - Solar Energy, 2019 - Elsevier
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 …

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 …

Multi-distribution ensemble probabilistic wind power forecasting

M Sun, C Feng, J Zhang - Renewable Energy, 2020 - Elsevier
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 COVID-19 recovered cases with Artificial Neural Networks to enable designing an effective blood supply chain

E Ayyildiz, M Erdogan, A Taskin - Computers in Biology and Medicine, 2021 - Elsevier
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 …