A review on the selected applications of forecasting models in renewable power systems
This paper presents a literature review on the selected applications of renewable resource
and power forecasting models to facilitate the optimal integration of renewable energy (RE) …
and power forecasting models to facilitate the optimal integration of renewable energy (RE) …
Balancing power and variable renewables: Three links
L Hirth, I Ziegenhagen - Renewable and Sustainable Energy Reviews, 2015 - Elsevier
Balancing power is used to quickly restore the supply-demand balance in power systems.
The need for this tends to be increased by the use of variable renewable energy sources …
The need for this tends to be increased by the use of variable renewable energy sources …
Deep concatenated residual network with bidirectional LSTM for one-hour-ahead wind power forecasting
This paper presents a deep residual network for improving time-series forecasting models,
indispensable to reliable and economical power grid operations, especially with high shares …
indispensable to reliable and economical power grid operations, especially with high shares …
[HTML][HTML] Advances in solar forecasting: Computer vision with deep learning
Renewable energy forecasting is crucial for integrating variable energy sources into the grid.
It allows power systems to address the intermittency of the energy supply at different …
It allows power systems to address the intermittency of the energy supply at different …
A review on the integration of probabilistic solar forecasting in power systems
As one of the fastest growing renewable energy sources, the integration of solar power
poses great challenges to power systems due to its variable and uncertain nature. As an …
poses great challenges to power systems due to its variable and uncertain nature. As an …
Prediction interval of wind power using parameter optimized Beta distribution based LSTM model
X Yuan, C Chen, M Jiang, Y Yuan - Applied Soft Computing, 2019 - Elsevier
Prediction interval of wind power (PIWP) is crucial to assessing the economic and safe
operation of the wind turbine and providing support for analysis of the stability of power …
operation of the wind turbine and providing support for analysis of the stability of power …
Operating reserve quantification using prediction intervals of wind power: An integrated probabilistic forecasting and decision methodology
Adequate reserves are urgently needed to hedge against wind power forecasting
uncertainties in power systems. Traditional reserve quantification sequentially acquires …
uncertainties in power systems. Traditional reserve quantification sequentially acquires …
Deterministic and probabilistic wind power forecasting using a variational Bayesian-based adaptive robust multi-kernel regression model
Accurate wind power forecasting has great practical significance for the safe and
economical operation of power systems. In reality, wind power data are recorded at high …
economical operation of power systems. In reality, wind power data are recorded at high …
Short-term wind speed or power forecasting with heteroscedastic support vector regression
Q Hu, S Zhang, M Yu, Z **e - IEEE Transactions on Sustainable …, 2015 - ieeexplore.ieee.org
Wind speed or wind power forecasting plays an important role in large-scale wind power
penetration due to their uncertainty. Support vector regression, widely used in wind speed or …
penetration due to their uncertainty. Support vector regression, widely used in wind speed or …
Ensemble deep learning-based non-crossing quantile regression for nonparametric probabilistic forecasting of wind power generation
W Cui, C Wan, Y Song - IEEE Transactions on Power Systems, 2022 - ieeexplore.ieee.org
Probabilistic forecasting that quantifies the prediction uncertainties is crucial for decision-
making in power systems. As a prevalent nonparametric probabilistic forecasting approach …
making in power systems. As a prevalent nonparametric probabilistic forecasting approach …