[HTML][HTML] Forecasting solar photovoltaic power production: A comprehensive review and innovative data-driven modeling framework
The intermittent and stochastic nature of Renewable Energy Sources (RESs) necessitates
accurate power production prediction for effective scheduling and grid management. This …
accurate power production prediction for effective scheduling and grid management. This …
[HTML][HTML] The role of energy storage systems for a secure energy supply: A comprehensive review of system needs and technology solutions
The way to produce and use energy is undergoing deep changes with the fast-pace
introduction of renewables and the electrification of transportation and heating systems. As a …
introduction of renewables and the electrification of transportation and heating systems. As a …
[HTML][HTML] Short-term photovoltaic power forecasting using meta-learning and numerical weather prediction independent Long Short-Term Memory models
Short-term photovoltaic (PV) power forecasting is essential for integrating renewable energy
sources into the grid as it provides accurate and timely information on the expected output of …
sources into the grid as it provides accurate and timely information on the expected output of …
[HTML][HTML] Evaluating neural network models in site-specific solar PV forecasting using numerical weather prediction data and weather observations
The effective use of solar photovoltaic (PV) installations implies the integration of solar PV
output into overall energy consumption planning, optimization, and control. Moreover, day …
output into overall energy consumption planning, optimization, and control. Moreover, day …
On the use of probabilistic forecasts in scheduling of renewable energy sources coupled to storages
Electric energy generation from renewable energy sources is generally non-dispatchable
due to its intrinsic volatility. Therefore, its integration into electricity markets and in power …
due to its intrinsic volatility. Therefore, its integration into electricity markets and in power …
A data-driven short-term pv generation and load forecasting approach for microgrid applications
The data-driven (DD) is a systematic approach to improve the data and model by
deriving/adding features to address the problem identified during the iterative loop of …
deriving/adding features to address the problem identified during the iterative loop of …
[HTML][HTML] Data-driven prediction models of photovoltaic energy for smart grid applications
Due to the low total cost of production, photovoltaic energy is a key component of installed
renewable energy worldwide. However, photovoltaic energy is volatile in nature as it …
renewable energy worldwide. However, photovoltaic energy is volatile in nature as it …
Energy forecasting tools and services
The increasing complexity of the power grid and the continuous integration of volatile
renewable energy systems on all aspects of it have made more precise forecasts of both …
renewable energy systems on all aspects of it have made more precise forecasts of both …
Prediction bands for solar energy: New short-term time series forecasting techniques
Short-term forecasts and risk management for photovoltaic energy is studied via a new
standpoint on time series: a result published by P. Cartier and Y. Perrin in 1995 permits …
standpoint on time series: a result published by P. Cartier and Y. Perrin in 1995 permits …
Probabilistic energy forecasting using the nearest neighbors quantile filter and quantile regression
Parametric quantile regression is a useful tool for obtaining probabilistic energy forecasts.
Nonetheless, traditional quantile regressions may be complicated to obtain using complex …
Nonetheless, traditional quantile regressions may be complicated to obtain using complex …