Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting
Solar and wind energy are inherently time-varying sources of energy on scales from minutes
to seasons. Thus, the incorporation of such intermittent and stochastic renewable energy …
to seasons. Thus, the incorporation of such intermittent and stochastic renewable energy …
PV power forecasting based on data-driven models: a review
Accurate PV power forecasting techniques are a prerequisite for the optimal management of
the grid and its stability. This paper presents a review of the recent developments in the field …
the grid and its stability. This paper presents a review of the recent developments in the field …
[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 …
Solar radiation forecasting using artificial neural network and random forest methods: Application to normal beam, horizontal diffuse and global components
Three methods, smart persistence, artificial neural network and random forest, are compared
to forecast the three components of solar irradiation (global horizontal, beam normal and …
to forecast the three components of solar irradiation (global horizontal, beam normal and …
Forecasting solar power using long-short term memory and convolutional neural networks
As solar photovoltaic (PV) generation becomes cost-effective, solar power comes into its
own as the alternative energy with the potential to make up a larger share of growing energy …
own as the alternative energy with the potential to make up a larger share of growing energy …
Systematic review on impact of different irradiance forecasting techniques for solar energy prediction
K Sudharshan, C Naveen, P Vishnuram… - Energies, 2022 - mdpi.com
As non-renewable energy sources are in the verge of exhaustion, the entire world turns
towards renewable sources to fill its energy demand. In the near future, solar energy will be …
towards renewable sources to fill its energy demand. In the near future, solar energy will be …
Hybrid convolutional neural network-multilayer perceptron model for solar radiation prediction
Urgent transition from the dependence on fossil fuels towards renewable energies requires
more solar photovoltaic power to be connected to the electricity grids, with reliable supply …
more solar photovoltaic power to be connected to the electricity grids, with reliable supply …
Solar and wind power generation forecasts using elastic net in time-varying forecast combinations
D Nikodinoska, M Käso, F Müsgens - Applied Energy, 2022 - Elsevier
Precise renewable energy feed-in forecasts are essential for an effective and efficient
integration of renewables into energy systems, and research contributions that help to …
integration of renewables into energy systems, and research contributions that help to …
[HTML][HTML] Rolling-horizon optimization integrated with recurrent neural network-driven forecasting for residential battery energy storage operations
In recent years, the installation of battery energy storage (BES) integrated with solar
photovoltaic (PV) panels in residential houses has been rapidly accelerated tied to the high …
photovoltaic (PV) panels in residential houses has been rapidly accelerated tied to the high …
The cost of day-ahead solar forecasting errors in the United States
As solar energy contributes an increasing share of total electricity generation, solar
forecasting errors become important relative to overall load uncertainty and can add costs to …
forecasting errors become important relative to overall load uncertainty and can add costs to …