[HTML][HTML] Comparison of machine learning methods for photovoltaic power forecasting based on numerical weather prediction
D Markovics, MJ Mayer - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
The increase of the worldwide installed photovoltaic (PV) capacity and the intermittent
nature of the solar resource highlights the importance of power forecasting for the grid …
nature of the solar resource highlights the importance of power forecasting for the grid …
A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality
The ability to forecast solar irradiance plays an indispensable role in solar power
forecasting, which constitutes an essential step in planning and operating power systems …
forecasting, which constitutes an essential step in planning and operating power systems …
Review and prospect of data-driven techniques for load forecasting in integrated energy systems
With synergies among multiple energy sectors, integrated energy systems (IESs) have been
recognized lately as an effective approach to accommodate large-scale renewables and …
recognized lately as an effective approach to accommodate large-scale renewables and …
Long sequence time-series forecasting with deep learning: A survey
The development of deep learning technology has brought great improvements to the field
of time series forecasting. Short sequence time-series forecasting no longer satisfies the …
of time series forecasting. Short sequence time-series forecasting no longer satisfies the …
A review of very short-term wind and solar power forecasting
R Tawn, J Browell - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Installed capacities of wind and solar power have grown rapidly over recent years, and the
pool of literature on very short-term (minutes-to hours-ahead) wind and solar forecasting has …
pool of literature on very short-term (minutes-to hours-ahead) wind and solar forecasting has …
[HTML][HTML] Forecasting: theory and practice
Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …
uncertainty that surrounds the future is both exciting and challenging, with individuals and …
[HTML][HTML] Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark
While the field of electricity price forecasting has benefited from plenty of contributions in the
last two decades, it arguably lacks a rigorous approach to evaluating new predictive …
last two decades, it arguably lacks a rigorous approach to evaluating new predictive …
Electricity price forecasting on the day-ahead market using machine learning
The price of electricity on the European market is very volatile. This is due both to its mode of
production by different sources, each with its own constraints (volume of production …
production by different sources, each with its own constraints (volume of production …
[HTML][HTML] The M4 Competition: 100,000 time series and 61 forecasting methods
The M4 Competition follows on from the three previous M competitions, the purpose of which
was to learn from empirical evidence both how to improve the forecasting accuracy and how …
was to learn from empirical evidence both how to improve the forecasting accuracy and how …
Short-term load forecasting based on LSTM networks considering attention mechanism
J Lin, J Ma, J Zhu, Y Cui - International Journal of Electrical Power & Energy …, 2022 - Elsevier
Reliable and accurate zonal electricity load forecasting is essential for power system
operation and planning. Probabilistic load forecasts can present more comprehensive …
operation and planning. Probabilistic load forecasts can present more comprehensive …