Novel machine learning methods to enhance wind power probabilistic forecasting: SPinHy-NN framework proposal for European electricity markets

The increasing penetration of weather-dependent energy sources brings additional challenges to the operation of the power system. Wind power forecasting is a valuable resource for these power operators: a tool that aids the decision-making process and facilitates risk management. On the other hand, the progress of machine learning and their...

Day-ahead Wind Power Predictions at Regional Scales: Post-processing Operational Weather Forecasts with a Hybrid Neural Network

A hybrid neural network model, comprising of a convolutional neural network and a multilayer perceptron network, has been developed for day-ahead forecasting of regional scale wind power production. This model requires operational weather forecasts as input and also has the capability to ingest data from ensemble forecasts. Even though the...