Introduced in Prediction of Energy Consumption for Variable Customer Portfolios Including Aleatoric Uncertainty Estimation2021
Predictions of energy consumption are crucial for energy retailers to minimize deviations from energy acquired in the day-ahead market and the actual consumption of their customers. The increasing spread of smartmeters means that retailers have access to hourly consumption values of all their contracted customers in realtime. Using machine learning algorithms, these hourly values can be used to calculate predictions for the future energy consumption of the customers. The present data set allows the training and validation of AI-based prediction models.
