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Probabilistic forecasting of power system imbalance using neural network-based ensembles
Each minute, our model predicts the imbalance of the current and upcoming two quarter-hours, along with uncertainty estimations on these forecasts.
Transfer Learning in Transformer-Based Demand Forecasting For Home Energy Management System
Specifically, we train an advanced forecasting model (a temporal fusion transformer) using data from multiple different households, and then finetune this global model on a new household with limited data (i. e. only a few days).
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