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Found 5 papers, 1 papers with code
AutoPV: Automated photovoltaic forecasts with limited information using an ensemble of pre-trained models
To tackle the problem of missing information about the PV mounting configuration, we use new data that become available during operation to adapt the ensemble weights to minimize the forecasting error.
Review of automated time series forecasting pipelines
We conclude that future research has to holistically consider the automation of the forecasting pipeline to enable the large-scale application of time series forecasting.
Concepts for Automated Machine Learning in Smart Grid Applications
Forecasts are elementary for sector coupling, where energy-consuming sectors are interconnected with the power-generating sector to address electricity storage challenges by adding flexibility to the power system.
pyWATTS: Python Workflow Automation Tool for Time Series
Time series data are fundamental for a variety of applications, ranging from financial markets to energy systems.
Integrating Battery Aging in the Optimization for Bidirectional Charging of Electric Vehicles
Smart charging of Electric Vehicles (EVs) reduces operating costs, allows more sustainable battery usage, and promotes the rise of electric mobility.
