This page is about the applications of machine learning (ML) in the context of electricity price forecasting. For an overview of electricity price forecasting more generally, please see the Wikipedia page on this topic.
The price of electric energy can be used to influence the utilization of flexibility options. To utilize flexibility more effectively, prices must be forecasted accurately. ML can help make these forecasts more accurate, improve temporal and spatial resolution, and quantify uncertainty.
Background Readings[edit | edit source]
Conferences, Journals, and Professional Organizations[edit | edit source]
Journals[edit | edit source]
- International Journal of Forecasting: The official journal of the International Institute of Forecasters. Journal website here.
Libraries and Tools[edit | edit source]
Data[edit | edit source]
General[edit | edit source]
- See the Electricity Systems page for general electricity systems datasets.