Til hovedinnhold

Combining Machine Learning and Optimization for Efficient Price Forecasting

Combining Machine Learning and Optimization for Efficient Price Forecasting

Kategori
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
Sammendrag
We present a framework based on machine learning for reducing the problem size of a short-term hydrothermal scheduling optimization model applied for price forecasting. The general idea is to reduce the optimization problem dimensions by finding patterns in input data, and without compromising the solution quality. The framework was tested on a data description of the Northern European power system, demonstrating significant reductions in computation times.
Oppdragsgiver
  • Research Council of Norway (RCN) / 268014
Språk
Engelsk
Forfatter(e)
Institusjon(er)
  • SINTEF Energi AS / Energisystemer
  • Norges miljø- og biovitenskapelige universitet
År
2020
Forlag
IEEE
Bok
2020 17th International Conference on the European Energy Market - EEM
Hefte nr.
2020
ISBN
978-1-7281-6919-4