Less Is More: Data-Driven Day-Ahead Electricity Price Forecasting with Short Training Windows

Volatility in the modern world and electricity Day-Ahead Markets (DAMs) usually makes long-term historical data irrelevant or even detrimental for accurate forecasting. This study directly addresses this challenge by proposing a novel forecasting paradigm centered on extremely short training windows...

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Egile Nagusiak:	Vasilis Michalakopoulos, Christoforos Menos-Aikateriniadis, Elissaios Sarmas, Antonis Zakynthinos, Pavlos S. Georgilakis, Dimitris Askounis
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	MDPI AG 2026-01-01
Saila:	Energies
Gaiak:	electricity price forecasting machine learning day-ahead market shallow training sizes
Sarrera elektronikoa:	https://www.mdpi.com/1996-1073/19/2/376
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