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Electricity Price Forecasting: The Dawn of Machine Learning.

Authors :
Jedrzejewski, Arkadiusz
Lago, Jesus
Marcjasz, Grzegorz
Weron, Rafal
Source :
IEEE Power & Energy Magazine; 2022, Vol. 20 Issue 3, p24-31, 8p
Publication Year :
2022

Abstract

Electricity Price Forecasting (EPF) IS A branch of forecasting at the interface of electrical engineering, statistics, computer science, and finance that focuses on predicting prices in wholesale electricity markets for a whole spectrum of horizons. These range from a few minutes (real-time/intraday auctions and continuous trading); through days (day-ahead [DA] auctions); to weeks, months, or even years (exchange and over-the-counter traded futures and forward contracts). DA markets are the workhorse of power trading, particularly in Europe, and a commonly used proxy for “the electricity price.” The vast majority—up to 90%—of the EPF literature has focused on predicting DA prices. These are typically determined around noon during 24 uniform-price auctions, one for each hour of the next day. This has direct implications for the way EPF models are built. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15407977
Volume :
20
Issue :
3
Database :
Complementary Index
Journal :
IEEE Power & Energy Magazine
Publication Type :
Academic Journal
Accession number :
156497136
Full Text :
https://doi.org/10.1109/MPE.2022.3150809