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Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts

Grzegorz Marcjasz, Bartosz Uniejewski, Rafał Weron

2020Energies43 citationsDOIOpen Access PDF

Abstract

In the last three decades the vast majority of electricity price forecasting (EPF) research has concerned day-ahead markets. However, the rapid expansion of renewable generation—mostly wind and solar—have shifted the focus to intraday markets, which can be used to balance the deviations between positions taken in the day-ahead market and the actual demand and renewable generation. A recent EPF study claims that the German intraday, continuous-time market for hourly products is weak-form efficient, that is, that the best predictor for the so-called ID3-Price index is the most recent transaction price. Here, we undermine this claim and show that we can beat the naïve forecast by combining it with a prediction of a parameter-rich model estimated using the least absolute shrinkage and selection operator (LASSO). We further argue, that that if augmented with timely predictions of fundamental variables for the coming hours, the LASSO-estimated model itself can significantly outperform the naïve forecast.

Topics & Concepts

Lasso (programming language)EconometricsEconomicsElectricity marketElectricity price forecastingRenewable energyElectricityComputer scienceEngineeringWorld Wide WebElectrical engineeringEnergy Load and Power ForecastingElectric Power System OptimizationEnergy Efficiency and Management
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