Comparing the forecasting performances of linear models for electricity prices with high RES penetration

Angelica Gianfreda, Francesco Ravazzolo and Luca Rossini

International Journal of Forecasting, 2020, vol. 36, issue 3, 974-986

Abstract: We compare alternative univariate versus multivariate models and frequentist versus Bayesian autoregressive and vector autoregressive specifications for hourly day-ahead electricity prices, both with and without renewable energy sources. The accuracy of point and density forecasts is inspected in four main European markets (Germany, Denmark, Italy, and Spain) characterized by different levels of renewable energy power generation. Our results show that the Bayesian vector autoregressive specifications with exogenous variables dominate other multivariate and univariate specifications in terms of both point forecasting and density forecasting.

Keywords: Point and density forecasting; Electricity markets; Hourly prices; Renewable energy sources; Demand; Fossil fuels (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (34)

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Related works:
Working Paper: Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration (2019)
Working Paper: Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:36:y:2020:i:3:p:974-986

DOI: 10.1016/j.ijforecast.2019.11.002

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