Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration

Angelica Gianfreda, Francesco Ravazzolo and Luca Rossini

No No 2/2018, Working Papers from Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School

Abstract: This paper compares alternative univariate versus multivariate models, probabilistic versus Bayesian autoregressive and vector autoregressive specifications for hourly day-ahead electricity prices, with and without renewable energy sources. The accuracy of point and density forecasts are 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 VAR specifications with exogenous variables dominate other multivariate and univariate specifications, in terms of both point and density forecasting.

Keywords: Density Forecasting; Electricity Market; Forecasting; Hourly Prices; Renewable Energies. (search for similar items in EconPapers)
Pages: 36
Date: 2018-01
New Economics Papers: this item is included in nep-ene, nep-for and nep-reg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://brage.bibsys.no/xmlui/bitstream/handle/112 ... quence=1&isAllowed=y

Related works:
Journal Article: Comparing the forecasting performances of linear models for electricity prices with high RES penetration (2020)
Working Paper: Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bny:wpaper:0060

Access Statistics for this paper

More papers in Working Papers from Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School Contact information at EDIRC.
Bibliographic data for series maintained by Helene Olsen ().