Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices
Kees E. Bouwman and
Dick van Dijk ()
Additional contact information
Eran Raviv: Erasmus University Rotterdam
Kees E. Bouwman: Erasmus University Rotterdam
No 13-068/III, Tinbergen Institute Discussion Papers from Tinbergen Institute
This discussion paper led to a publication in 'Energy Economics' , 2015, 50, 227-239. The daily average price of electricity represents the price of electricity to be delivered over the full next day and serves as a key reference price in the electricity market. It is an aggregate that equals the average of hourly prices for delivery during each of the 24 individual hours. This paper demonstrates that the disaggregated hourly prices contain useful predictive information for the daily average price. Multivariate models for the full panel of hourly prices significantly outperform univariate models of the daily average price, with reductions in Root Mean Squared Error of up to 16%. Substantial care is required in order to achieve these forecast improvements. Rich multivariate models are needed to exploit the relations between different hourly prices, but the risk of overfitting must be mitigated by using dimension reduction techniques, shrinkage and forecast combinations.
Keywords: Electricity market; Forecasting; Hourly prices; Dimension reduction; Shrinkage; Forecast combinations (search for similar items in EconPapers)
JEL-codes: C53 C32 Q47 (search for similar items in EconPapers)
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 Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: http://EconPapers.repec.org/RePEc:tin:wpaper:20130068
Access Statistics for this paper
More papers in Tinbergen Institute Discussion Papers from Tinbergen Institute Contact information at EDIRC.
Series data maintained by Tinbergen Office +31 (0)10-4088900 ().