Forecasting of daily electricity prices with factor models: Utilizing intra-day and inter-zone relationships

Katarzyna Maciejowska () and Rafał Weron

No HSC/13/11, HSC Research Reports from Hugo Steinhaus Center, Wroclaw University of Science and Technology

Abstract: We show that incorporating the intra-day and inter-zone relationships of electricity prices in the Pennsylvania--New Jersey--Maryland (PJM) Interconnection improves the accuracy of short- and medium-term forecasts of average daily prices for a major PJM market hub -- the Dominion Hub in Virginia, U.S. The forecasting performance of four multivariate models calibrated to hourly and/or zonal day-ahead prices is evaluated and compared with that of a univariate model, which uses only average daily data for the Dominion Hub. The multivariate competitors include a restricted vector autoregressive model and three factor models with the common and idiosyncratic components estimated using principal components in a semiparametric setup. The results indicate that there are forecast improvements from incorporating the additional information, essentially for all considered forecast horizons ranging from one day to two months, but only when the correlation structure of prices across locations and hours is modeled using factor models.

Keywords: Wholesale electricity price; Forecasting; Vector autoregression; Factor model; Principal components; PJM market (search for similar items in EconPapers)
JEL-codes: C32 C38 C53 Q47 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2013-12-30
New Economics Papers: this item is included in nep-ene, nep-for and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Forecasting of daily electricity prices with factor models: utilizing intra-day and inter-zone relationships (2015)
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