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

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.