Journal article

Bayesian modeling and forecasting of intraday electricity load

R Cottet, M Smith

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION | AMER STATISTICAL ASSOC | Published : 2003

Abstract

The advent of wholesale electricity markets has brought renewed focus on intraday electricity load forecasting. This article proposes a multiequation regression model with a diagonal first-order stationary vector autoregresson (VAR) for modeling and forecasting intraday electricity load. The correlation structure of the disturbances to the VAR and the appropriate subset of regressors are explored using Bayesian model selection methodology. The full spectrum of finite-sample inference is obtained using a Bayesian Markov chain Monte Carlo sampling scheme. This includes the predictive distribution of load and the distribution of the time and level of daily peak load, something that is difficult..

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University of Melbourne Researchers