A semi-parametric time series approach in modeling hourly electricity loads


In this paper we develop a semi-parametric approach to model nonlinear relationships in serially correlated data. To illustrate the usefulness of this approach, we apply it to a set of hourly electricity load data. This approach takes into consideration the effect of temperature combined with those of time-of-day and type-of-day via nonparametric estimation. In addition, an ARIMA model is used to model the serial correlation in the data. An iterative backfitting algorithm is used to estimate the model. Post-sample forecasting performance is evaluated and comparative results are presented.  Copyright © 2006 John Wiley & Sons, Ltd.

Similar works

Full text


Research Papers in Economics

Last time updated on 06/07/2012

This paper was published in Research Papers in Economics.

Having an issue?

Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.