With the deployment of smart grid technologies, many utilities can now take advantage of hourly or sub-hourly data from millions of smart meters. There are many upsides to this – such as the fact that utilities can potentially charge customers different rates based on the time of day they use electricity.

However, there are downsides as well:

• Many forecasting methodologies are outdated.
• The days of one-size-fits-all models are gone for the utility forecaster.

This paper tackles these considerations through an electric load-forecasting case study.