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- Many forecasting methodologies are outdated.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. In particular, the paper:
- Investigates how a number of approaches using geographic hierarchy and weather station data can improve the predictive analytics used to determine future electric usage.
- Demonstrates why using geographic hierarchies is now imperative for utilities.
Download now, to know more about.