The load model is a machine learning product which estimates a half-hourly annual demand profile for each household based on a series of demographic, geographic & heating type factors. To enable us to estimate capacity on the electricity network while protecting individual customers data privacy by using modelled data. These views are then aggregated up the networks hierarchy based on the combinations of customers associated with each asset. This view is supplemented with the forward distributed forward energy scenarios (DFES) which highlight the expected impact of low carbon technology on the network (LCT) such as heat-pumps or electricity vehicles. The view demonstrated here represents a sample iteration of our evolving network capacity & load model - highlighting estimated peak usage against asset rating.

A description of my dataset