In Analytics, Use Cases

In 2010, BC Hydro estimated that energy theft cost the utility up to CAD $100 million annually in lost revenues. That’s enough power to supply 77,000 homes for a year.

As described in this EY article, much of the theft supported illegal marijuana growing operations hidden in residential buildings across the BC Hydro service territory, an area the size of the UK and France combined.

At the time, BC Hydro had just finished installing smart meters for all of their 1.9 million customers. Smart meters meant no more human meter readers walking routes and reporting suspicious activity. But smart meters also meant a valuable source of big data for detecting and prosecuting energy theft.

BC Hydro also installed smart meters along feeders and segments on the power grid, upstream from consumption meters on houses and businesses. By using situational intelligence applications that combined spatial, temporal and network analytics, BC Hydro began to detect which locations had abnormally low energy consumption, which could indicate power theft.

In particular, BC Hydro could compare energy delivered down a feeder with energy billed from meters along that feeder. If those two numbers weren’t equal, then energy was being lost and potentially stolen. Other factors such as weather, season, time of day, size and type of building, and so on enhanced BC Hydro’s ability to identify likely instances of energy theft.

Advanced visualizations helped revenue analysts and field investigators prioritize, locate, and research suspected theft cases. If a case warranted legal prosecution, the data and visualizations provided compelling evidence at trial.

Today, theft has been reduced by 75 percent. Plus, customers are safer, with fewer dangerous hacks into the power grid. BC Hydro continues to use advanced analytics and visualization to reclaim revenues lost to theft as well as technical and non-technical loss.

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