Catching energy thieves

The Case:

It is estimated that energy theft amounts to 4% of the total energy used in the world annually. This theft costs the world economy over $64 billion a year and is responsible for over 1% of the total emissions of CO2 (more than the country of Italy releases in 1 year).0-

The Challenge:

Energy theft losses are caused by non-paying customers. A large portion of the energy is being stolen in rural areas and in the slums surrounding major cities in the developing world where installing smart meters is more difficult due to poor infrastructure.

Reaching these areas is also difficult and some energy companies choose to take a loss than to waste more resources trying to conduct expensive investigations which have a success rate of less than 10%.

The Solution:

We’ve developed an algorithm for the detection of energy theft using regular non-smart meter technology. The algorithm is an improvement of an existing solution that was deployed in Brazil to solve the very same problem of catching thieves in areas where taking accurate meter readings is more difficult.

Our solution was developed in close collaboration with one of the biggest DSOs in Bulgaria. The algorithm first looks at the historical energy consumption data and tries to find customers with an anomalous usage pattern. Then the algorithm uses a wide range of external data (such as weather data) to determine if the customer is a thief or not. Then an alert is given to an inspector to go and examine the set consumer. Upon inspection, a report is generated which is then used by the system to improve its predictions.

The Outcome:

With this approach, we can increase the success rate of inspection by up to 30%.