AI Case Study

Enel improved the average energy recovered per non-technical loss inspection by 70% in Italy and more than 300% in Spain using machine learning

Enel leverages C3 IoT to identify electricity theft (non-technical loss) and recover unbilled energy. The solution applies machine learning and analytics to calculate the probability of fraud for each customer meter using data from seven Enel source systems. The company managed to improve the average energy recovered per inspection in both Italy and Spain.

Industry

Utilities

Electricity

Project Overview

Identifying and recovering electricity theft:
"With C3 IoT, Enel transformed its approach to identifying and prioritizing electricity theft (non-technical loss) to drive a step change in the recovery of unbilled energy, while improving productivity. The effort required building AI/machine learning algorithm to match the performance delivered by Enel experts using a process honed over 30 years of experience. While this was a significant challenge in and of itself, Enel set an ambitious target to double the performance achieved in recent operating years.

A key innovation that enabled this transformation was to replace traditional non-technical loss identification processes, focused primarily on improving the success of field inspections, with C3 IoT’s advanced AI algorithms to prioritize potential cases of non-technical loss at service points, based on a blend of the magnitude of energy recovery and likelihood of fraud.

The system integrates and correlates 10 trillion rows of data from seven Enel source systems and 22 data integrations into a unified, federated cloud image in near real-time, running on Amazon Web Services. Using analytics and more than 500 advanced machine learning features, C3 Fraud Detection continuously updates probability of fraud for each customer meter."

Reported Results

"With C3 Fraud Detection, Enel improved the average energy recovered per inspection by 70 percent in Italy and more than tripled it in Spain"

Technology

analytics and more than 500 advanced machine learning features

Function

Customer Service

Other

Background

"Global Fortune 100 Enel is executing an enterprise-wide digitalization strategy aimed at increasing efficiency, developing new services, and spreading a digital culture across the organization. Central to achieving Enel’s goals is the large-scale deployment of C3 IoT’s big data, predictive analytics platform (PaaS) and SaaS applications. Enel operates the largest enterprise IoT system across 20 million smart meters across Italy and Spain."

Benefits

Data

10 trillion rows of data from seven Enel source systems and 22 data integrations into a unified, federated cloud image in near real-time