Largest Production Deployment of AI and IoT Applications

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Overview

To increase efficiency, develop new services, and spread a digital culture across the organization, Enel is executing an enterprise-wide digitalization strategy. Central to achieving the Fortune 100 company’s goals is the large-scale deployment of the C3 AI Suite and applications. Enel operates the world’s largest enterprise IoT system with millions of smart meters across Italy and Spain.

About Enel

  • 96GW Generation Capacity
  • €71 Billion Annual Revenue
  • 62M Customers Globally
  • 73,000 Employees

Project Highlights

  • 8+ Year Strategic Partnership
  • 25+ Data Sources
  • 50TB Unified Federated Cloud Image
  • 10M Node In-memory Graph Network
fabio veronese

"Talking about digitalization, new technology, the move to the cloud, and the adoption of platforms, our experience with C3 AI has been a wonderful example.”

Fabio Veronese
Head of Infrastructure & Networks Digital Hub, Enel

Enterprise Digital Transformation

Enel and C3 AI have been working together since 2013. Two of Enel’s enterprise-wide digital transformation efforts with C3 AI are fraud detection and predictive maintenance of distribution assets.

With C3 AI, Enel transformed its approach to identifying and prioritizing electricity theft (non-technical loss), with a goal to double the recovery of un-billed energy while improving productivity. The effort required building AI/machine learning algorithms to match the performance delivered by Enel experts using a process honed over 30 years of experience.

To accomplish this, the teams collaborated to replace traditional non-technical loss identification processes with the C3 AI Fraud Detection application. The new application uses advanced AI capabilities 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 8 trillion rows of data from 83 Enel source systems and 218 data integrations into a unified, federated cloud image in near-real-time, running on Amazon Web Services. Using analytics and more than 300 machine learning models with thousands of machine learning features, C3 AI Fraud Detection continuously updates probability of fraud for each customer meter.

To improve grid reliability and reduce the occurrence of faults, Enel deployed the C3 AI Reliability application for five control centers. The application uses AI to analyze real-time network sensor data, smart meter data, asset maintenance records, and weather data to predict feeder failure.

The system provides a holistic view of Enel’s operating assets by integrating data from eight disparate systems (SCADA, Grid Topology, Weather, Power Quality, Maintenance, Workforce, Work Management, and Inventory) and presents relevant, actionable insights. Key innovations in this project include a time-based view of Enel’s as-operated network state using an advanced graph network approach, and the use of an advanced machine learning framework that continuously learns to improve prediction performance.

Results

13
Production Applications Deployed at Scale
360M+
Sensors Monitored
2X
Performance Increase in Identifying Unbilled Energy
€2.5B
Cumulative Economic Benefit Target from Digitalization

Solution Architecture

Enel Solution Architecture

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