Schneider Electric Case Studies Empowering Enel for a bright, connected future
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Empowering Enel for a bright, connected future

Schneider Electric
Analytics & Modeling - Real Time Analytics
Platform as a Service (PaaS) - Connectivity Platforms
Utilities
Logistics & Transportation
Maintenance
Energy Management System
Predictive Maintenance
Cloud Planning, Design & Implementation Services
System Integration
Enel, Italy’s largest power company and Europe’s second listed utility for installed generation capacity, recognized the need for an advanced distribution management system. However, they lacked the internal resources necessary to create mathematical algorithms to enhance distribution management. In the past, some employees tried inventing solutions, but without an adequate technical background it held no scientific value. Their employees were spending too many resources trying to create a solution without solid analysis. Without the analysis, the data meant nothing.
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Enel is Italy’s largest power company and Europe’s second listed utility for installed generation capacity. It operates in 40 countries worldwide, has around 95,000 MW of net installed capacity, and sells power and gas to more than 61 million customers. The company is based in Rome, Italy and is a major player in the global power and gas markets. Enel's operations span the entire energy chain, including the generation, distribution and sale of electricity and gas, and the development of renewable sources.
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Enel implemented Schneider Electric's EcoStruxure Advanced Distribution Management System (ADMS), a real-time solution that provides complete functionality for the planning, operation, and analysis of a utility’s distribution system. The system is designed to help complex utilities like Enel minimize power and energy losses, optimize voltage profiles, and reduce general costs by enabling peak sharing via demand response (DR) and distributed system and demand response (DSDR). Enel used Schneider Electric EcoStruxure ADMS to provide a visual, mathematical model of its distribution network, including detailed models for voltage management, micro-generation, frequency variation, DR, and other Smart Grid management data. The utility now has more accurate data and a system that can predict the impact of power outages, generation, and voltage variation.
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Significant energy and cost savings through the optimization of its existing network resources and operations.
Streamlined energy production and decreased CO2 emissions.
Supply restoration and network reconfiguration, which reduces time and creates a fast and reliable system for producing results.
Energy savings of 144 GWh per year.
Reduction of 75,000 tCO2 per year.
Steady gain of about 4% all year round.
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