Experience of Enel's remote predictive diagnostic center in monitoring thermal power plants using AVEVA Predictive Analytics as one of the main anomaly detection tools.
Enel is a multinational company that produces and distributes electricity and gas. It was established as a public entity at the end of 1962; In 1992 it was transformed into a joint-stock company and in 1999, after the liberalization of the electricity market, it was privatized. The Italian State, through the Ministry of Economy and Finance, still remains the main shareholder and December 2020, it owned 23.6% of the share capital.6 It is listed on the Milan Stock Exchange. Enel is the 90th company in the world by sales volume with 140.5 billion euros and a stock market capitalization of 54 billion euros.
Goals
- Leverage AVEVA Predictive Analytics to build a remote predictive diagnostic center for the identification and reporting of anomalies in asset behavior at Enel's 28 power generation plants.
- Greater asset availability and lower maintenance costs
Challenges
- Monitor the health and performance of more than 1,285 individual power generation assets using 5,035 predictive models that monitor 7,000 individual PI System tags
- Dispersed power generation assets spanning 5 countries and 2 continents.
Solutions
- AVEVA™ PI System™
- AVEVA™ Predictive Analytics
Results
- 402 total captures from AVEVA Predictive Analytics
- More than 40 million euros in savings in maintenance costs and prevention of asset failures
- Increased plant availability KPI by 1.48 percentage points across the fleet
“AVEVA is not just a supplier for us. We consider them part of our team.”
Claudio Macchia, Mechanical Engineer, Enel
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