1
Disturbance identification and analysis
Algorithms are used for detailed analysis, identifying specific causes of outages and optimizing network interventions.
Disturbance Analysis
Advanced monitoring and diagnostics to increase reliability and prevent transmission system interruptions.
Project objective
The Disturbance Analysis project aims to develop advanced computing techniques to improve the automatic analysis of events in the electrical system. The goal is to identify causes of interruptions and potential evolving issues, enabling preventive actions to ensure grid stability and security.
Investment:
R$
3191506,
00
Why is this project essential?
As Brazil’s electrical system grows in complexity, improving analysis and monitoring tools is crucial.
This project positions Evoltz at the technological forefront, developing solutions that reinforce the safety and efficiency of the nation’s energy transmission infrastructure.
Originality and innovation
This project is a pioneer in applying new techniques for analyzing oscillographic data, such as integrating information from different sources, including weather and georeferenced data. The SINAPE.Net platform provides a detailed view of occurrences, integrating features like automatic event detection and correlation with data on wildfires and other incidents.
Scope achieved
Enhanced algorithms for automatic analysis
Creation of an event analysis platform
Integration with georeferenced and weather data
Implementation of alarm systems and automatic notifications
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Integration with external data
Incorporating weather and wildfire data enables more comprehensive and contextualized event analysis.
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Specialized alarm generation
The developed platform includes an alarm system that aids in rapid incident detection and provides critical information to the control team.
4
Multi-resolution visualization
Tools offer views at different time scales of events, facilitating the analysis of phenomena with varying durations and amplitudes.
Looking to the Future
Greater accuracy and agility:
Advanced algorithms reduce response times and improve the accuracy of analyses.
Reduced operational failures
Detailed analysis and disturbance prevention help minimize failures and interruptions, enhancing reliability for consumers.
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