End User
ELGO
Description
SCADA systems produce massive volumes of event logs during both planned and unplanned outages, making it difficult to isolate meaningful signals. This service uses machine learning and GenAI to analyze logs in real time, filtering out noise and highlighting the most informative events. It helps identify likely root causes and generates concise summaries to assist operators during incidents. By accelerating root cause analysis and reducing cognitive load, the tool enables faster response and recovery, improves operational efficiency, and enhances overall system reliability.
Core Capabilities
Optimization & Decision Support
Automation & Control Systems
Business Need
This service tackles a critical issue in SCADA-based control centers: the difficulty of identifying root causes during unplanned outages due to overwhelming volumes of log data. Operators are often forced to sift through noisy, redundant logs, slowing down response times and delaying system recovery. This AI-powered tool automates real-time log analysis, filtering out noise, surfacing key events, and suggesting likely root causes. While it won't replace field inspections, it significantly accelerates initial diagnosis, enabling faster, more informed responses. The result is improved operational efficiency, reduced downtime, and enhanced grid reliability during high-stakes events.
Key Performance Indicators
Accuracy and relevance of event clustering, evaluated by domain professionals
Quality and usefulness of generated outage summaries, assessed by domain experts
Time taken to analyze logs and generate insights during unplanned outages (Δtime)
Reduction in time to identify root cause compared to manual analysis (Δtime)
Confusion matrix to assess classification performance (e.g., true positives, false positives, etc.) where applicable
Data Provided
SCADA Event logs
Outage events from MySQL DB
TEF
TEF TSO