AI Integration in Substations: From Data Collection to Intelligent Decisions
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Modern substations generate enormous amounts of data. Protection relays record events and waveforms, monitoring systems track equipment condition, cameras watch the switchyard, and SCADA systems log thousands of points every few seconds. For years, much of this data went unanalyzed simply because there were not enough engineers to review it. Artificial intelligence is changing that, turning substation data into early warnings, better decisions, and more efficient operations.
Predictive Maintenance and Anomaly Detection
The most mature application of AI in substations is predictive maintenance. Machine learning models trained on historical equipment data can learn the normal behavior of a transformer, breaker, or battery system and flag deviations that may indicate a developing problem.
A circuit breaker, for example, produces a characteristic signature each time it operates: trip coil current, contact travel time, and motor charging current. An AI model can compare each operation to that breaker’s own history and to similar breakers across the fleet, identifying subtle changes such as slower operation or abnormal coil current long before the breaker fails to clear a fault. Similar approaches apply to transformers, capacitor banks, and substation batteries.
Read the full article at:
https://online.electricity-today.com/electricity-today/q3-2026/