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Use case

Real-Time Detection and Reporting of Hydropower Generation Events

Pablo Sanchez
Industry Principal
Reading time:
Watch time:
2
min.
Updated:
Watch time:
August 31, 2026

The Challenge

Hydropower units operate under different modes depending on AGC (Automatic Generation Control) status and complementary services configuration.

Without automated classification, obtaining a clear operational overview and summarizing events and operating hours required significant manual effort.

  • Multiple operating modes and turbine configurations
  • Operating states derived from several signals
  • No consolidated real-time overview
  • Manual event and operating-hour reporting
  • Operational anomalies difficult to summarize

The Approach

Engineers combined value-based searches, dashboards and AI-assisted analysis to automatically detect and summarize operating conditions.

State definition: Value-based searches defined hydropower unit generation states, based on AGC and complementary services configuration.

Event tracking: Conditions were automatically classified and tracked over time

Real-time overview: A Gantt chart consolidated all states in the main dashboard

AI-assisted analysis: TrendMiner Agent aggregated events, operating hours and anomalies through natural-language requests

Gantt chart and overview dashboard with state detection and complementary plant information

Key Insight

Converting process signals into defined operating states created a clear real-time overview, while AI enabled fast aggregation and analysis of operational events.

Results

KPIResult
Operating state detectionModes automatically classified
Real-time visibilityGantt overview created
Event reportingEvents and operating hours summarized
Anomaly trackingDeviations quantified by period
Analysis capabilityNatural-language AI analysis enabled

Value

By automatically detecting and summarizing operating states, the team improved operational visibility, simplified recurring reporting and enabled faster analysis of generation events and anomalies.

Energy & natural resources
Reporting Compliance & Safety
Operational Performance Management
Production Reporting
Process Health Monitoring
Process Engineer
Plant Manager
Operator
Automation Engineer
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The Challenge

Hydropower units operate under different modes depending on AGC (Automatic Generation Control) status and complementary services configuration.

Without automated classification, obtaining a clear operational overview and summarizing events and operating hours required significant manual effort.

  • Multiple operating modes and turbine configurations
  • Operating states derived from several signals
  • No consolidated real-time overview
  • Manual event and operating-hour reporting
  • Operational anomalies difficult to summarize

The Approach

Engineers combined value-based searches, dashboards and AI-assisted analysis to automatically detect and summarize operating conditions.

State definition: Value-based searches defined hydropower unit generation states, based on AGC and complementary services configuration.

Event tracking: Conditions were automatically classified and tracked over time

Real-time overview: A Gantt chart consolidated all states in the main dashboard

AI-assisted analysis: TrendMiner Agent aggregated events, operating hours and anomalies through natural-language requests

Gantt chart and overview dashboard with state detection and complementary plant information

Key Insight

Converting process signals into defined operating states created a clear real-time overview, while AI enabled fast aggregation and analysis of operational events.

Results

KPIResult
Operating state detectionModes automatically classified
Real-time visibilityGantt overview created
Event reportingEvents and operating hours summarized
Anomaly trackingDeviations quantified by period
Analysis capabilityNatural-language AI analysis enabled

Value

By automatically detecting and summarizing operating states, the team improved operational visibility, simplified recurring reporting and enabled faster analysis of generation events and anomalies.

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Share with a co-worker

The Challenge

Hydropower units operate under different modes depending on AGC (Automatic Generation Control) status and complementary services configuration.

Without automated classification, obtaining a clear operational overview and summarizing events and operating hours required significant manual effort.

  • Multiple operating modes and turbine configurations
  • Operating states derived from several signals
  • No consolidated real-time overview
  • Manual event and operating-hour reporting
  • Operational anomalies difficult to summarize

The Approach

Engineers combined value-based searches, dashboards and AI-assisted analysis to automatically detect and summarize operating conditions.

State definition: Value-based searches defined hydropower unit generation states, based on AGC and complementary services configuration.

Event tracking: Conditions were automatically classified and tracked over time

Real-time overview: A Gantt chart consolidated all states in the main dashboard

AI-assisted analysis: TrendMiner Agent aggregated events, operating hours and anomalies through natural-language requests

Gantt chart and overview dashboard with state detection and complementary plant information

Key Insight

Converting process signals into defined operating states created a clear real-time overview, while AI enabled fast aggregation and analysis of operational events.

Results

KPIResult
Operating state detectionModes automatically classified
Real-time visibilityGantt overview created
Event reportingEvents and operating hours summarized
Anomaly trackingDeviations quantified by period
Analysis capabilityNatural-language AI analysis enabled

Value

By automatically detecting and summarizing operating states, the team improved operational visibility, simplified recurring reporting and enabled faster analysis of generation events and anomalies.

Access now

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