Six Real-World Case Studies: How Predictive Analytics Boosts Power Plant Performance

Despite robust plans for enhancing availability, reliability, efficiency and compliance, many power generation firms now hit a performance plateau that hampers corporate objectives.

Aging assets, right‑sizing drives, a shrinking skilled workforce, and restrictive OEM contracts further deepen the gap, creating an equipment performance shortfall that reverberates across operations, maintenance and finance whenever equipment underperforms.

SmartSignal’s EPI*Center is designed to lift operators beyond this plateau by delivering early, actionable warnings of abnormal performance across all critical systems and operating states—well beyond what traditional condition monitoring tools like vibration analysis can reveal.

Challenges for the Best‑Run Plants

To illustrate the added value of predictive analytics, the following case histories showcase customers who already fielded rigorous preventive maintenance, state‑of‑the‑art condition monitoring (vibration, thermography, etc.) and industry‑standard trending programs yet still experienced unpredictable equipment issues. They added EPI*Center’s predictive analytics to gain early insight into emerging faults.

• Implemented rigorous preventive maintenance programs.
• Employed advanced condition monitoring such as vibration and thermography.
• Maintained trending programs consistent with industry standards on priority equipment.
• Continued to experience unpredictable equipment problems despite trained staff.

Predictive Analytics in Action

Each case below details a situation where SmartSignal clients turned early warnings into tangible value. In every instance, the emerging problem eluded traditional monitoring or trending tools.

• Highlights the range of critical equipment covered by EPI*Center.
• Provides insights into typical actions triggered by WatchList incidents.
• Quantifies the resulting benefits.

Case Study #1 – Air Heater Support Bearing Problem

Problem: On December 22, a fossil‑fuel plant’s secondary air heater support bearing temperature spiked 40 °F above ambient‑based normal, triggering a WatchList incident. No other plant systems flagged the anomaly.

Solution: Operators added 3.5 gallons of oil to the 25‑30 gallon capacity bearing, normalizing temperatures immediately.

Benefits: The early warning prevented a bearing failure that, in July, had taken nine days to repair and cost 138,804 MWh of lost generation—equivalent to $1.5 M–$4 M at $10–$30 per MWh.

Case Study #2 – Early Warning of Shorted Turns on an Exciter

Problem: A 1,500 + MW plant reported high exciter amperage (5 A to 15 A above predicted norms) on the WatchList, just weeks before a planned 80‑plus‑day outage.

Solution: Engineering diagnosed shorted turns in the rotor and rewound the exciter during the scheduled outage.

Benefits: The predictive alert accurately identified the fault, enabling timely corrective action and avoiding a costly unplanned outage.

Case Study #3 – Early Detection of Developing Bearing Issue on Turbine Generator

Problem: A 420 MW GE steam turbine’s low‑pressure turbine bearing showed a 14‑°F temperature rise—below the normal threshold but flagged by EPI*Center.

Solution: Subsequent vibration data revealed a 1 Mil step change; a PM&D Center specialist recommended a detailed inspection. The bearing, scheduled for a two‑week planned outage, was found damaged, repaired, and replaced.

Benefits: Avoided a potential in‑service failure or forced outage during peak demand, preserving the company’s Peak Power Reliability Rating and saving $503,800–$655,000 in outage costs.

Case Study #4 – Early Warning of Inboard Bearing Damage on a Boiler Feed Pump

Problem: A fossil‑fuel plant’s boiler feed pump motor bearings were flagged for rising temperatures seven days before traditional monitoring would have triggered an alarm.

Solution: A planned outage was scheduled at an optimal time, and the bearings were replaced without an unplanned trip.

Benefits: The early warning enabled a cost‑effective planned outage and avoided a forced outage that would have cost significant generation revenue.

Case Study #5 – Early Detection of Loose Coupling on ID Fan D

Problem: On January 31, high amperage incidents appeared on the WatchList for ID Fan D.

Solution: Investigation revealed a loose shaft‑coupling set‑screw; tightening was completed before the planned outage.

Benefits: Prevented fan loss and load reduction, ensuring continuous operation.

Case Study #6 – Early Warning of Bearing Cooling Issue on a Circulating Water Pump

Problem: In early February, a 700‑+ MW plant’s circulating water pump bearings showed 20‑80 °F temperature deviations above EPI*Center norms, yet the DCS had not yet alarmed.

Solution: Investigation uncovered a cooling water restriction; a temporary line reduced temperatures by 20 °F, and a permanent line was installed during a planned outage.

Benefits: The early warning prompted a timely repair that prevented bearing and shaft damage, avoided back‑pressure issues, and maintained condenser flow during winter operation.

Why EPI*Center Delivers Real Value

EPI*Center is a software solution that harnesses existing process, condition‑monitoring, and electrical sensor data to provide:

• Early warnings of equipment anomalies that other systems miss.
• Consistent alerts across all equipment and operating regimes.
• Rapid configuration, deployment, and immediate return on investment.

By turning predictive analytics into actionable insights, power plants can close the performance gap, reduce downtime, and protect corporate performance.