Sensor Integrity & Data Confidence

Challenge: Renewable generation performance depends heavily on sensor accuracy, yet sensor health is often unmanaged. Wind speed and river/reservoir level sensors directly influence generation expectations and dispatch decisions. Temperature and vibration sensors are critical for early fault detection, but failures often go unnoticed. Sensors may degrade or drift slowly, producing believable but incorrect data that skews generation set points and KPIs.

Solution: Konductor continuously monitors sensor behaviour alongside asset performance to detect sensor failure, drift, or implausible values. The platform applies contextual checks including detection of flat-lined or frozen signals, cross-comparison of related sensors (e.g. wind speed vs power output), identification of gradual sensor drift, and validation against historical and environmental patterns.

Results: The platform delivers improved confidence in resource and condition-monitoring data, reduced risk of incorrect dispatch or control decisions, faster identification of calibration and replacement needs, more accurate generation reporting, and lower operational risk from hidden sensor degradation.