A leading North American independent power producer wanted to identify and recover hidden performance losses at a 305 MW wind farm. The wind farm had been recently acquired by the IPP. Wind PulseSense analyzed high-frequency, event and 10-minute SCADA data without requiring additional hardware. The analysis identified four opportunities: Turbine-specific yaw misalignment that a previous sitewide LiDAR-based correction had not resolved Incorrect blade-pitch configurations Curt

Can You Trust Your Wind Analytics Provider? Not all wind analytics deliver equally reliable results. The quality of an analytic depends on the data it uses, the domain expertise behind its development, and how thoroughly it has been validated under real operating conditions. This case study compares two approaches to detecting yaw misalignment: OpenOA, an open-source method using 10-minute SCADA data, and Wind PulseSense, which combines high-frequency SCADA data with physics-

A wind plant in Southeast Asia was producing below its pre-construction expectations, despite remaining under an OEM full-service agreement and warranty. Wind PulseSense analyzed the plant’s existing operating data to identify the causes of underperformance and recommend corrective actions without requiring additional hardware. The analysis uncovered three important issues: Significant static yaw misalignment on 27 of 30 turbines Unnecessary yaw-error shutdowns during lower w