Clir’s software platform uses machine learning algorithms to categorize and quantify areas of underperformance across wind assets (e.g. yaw, blade pitch), resulting in recommended actions for improvement. Customers realize Annual Energy Production (AEP) gains of up to 5% from Clir’s actionable insights.

Driven by cost reductions and performance improvements, global wind power capacity is growing rapidly. However, wind farms continue to operate at sub-optimal levels. According to the Electric Power Research Institute (EPRI), most wind farms have an opportunity to increase energy output with better data analytics.

Clir stands out from competing software solutions in this growing market due to its ability to generate actionable optimization recommendations, moving beyond data monitoring and visualization.


[North American Wind Power] Software Start-Up Clir Aims To Increase Wind Farm Performance (jun 20, 2018)