Wind farm analytics

Nokia Wind farm analytics help wind energy generating companies minimize unplanned downtime, lower operating costs, improve capital planning efficiency, and make informed, risk and return-based decisions.

The Nokia difference

Wind energy companies need to reduce operations and maintenance costs and downtime from turbine failure while still earning the highest return on their capital spending. They need to make the right decisions from moment to moment at scale and speed. With Nokia Wind farm analytics, they can address each of these challenges, and more.

Extend asset life and optimize repair and replace with predictive maintenance

Predict turbine failure times and optimize repair and replacement to extend asset life and minimize downtime. Machine learning predicts asset failure with greater confidence and determines optimal repair times to extend operating hours and increase return on capital.

wind farm analytics

Automated workforce optimization

Go beyond predictive maintenance with real-time workforce optimization to significantly lower costs and minimize downtime. Using sophisticated machine learning and prescriptive analytics, Nokia determines the optimal schedule and routing for wind turbine maintenance crews and automatically schedules work orders in your field service maintenance system. Our advanced analytics considers real-time, dynamic variables like weather and traffic to continuously optimize operation and maintenance activities, significantly driving down O&M costs. That savings drops straight to the bottom line.

Optimize asset utilization and mitigate risk

Using asset analytics, planning engineers and engineering and operations groups easily collaborate to simultaneously lower risk and optimize spending. This collaboration supports a culture of improved decision-making driven by insights from analytics.

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Complete this short form or give us a call to arrange a demo of Wind farm analytics and learn how Nokia can help your wind farm operate more cost-effectively every day.

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