Conference programme

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Delegates are invited to meet and discuss with the poster presenters during the poster presentation sessions between 10:30-11:30 and 16:00-17:00 on Thursday, 19 November 2015.

Lead Session Chair:
Stephan Barth, ForWind - Center for Wind Energy Research, Germany
Alain Fremaux Schneider Electric, United States
Co-authors:
Don Leick (1) F
(1) Schneider Electric, Burnsville, United States

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Poster

Poster Download poster (7.06 MB)

Abstract

Cutting Repair Costs with Post-Thunderstorm Blade Inspection

Introduction

Lightning is a leading cause of blade damage, and often the leading cause of unplanned outages, in many parts of Europe and the world. If not detected, blade damage can propagate and lead to a far more expensive repair or even full replacement of the blade. Proactive blade inspection program to promptly detect lightning damage and repair blades before damage progresses can significantly reduce blade repair costs.

Approach

Lightning-related blade inspection is an emerging best practice with wind farm (park) operators in N. America and Europe. Rather than inspecting blades for damage on an annual basis, blades are inspected after a thunderstorm. Only turbines likely to be struck by lightning are inspected. Since SCADA systems normally cannot detect and alert operators to a lightning strike, turbines to be inspected are identified using lightning data. The location of turbines and lightning strikes are correlated. A quick ground-based inspection is done for lightning damage. If damage is found, appropriate repair action is then taken.

Main body of abstract

Depending on where a wind farm is located, lightning is typically the leading or second leading cause of blade damage, behind leading-edge erosion. While lightning is less of an issue in the UK and North Sea it is a significant issue in most of Europe. Lightning frequency is even higher in the US, China, Brazil and many other high growth regions for wind energy. (Will show actual ground lightning strikes observed in Europe & the globe for past 3 years.)

Wind farms typically experience even higher lightning rates. They are particularly prone to lightning given the nature of the tall structures, often compounded by the turbine position on ridges and hills. Movement of blades through the atmosphere also builds an electrical charge. Blades are almost always the attachment point.

Often the blade damage is a puncture or other not obviously visible damage. With the stresses on blades, this damage can propagate over time into much more extensive damage. This causes a more extensive repair, or even cause a full blade replacement. Typical repair costs to patch a puncture might be 6,000 to 12,000 euros, whereas a blade replacement, including crane rental, can cost 100,000 to 250,000 euros.

It is uncommon for a wind farm to have mechanisms to alert operations to a lightning strike on a turbine. Therefore the only way to identify turbines that may have been hit by lightning is to use lightning data from lightning detection networks. Several commercial lightning detection networks operate in Europe with locational accuracy sufficient to support blade inspection. It is important to understand the accuracy of the network, and the error distribution pattern.

After a thunderstorm, such as the following day, the location of turbines and lightning strikes are correlated and the specific turbines to be inspected are identified. The turbine inspection report can include specifics about the lightning strike such as exact time and amplitude. This data can also be useful for warranty and insurance claims. A quick ground-based inspection using binoculars or a telescope is done for lightning damage. If damage is found, appropriate repair action is then taken. Typically depending on the damage (if any), the options will be to continue to operate and monitor, operate and repair when work can be scheduled, or immediately stop operation until repaired. Another option might be to de-rate the turbine.


Conclusion

Implementing a proactive blade inspection program to detect lightning damage can significantly reduce blade repair costs. It can also reduce lost generation revenue due to out-of-production turbines. And the lightning data involved also has secondary uses for warranty and insurance claims.


Learning objectives
Participants will learn:
• Behavior of lightning strikes in wind farms, and frequency of lighting in different regions of the world
• Typical blade damage caused by lightning
• Requirements for lightning data for identifying turbines to inspect
• Steps involved in implementing a proactive lightning blade inspection program
• Benefits of such an inspection program