Source:Vaisala

Pattern Energy , a leading independent power company with wind power operations in the U.S., Canada, and Chile, plans to use lightning information provided by Finland’s Vaisala to build a better blade inspection and maintenance program that will ultimately help it assess where lightning damage is likely to have occurred to reduce inspection and replacement costs. 

Lightning often challenges wind farm assets and affects operations, especially if your assets are in a lightning-prone area. Blade damage due to lightning strikes can result in a significant amount of time for inspection and repair, not to mention the cost to repair or replace a blade.

Access to detailed information about a lightning event companies the power to make smart decisions, save time, money, and even improve your process to better manage your operational budget and exceed performance expectations.

Lightning Data as Part of a New Data System

With previous experience and knowledge about the availability of Vaisala’s lightning information, Pattern Energy decided to implement lightning information as part of its data system, and in particular, historical lightning information. This would allow Pattern Energy to conduct assessments of blade damage, and send detailed insurance or warranty-based claims.

- Before we didn’t have any insight into historical lightning data, or a good way of assessing lightning damage, Ben Rice, Operations Engineering Manager, at Pattern Energy says.

Previously Pattern Energy implemented a long-term contract for lightning information it first evaluated risk across its operational portfolios. Working with Vaisala, Pattern Energy learned that a substantial part of its fleet was susceptible to lightning. Pattern Energy already understood how lightning affects its operations and why it was critical to verify its occurrence. Lightning strikes to wind turbines can result in a large amount of damage each year.

The blades are particularly vulnerable, causing turbines, and therefore wind projects, to underperform while driving up operations and maintenance costs.

Additionally, lightning can increase the risk of future failures due to residual effects. Thus, it is important to quickly identify wind turbines that have suffered a strike in order to reduce the probability of further losses and damage.  With ten wind turbine sites between central Canada and Texas, Pattern Energy’s operations are in a prime area of lightning activity. After receiving a few detailed reports from Vaisala about lightning risks and reviewing the density of lightning in its operating area, Pattern Energy could clearly see the value of accessing Vaisala’s full historical lightning database and incorporating it into its reporting and data infrastructure programs.

Implementing the Solution

Pattern Energy began with a three-year contract for the Vaisala FALLS (Fault Analysis Lightning Location System) for all of its sites in lightning-impacted areas. FALLS software allows wind farm operators to access historical lightning data and analyze past exposure to assets. Pattern Energy uses FALLS to overlay infrastructure with the correlating lightning activity.

Having this data increases Pattern Energy’s chances of determining exactly which turbines were affected, and how extensive the damage may be.

While there is no way to remove the risk of lightning, knowing an asset was affected saves cost and up to half the inspection time compared to not having any insight into the cause of damage or where lightning might have occurred. Lightning information can be used to build a better blade inspection and maintenance program. Knowing lightning is the cause means it can mobilize inspection and repairs quickly, assess where future lightning damage is mostly likely to occur, and reduce the number of times occur, and reduce the number of times inspections are needed.

– We wanted to go straight to the source for lightning data. In general, [FALLS] has helped us look back and assess turbine damage, enabling us to determine whether lightning truly caused damage and exactly when that damage occurred.