Energy Webinar Series 2014 - Mitigating Lightning Impacts on Wind Farms

Mitigating the Impact of
Lightning on Wind Farms
Energy Webinar Series
Nic Wilson
Energy Regional Segment Manager, Americas
18 July 2014

/ Energy Webinar Series / 2014.07.18 / ©Vaisala
Today’s Speaker
 Based in Boulder, Colorado, USA
 5+ years experience in wind energy applications
 10+ years experience in lightning data applications
 nic.wilson@vaisala.com
Nic Wilson
Energy Regional Segment
Manager, Americas

Agenda
Introduction to Lightning
Wind Energy and Lightning
 Applications
 Software and Systems
 Wind Energy Lightning Research
 Current Applications for Lightning
Data

Lightning Detection
 Lightning is a high-current electrical discharge which takes
place in convective thunderstorms
 One of the leading causes of electricity outages globally

TCP/IP from Sensor
or
RS232 (or RS422)
TCP/IP
Communications
to Network
TLP™
TLP™ - Hot Back Up
TLD100/200
FALLS® Server
Real-time Display terminals
(LTS2005 Software)
Real-Time Historical, Post-processing
Historical data analysis modules
(FALLS®, DAM® Software)
Digi-Term server (if serial)
Modem kits (option) or LAN switch (option)
LAN switchLAN switch
Network Sensors
LS7002
TLD100/200 back up
Lightning Detection Network
 >95% DE for CG and
<200 m median LA

National Lightning Detection Network®

GLD360 Global Lightning Data
 GLD360 data available globally
 Combines VLF magnetic direction finding (MDF) and time-of-
arrival (TOA) technologies for lightning detection (CG + IC)
 >70% detection efficiency for cloud-to-ground lightning and better
than 2 km median location accuracy

FALLS® Client Reliability Analysis
 Determine if lightning was the
cause for a SCADA issued fault
 Locate wind turbines likely hit
by lightning
 Validate your lightning
protection design
A FALLS® Client Reliability Analysis for a transmission line
segment in Michigan on the evening of August 22, 2007. The
blue ellipse best correlates with the time stamp from the DFR, so
field maintenance crews can be sent to the location south of State
Route 46 with confidence that lightning was the cause.

TXD100 System Design
HTTPS Query
Login, Time, Geography,
Request Type, ….
Response
Data packaged per
request type
RTDBFormatter
DataHandler
WebServer
MasterStation
DFR
DFR
DFR
Auto E-Mail
Distribution

STRIKEnet and Custom Reports
 User-created reports available
from Weather Fusion STRIKEnet
 Specify the location (geo-
coordinates or address)
 Define time window (up to 72
hours)
 Custom forensic reports available
from experienced lightning
scientists
 Asset correlations
 Density and exposure maps

Integrated Offerings
Schneider Electric
MxVision WeatherSentry
Indji Systems Indji Watch

Energy Customers for Lightning
Wind Farm Owners
& Operators
How do I better
maintain my wind
turbines to lower
operating costs?
Is it safe for me to
continue working
on the wind
turbine?

Wind Farm Safety
 Wind turbines are 50 to 140 meters
above ground level requiring service
technicians 30 min to safely climb or
descend to ground
 Lightning warnings must be issued
early and accurately to ensure
operational efficiency and human
safety
 All-clear notifications are
issued when the threat of
lightning is no longer
present

Wind Turbine Damage Validation
 It is difficult to protect wind turbines from
lightning damage due to their height and
number of components
 Receptor tips on the blades try to attract
lightning and direct it through a proper
grounding system
 Certification standards require protection from
98% of lightning strikes
 Unprotected blades struck by lightning are
damaged by a heat explosion as the air inside
quickly expands
 Lightning correlation reports determine
which turbines must be inspected to identify
damage and repair

• Global leader in weather measurement equipment and services, based in Finland
• Owns and operates the North American Lightning Detection Network (NALDN) and
Global Lightning Dataset (GLD360) which provides data services to the leading
electricity transmission and wind farm operators to support their operations
• Global renewable energy company with parent EDP Group located in Portugal
• Operating in the USA and Canada since 2007 with over 3,700 MW and 28 wind farms
• Top university in the USA in environmental research as rated by the Journal Science of
the Total Environment in February 2013
• Professors Dr. Philip Krider and Dr. Kenneth Cummins are world-renown experts in the
field of atmospheric physics
Field Study Research Team

• Lightning strikes to turbines is a significant problem faced by wind farm operators
• Lightning can damage turbine blades and lead to reduced operating
efficiency and costly repairs
• The use of remote sensing technologies such as Vaisala’s North American
Lightning Detection Network (NALDN) allows wind farm operators to identify
potential lightning strikes and inspect turbines for damage
• It is less costly to repair lightning damage if it is identified early
Typical blade
damage
caused by
lightning
Research Motivations

• What fraction of lightning attachment to wind turbines are upward flashes that
are not detected by lightning detection networks?
• Do these events cause damage to wind turbines?
• What is the attractive radius (horizontal distance from a tall object where a
downward flash will attach) of a wind turbine, and how does it compare to that of
a stationary tower?
Industry Questions

• Field study operated from June 12, 2012 until September
7, 2012 (88 days)
• Automatically triggered cameras were deployed in a large
EDPR wind farm in the central USA that was instrumented
to report lightning current transients in turbine blades
• Lightning strike data from the NALDN was compared to
video recordings of turbine strikes to determine the
accuracy of the NALDN, the average attractive radius of
the wind turbines, and the likelihood of upward lightning
originating from turbines.
• Lightning strikes to a stationary radio tower were
compared with strikes to turbines in order to evaluate the
differences in attractive radius between the two
Field Study Approach

Video
• Two 60 fps PC-based systems using ufoCapture
software
Turbine Blade Current
• Current in conductor attached to receptors on
blades
Lightning Data
• NALDN cloud-to-ground stroke and in-cloud flash
data
Radiation-field Waveforms
• Automatic NLDN sensor recordings (400 Hz to 400
kHz) at nearby sensors (160 and 220 km away)
Composite Radar Reflectivity
• NMQ (Q2) mosaic reflectivity
• Used to identify storm type and storm phase for
upward lightning
Observation System

Video Observations (west side of wind farm)
• 7 turbine strikes were recorded, 3 of which were upward
• 2 radio tower strikes were recorded, 1 of which was upward
• 2 had no return strokes (triggered by nearby +CG stroke)
NALDN Data
• 491 NALDN events were recorded within 1 km of wind turbines during this time (219
west, 272 east)
• 229 events were cloud-to-ground (CG) and 262 events were in-cloud (IC)
• Not all NALDN events were captured on camera due to equipment issues and limited
field of view
• NALDN waveforms were obtained for all turbine strike events
Upward Cases
• NALDN reported no return strokes
• NALDN waveforms showed “impulsive “ magnetic fields with inferred peak currents of
less than 2-3 kA
• Blade damage for 1 of the 3 cases (not caught on video)
Video Observations Summary

Cloud to ground (CG) cases
June 15th
 CG strike to 1 turbine (-27.5 kA) with NALDN
location error of 169 m and no observed damage
July 26th
 CG strike to 2 turbines with blade damage in both
cases
 First at 00:25:22 GMT (-12.2 kA) with NALDN
location error of 104 m with damage to blade
spar
 Second at 00:34:02 GMT (-22.1 kA) with
NALDN location error of 84 m with damage to
blade spar
8/2
 CG strike to 1 turbine (-19.3 kA) and no
observed damage
Video Observations

Upward Cases
June 15th
 +CG triggers upward lightning from a
turbine blade at its 3 o’clock position
 +CG triggers upward lightning from 2
turbines and a radio tower simultaneously
September 7th
 Distant +CG or overhead cloud flash
triggers simultaneous upward lightning
from two turbines
 Return-stroke-like process observed
Video Observations

Upward Lightning Video | 7 Sep. 2012

• All upward cases occurred in trailing stratiform regions associated with east-
propagating squall lines or large multi-cellular storms
June 15th
05:37
June 15th
06:54
Sep. 7th
17:30
Upward Lightning Environment

• SCADA measured currents were time-correlated with NLDN reports
• Allowed evaluation of NLDN detection and location accuracy
• Median / Mean location errors were 100 m / 240 m
• Blade current measurements
• 26 total; 19 on east side (no video), 7 on west side (5 with video)
• All were associated with CG strokes reported by NLDN (24 were likely
downward direct attachment, other 2 had large +CG triggering events nearby)
0
10
20
30
40
50
60
70
80
90
100
0
1
2
3
4
5
6
7
8
9
10
50
150
250
400
600
800
1000
1200
1400
Cumulative
Count
Distance (m)
SCADA Event Location Error
0
10
20
30
40
50
60
70
-120 -90 -60 -30 0 30 60 90 120
SCADACurrent
NLDN Peak Currnet
Peak Current Comparison
MW West
MW East
SCADA Observations

• Computed for the whole wind farm using historic data (N turbines):
• R = 276 m
• Where hub height = 80 m and blade tip height = 125 m
• Literature indicates that the attractive radius should be 160 – 200 m for a tower
this height
• Computed for the radio tower inside the wind farm to compare
• R = 300 m
• Where tower height = 231 m
• Literature indicates that the attractive radius should be ~300 m for a tower this
height
• NALDN behavior similar with 1 of 2 strikes within 300 m attaching and 1 of 8
within 500 m
Attractive Radius

• All lightning attachments to turbines were to the blades
• NLDN detection efficiency for downward lightning attachment was 100%
• Upward lightning attachment to wind turbines was most-easily initiated by nearby +CG
strokes and had low currents with 100% detection efficiency
• However, 0% detection efficiency for “return-stroke-like” current measured in the blades
• No correlation observed between the lightning peak current and resultant damage to turbine
blades
• Turbine lightning protection systems work well until they do not
• Wind turbines may have a larger attractive radius for lightning
• Space charge around moving blades may be inhibited
• It is advisable to inspect wind turbine lightning protection systems regularly to minimize the
risk of mechanical damages to the turbine and related repairs
Research Conclusions

Lightning Data for Wind Farm
Operations
 Lightning data from the NALDN allows typical wind
farm operators to find 25-30% more damaged blades
than when they do blanket ground searches
following storms
 Typical inspection costs are 300 USD per turbine in
addition to mobilization costs
 Early identification can keep repair costs below 10
kUSD as opposed to over 100 kUSD for full blade
repair
 Costly wind turbine downtime is also minimized – 1,200
USD per day for a 2 MW turbine
 Blade repairs need to have the appropriate wind and
temperature conditions

Thank You!!!
 Based in Boulder, Colorado, USA
 5+ years experience in wind energy applications
 10+ years experience in lightning data applications
 nic.wilson@vaisala.com
Nic Wilson
Energy Regional Segment
Manager, Americas
vaisala.com/renewable
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Energy Webinar Series 2014 - Mitigating Lightning Impacts on Wind Farms

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Energy Webinar Series 2014 - Mitigating Lightning Impacts on Wind Farms