Rain Erosion Maps for Wind Turbines Based on Geographical Locations: A Case Study in Ireland and Britain

Abstract

Erosion rates of wind turbine blades are not constant, and they depend on many external factors including meteorological differences relating to global weather patterns. In order to track the degradation of the turbine blades, it is important to analyse the distribution and change in weather conditions across the country. This case study addresses rainfall in Western Europe using the UK and Ireland data to create a relationship between the erosion rate of wind turbine blades and rainfall for both countries. In order to match the appropriate erosion data to the meteorological data, 2 months of the annual rainfall were chosen, and the differences were analysed. The month of highest rain, January and month of least rain, May were selected for the study. The two variables were then combined with other data including hailstorm events and locations of wind turbine farms to create a general overview of erosion with relation to wind turbine blades.

Full text

Vol.:(0123456789)
1 3
Journal of Bio- and Tribo-Corrosion (2021) 7:34
https://doi.org/10.1007/s40735-021-00472-0
Rain Erosion Maps forWind Turbines Based onGeographical Locations:
ACase Study inIreland andBritain
K.Pugh1 · M.M.Stack1
Received: 8 September 2020 / Revised: 15 December 2020 / Accepted: 1 January 2021
© The Author(s) 2021
Abstract
Erosion rates of wind turbine blades are not constant, and they depend on many external factors including meteorological
differences relating to global weather patterns. In order to track the degradation of the turbine blades, it is important to analyse
the distribution and change in weather conditions across the country. This case study addresses rainfall in Western Europe
using the UK and Ireland data to create a relationship between the erosion rate of wind turbine blades and rainfall for both
countries. In order to match the appropriate erosion data to the meteorological data, 2months of the annual rainfall were
chosen, and the differences were analysed. The month of highest rain, January and month of least rain, May were selected
for the study. The two variables were then combined with other data including hailstorm events and locations of wind turbine
farms to create a general overview of erosion with relation to wind turbine blades.
Keywords Wind· Turbine· Maps· UK· Ireland· Erosion· Rainfall· Composites· Testing
1 Introduction
Wind energy has become an increasingly popular choice
of renewable energy with many countries across the world
attempting to become carbon neutral [1]. This has resulted
in a major research focus within the wind energy sector,
addressing all aspects of energy conversion. This boom has
had a very significant impact on the design, manufactur-
ing and efficiency of the turbines and their blades [2]. One
common advance is to install much larger blades, however,
this is coupled with substantially greater tip velocities of
the blades. These increased velocities create a higher risk
of degradation of the leading edge due to impacts from rain
erosion [3]. With tip speeds from turbines reaching 300mph,
the repeated impact of raindrops is sufficiently energetic to
erode the material. The erosion rates of wind turbines have a
direct relationship to the environment they are erected. More
rainfall will result in more erosion of turbine blades [4].
Typically wind turbine farms are constructed in barren
locations due to land availability, wind speeds and away
from local beauty spots; however, this results in turbines
being subjected to harsh conditions and in some locations
heavy rainfall. Within this case study, data from the Met
Office [5, 6], Irish weather data [7] and experimental data
will be combined to map the UK and Ireland in terms of
erosion on wind turbine blades. This is being carried out
to display the relationship between the locations of wind
turbine farms and their environment. This will, in turn, also
aid in visualizing the wind farms that are at higher risk from
erosion degradation and will require more maintenance. This
is to mitigate failures and increase power output by keep-
ing the blades smooth and promoting greater aerodynamic
efficiency.
2 Methodology andResults
The procedure began by collating data from the Met office
and Irish weather data. With this data an average rainfall map
over the last 20years was created. It should be noted that
the turbine blades will inevitably experience varying rainfall
rates throughout the year, which will, in turn, result in vary-
ing erosion rates. To map this phenomenon, the months of
highest and lowest rainfall were chosen which were January
and May, respectively. Showing the two extremes of rainfall
months will provide more insight than a yearly average and
* K. Pugh
kieran.pugh@strath.ac.uk
1 Department ofMechanical Engineering, University
ofStrathclyde Glasgow, 16 Richmond St, GlasgowG11XQ,
UK

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allow for contrast to be observed between the 2months. The
result of this can be seen in Fig.3.
Upon the completion of this map an experimental pro-
cess in the Tribology laboratory at the University of Strath-
clyde was carried out to relate rainfall across the country
to the degradation of wind turbine blades. There are many
different ways to test for rain erosion [8]; however, the test
method used for this case study is the whirling arm setup
[9]. This consists of a large chamber with induced rainfall
from hypodermic needles; in the centre of the chamber is
a rotating arm which holds the material sample at the end.
Adjusting the rotational speed of the spinning arm will
adjust the impact velocity the sample encounters with the
water droplet. The experimental setup can be seen in Fig.1
and a schematic is shown in Fig.2.
The material used in this experiment was G10 epoxy
glass which is a similar glass fibre epoxy composite used
within the wind turbine manufacturing industry [10]. The
impact velocity was set to 60ms−1 as this will simulate the
leading edge of 2MW turbines with a diameter of 100m.
One of the assumptions that was made to relate the experi-
mental data to the weather data was that the wind turbines
were always turning when it was raining. Although this
might result in an overestimation in erosion, it is deemed
a worst-case scenario that has a possibility of occurring.
All the variables which were kept constant includ-
ing impact velocity, temperature and rainfall were all
calibrated before the experimental campaign began. The
impact velocity was calibrated using light transducer
which was held close to the rotating shaft where a thin
reflective strip was placed. A light source was focused
onto the shaft and the transducer would give an electri-
cal output when the light was reflected from the reflec-
tive strip each time it would rotate. The rain fall was cali-
brated by running the rain system for five hours and the
water tank which feeds the rig was weighed periodically
every 30min to calculate the water consumed and hence
the rainfall rate. The pump used was a peristaltic pump
which proved to be extremely reliable and hence outputted
50mm/h every 30min. The temperature inside the rig was
also measured and kept at 29°C, a temperature calibration
test was carried out during the calibration of the rainfall
where the temperature was measured using a probe inside
the chamber and a reading was taken every 30min for the
five hours and the temperature only fluctuated ± 1°C.
The same procedure was carried out for all samples
which included a 48-h drying period before measuring
the mass and kept in the same container to ensure the con-
ditions when the sample was drying were kept constant.
After the 48 drying period the samples were weighed on a
balance accurate to 0.00001g and the mass of the sample
was measured five times equally spaced out over one hour.
From this a measurement error of ± 0.001% and standard
deviation of 1.09E−05 was calculated for the neutral water
and a measurement error of ± 0.019% and standard devia-
tion of 1.16E−04 for the saltwater experiment.
The construction of the rainfall map (Fig.3) allows the
setup for the experiment to be finalised. The key to the
map displays: Below 50mm, 50mm, 75mm, 100mm,
150mm, 200mm, 300mm, 500mm and above 500mm.
The rainfall rate of the whirling arm rig is 50mm/h there-
for the time each sample exposed to rain erosion can be
determined, this is.
shown in Table1.
The chosen measurement for erosion is mass loss as a
percentage of the original sample. The mass of the test
material was measured before the experiment and after
each exposure time. This would result in a direct numeri-
cal relation between the average monthly rainfall and the
erosion as a mass loss.
Fig. 1 Whirling arm rain erosion rig
Fig. 2 Whirling arm schematic

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This methodology was repeated with saltwater instead of
rainwater to simulate offshore conditions. The saltwater used
was a 3.5% saline solution which most accurately describes
the seawater in the UK and Ireland [11]. The results and
errors can be seen in Table2
Fig. 3 The average rainfall in the months of January and May
Table 1 Exposure time in
erosion rig to achieve required
rainfall
Rainfall (mm) Exposure
Time
(min)
50 60
75 90
100 120
150 180
200 240
300 360
500 600
Table 2 Mass loss results from
erosion testing Exposure time
(min)
Cumulative rainfall
(mm)
Neutral water mass loss (%)
(± 0.001%)
Saltwater (3.5% saline
solution) mass loss (%)
(± 0.019%)
60 50 0.037 0.001
90 75 0.046 0.014
120 100 0.055 0.071
180 150 0.073 0.075
240 200 0.091 0.120
360 300 0.127 0.205
600 500 0.199 0.276

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3 Rainfall Map
The rainfall mostly averages between 50 and 500mm of
rain with some few areas showing more extreme rain. It
is clear that the month of May experiences considerably
less rain as it shows highs of 300mm whereas this rate is
fairly common in January. The areas of intensity are very
similar in both months with the west coast of Scotland
showing a high rainfall and also the west coast of Ireland,
predominantly the south west coast of Ireland displaying
very heavy rainfall. These are historically harsher climates
due to the prominent westerly wind from the Atlantic [12].
This leads to further erosion as the largest windfarms are
located in these areas due to the increased power output
from the consistent wind [13]. This is a very common
trade-off when building a windfarm as the conditions that
yield the most power generation are also the conditions
which deteriorate the turbine blades most rapidly, there-
fore the life of the turbine blade will be reduced [14].
Part of the experimental process was also to under-
stand sea water effects which help describe the erosion
behaviour of offshore wind turbines. This was completed
by running a saltwater solution (3.5% saline solution)
through the experimental rig to simulate offshore condi-
tions. Previous work on this topic by the current research
group showed similar results to the saltwater exposure in
this investigation. This had concluded that the saltwater
proved more erosive when subject to high velocity impacts
from the leading edge of the turbine blade and would cre-
ate larger, more destructive cracks and loss of material
from the sample [15]. The added effect of the more con-
sistent wind from offshore conditions with the sea water
climate is conducive to an erosive atmosphere and hence
a short life span of turbine blades. Offshore wind farms
have many other problematic characteristics including the
corrosive nature of sea water which will attack any metal-
lic parts and the anchoring of the structure to the seabed.
However, the remote locations and the large blade size
allows very significant energy capture [16]. Even though
offshore wind turbines encounter major drawbacks such as
increased levels erosion and corrosion, the advantage of
having the open space to build larger, more efficient wind
turbines with more consistent wind makes them economi-
cally viable [17].
4 Erosion Maps
Once the rainfall maps were created the link between
rainfall rate and erosion rate could be made as mentioned
previously. This allowed the same maps to be created with
the key displaying erosion as a percentage mass loss of a
theoretical turbine blade.
The results showed a maximum mass loss of 0.199%
which relates to 500mm of rainfall and a minimum
mass loss of 0.037% which relates to 50mm of rainfall.
Although mass loss is not the most precise measurement
for erosion when compared to imaging samples and iden-
tifying gauges, cracks and loss of material [18, 19]; it does
allow for a broader comparison between samples.
The measurement of mass loss can be loosely linked
to the efficiency of the turbine, which is also why this
measurement was used to map erosion across the UK and
Ireland. With all material lost from the wind turbine blades
it will affect the aerodynamic profile of the blades, with
more mass lost the greater the effect it will have. The dis-
turbed airflow over the blade will impede the performance
of the turbine. A damaged blade will require a higher air-
flow or blade angle to produce the same output [20]. This
has been proved experimentally within the literature which
considered the drag coefficients of compromised blades
[21] and also the microscopy of material subject to rain
droplets at high velocities [22].
The degradation of the sample should erode in three
distinct stages. The first is the initiation period; where the
sample is at its smoothest and difficult to penetrate, this
is when the turbine blades are brand new and operating at
optimal efficiency. Secondly is steady state erosion; where
the sample has been impacted by a critical number of drop-
lets to affect the surface roughness of the sample enough
to instigate more considerable erosion which continues at
a constant rate. It is during this stage that the turbine starts
to decline in efficiency. Lastly the third stage is the final
erosion region where the erosion rate decreases, however,
this is when the turbine blade is at its most vulnerable and
the erosion on the blades can begin to become structural
weak points [23]. It is important to locate areas of signifi-
cant erosion across the country as the timing of mainte-
nance to repair or replace blades is crucial in the optimisa-
tion of power production from wind turbine blades.
The rainfall data is only available on land, therefore
there was no offshore rain data to compare to the offshore
erosion data. From the experiments using saltwater (3.5%
saline solution) there was a higher mass loss at the higher
exposure times compared to the neutral water tests. To
compensate for this a border of approximately 10 miles
was created offshore around the islands and assumed to
be one grade above the adjacent onshore erosion rate. For
example, the mainland of Shetland displayed an erosion
of 0.046% mass loss therefor a 10-mile boundary off the
coast of Shetland was created displaying the next grade up
in the key which is an erosion of 0.055% mass loss. This
is displayed in Fig.4.

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5 Points ofInterest onErosion maps
Construction of these maps now allows for further com-
parison to be made including locations of major wind
farms and also areas of high hail rates which is displayed
in Fig.5. Even though the rainfall rate maps cover all
precipitation, it is important to locate areas of high hail
impact as these tribological actions can be detrimental to
its structural integrity. Although the probability of hail
striking wind turbine blades is very low and the dam-
age would be difficult to ascertain, and it could possibly
be masked as the outcome of heavy rainfall erosion, the
implications of hail impacts have been proven experimen-
tally to cause substantial damage. In a study looking into
ballistic ice impacts, it was shown that the impact would
delaminate and crack the composite material [24]. This
would not only create a weak point in the blade structure
itself but also create an initiation site for rain erosion to
occur and for crack propagation into the structure of the
blade. The areas of frequent hail are shown in Fig.5 as
the red overlay, and from the maps it is clear that the west
coast is more adversely affected by hail. Unfortunately,
there was limited data on hail in The Republic of Ireland;
therefore, assumptions on this issue for this area of the
map need to be treated with caution.
Also superimposed onto the map in Fig.5 is the loca-
tions of some large wind farms and the largest in Scotland,
England, Ireland, Wales, Northern Ireland and The Republic
of Ireland have been labelled [25]. This not only allows for
a comparison between the size of the various windfarms in
each region but also how adversely affected each one is by
the climate and the subsequent erosion. Most of the wind-
farms are in compromising locations but, as discussed previ-
ously, this is a trade-off between greater access to consistent
wind to the lifetime of the blades.
6 Areas Which May be Addressed inFuture
Work
There are some additional modifications which will help
optimise these maps when they are recreated with future
results. The main extension would be the use of additional
data to help aid the validity of the results and as mentioned
previously if enough datapoints are available then a dynamic
map could be potentially created.
There are many additions which could be made to the ero-
sion data and the weather data which could provide further
insight into geographical differences including the droplet
size, pH value and intensity which would aid the erosion
Fig. 4 The monthly erosion rates in January and May

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data. These data sets however are difficult to pinpoint as they
are mostly stochastic.
The most important evolution for these maps would
be the inclusion of offshore rain data to include the large
offshore wind farms that could not be included within this
study. With almost half of the UK wind energy coming from
offshore wind farms [26] the inclusion of this data would
provide a more thorough overview of the erosion of the
UK and Ireland’s wind turbine blades and hence the loss in
power due to aerodynamic inefficiencies.
7 Conclusions
In conclusion, the data from the rainfall within the UK and
Republic of Ireland were formatted together to produce an
Ireland/Britain map showing the average rainfall across the
two countries in both January and May averaged over the
last 20years. These maps were then used as the basis for an
erosion experiment converting the rainfall to exposure time
within the erosion rig. These results were then arranged on
the map to display the degradation of the turbine blades from
rain droplet impacts. This was coupled by a saltwater erosion
experiment that used 3.5% saline solution as the droplets to
simulate offshore wind turbines which are subject to being
eroded by sea water (salt spray corrosion enhanced erosion)
in the atmosphere. These two maps were then superimposed
to display areas of frequent hail and the locations of each
country’s largest wind turbine farm. This was carried out
in an attempt to visualise the erosion patterns across both
Ireland and the UK.
It is clear that the general trend consists of greater ero-
sion in the west coast of both the UK and The Republic of
Ireland with the highest erosion areas being the north west of
Scotland where the land tends to be at a higher elevation and
also the south west of Ireland where there is no protection
from the prevailing wind over the Atlantic.
The locations of frequent hailstorms across the UK and
the republic of Ireland could be considered stochastic, how-
ever, the locations of some major wind farms overlap with
frequent hail; this can be seen predominantly in Northern
Ireland. This overlap could potentially reduce the lifetime of
the turbine blades at an increased rate due to more powerful
impacts from hailstones.
Fig. 5 The monthly erosion rates in January and May with overlays of major wind turbine farms and areas of frequent hail

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These mapping methods have potential to be used in life-
time modelling of wind turbine blades and have the possi-
bility to be developed into a dynamic map that can display
changes in new wind farms and changing climates. This is
particularly important due to weather changes over long
periods of time on the annual cycle.
Acknowledgements The authors would like to acknowledge the sup-
port of the Interreg (Northern Ireland—Ireland—Scotland) Special EU
Programmes Grant No SPIRE2_INT-VA-049 ‘‘Storage Platform for the
Integration of Renewable Energy (SPIRE 2)’’.
Compliance with Ethical Standards
Conflict of interest On behalf of all authors, the corresponding author
states that there is no conflict of interest.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
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