Volume 2, No. 9
September, 2024 p-ISSN 3032-3037|
e-ISSN 3031-5786
Danu
Triatmoko1*, Muhammad Arsyad2, Pariabti Palloan3
Physics Study
Program, Postgraduate Program, Makassar State University, Indonesia
E-mail:danu.triatmoko@bmkg.go.id,m_arsyad288@unm.ac.id
This research aims to evaluate the potential
for wind energy in Kolaka Regency using ERA5-Land reanalysis data from the
output of the European Center for Medium-Range Weather Forecasts (ECMWF) model,
which has a spatial resolution of 9 km with hourly temporal resolution for the
period from 2001 to 2020. This research also compared the quality of ERA5-Land
reanalysis wind speed data on data from nearby meteorological stations using
statistical assessment methods. The analysis results reveal that the highest average
wind speed was discovered at a height of 80 to 150 meters with a range of 4.99
to 5.93 m/s. The spatial distribution map of wind power density indicates that
the energy potential at a height of 80 to 150 meters can reach 60 to 170 W/m2.
The largest wind energy potential in Kolaka Regency can be generated in the DJF
period (December-January-February) with the highest average monthly wind power
density in January and the JJA period (June-July-August) with the highest
average in July. In general, Kolaka Regency can be classified as an area with
first-class wind energy potential, so it tends to be more suitable for the
development of small-scale power plants. The suitable locations for developing
small-scale wind power plants in Kolaka Regency are the southern Pomalaa coast
and the Tanggetada coast because both locations have better wind energy sources
than other areas.
Keywords:Reanalysis data,
ERA5-Land, wind power density, wind energy potential.
Wind energy is an alternative
energy to replace fossil energy which has advantages including being
environmentally friendly, not polluting CO2 emissions, unlimited resources,
reliable and easy to find.
A significant increase in global wind energy capacity occurred from 2008
to 2018. In 2008, global wind energy capacity was only 121 gigawatts (GW) and
increased to 591 GW in 2018, around 568.4 GW operates onshore and the rest is offshore.
This makes wind the second largest source of renewable energy after hydro
energy which reaches a capacity of 1,132 GW
According to
Utilization of wind energy as new renewable energy (EBT) in Indonesia is
still relatively low, only around 0.1% of the total wind energy potential of
60.6 GW
One of the regions in Indonesia that has large wind energy potential is
Sidrap and Jeneponto in South Sulawesi. Currently both areas have also had PLTB
built and are operating commercially. Sidrap PLTB has a capacity of 75 MW from
30 installed wind turbines with a blade length of 57 meters and a turbine hub
height of 80 meters
The potential of wind energy for electricity generation is very dependent
on the distribution of wind speed throughout the year
To identify the assessment of wind energy potential and determine the
optimal turbine hub height, characterization of the vertical wind speed profile
is required
According to
The use of ERA5 or ERA-Interim data from the European Center for Medium-Range
Weather Forecasts (ECMWF) reanalysis model has been widely used in studies
assessing the potential for offshore and onshore wind energy in several
countries.
Meanwhile, in this research, the ECMWF reanalysis data used to evaluate
the assessment of wind energy potential is ERA5-Land. Utilization of ERA5-Land
reanalysis wind speed data in research
According to
1.
Wind Speed Data Quality TestReanalysisERA5-Land
To measure the quality of the ERA5-Land reanalysis
wind speed data against meteorological station observation data, validation of
the average wind speed at a height of 10 meters was carried out over a 20 year
period (2001-2020). Validation was carried out by comparing the distribution
pattern of ERA5-Land reanalysis data with observation data from the Sangia
Nibandera Kolaka Meteorological Station. In addition, the statistical metric
parameter values RMSE, MAE, MBE, and STDE were calculated to
measure the deviation or error values of the observation data.
a.
Comparison
To compare observation data with the ERA5-Land
reanalysis, grids 661, 699, and 736 were chosen because they have the closest
distance to the location of the Sangia Nibandera Kolaka Meteorological Station,
which is less than 15 km (see Figure 3.1). Value comparison
The
graphic pattern in Figure 4.1b shows
OngridsERA5 reanalysis-Landstudied, the lowest seasonality occurred at
MAM for the location
b.
Wind direction comparisonreanalysisERA5-Land and observations
To compare
the distribution of wind direction at a height of 10 meters from observations
with ERA5-Land reanalysis, the data used is only for the period 2014 to 2020.
This is due to the availability of data from hourly wind direction observations
at the Sangia Nibandera Kolaka Meteorological Station. The ERA5-Land reanalysis
wind direction data compared to observational data in this study is data at
grid locations 661, 699, and 736.
The percentage level of dominance of the West wind
direction reached 21.51% and the East wind direction reached 20.01% for
observations from the Sangia Nibandera Kolaka Meteorological Station.
Meanwhile, the ERA5-Land reanalysis wind direction on grids 661, 699, and 736,
the percentage of dominance of the West wind direction reached 33.65%, 37.39%,
and 34.44% respectively and the East direction reached 20.24% respectively. ,
26.19%, and 30.90%, as shown.
c.
Statistical test analysis of wind speedERA5-Land reanalysis
Evaluation
of the performance of the average wind speed at a height of 10 meters from the
ERA5-Land reanalysis was carried out using statistical tests to measure error
values against reference data from meteorological stations.
Analysis of statistical metrics such as RMSE, MAE, MBE, and STDE shows that
STDE values of more than 0.5 m/s only occur in January and June
in some grids, with the highest value in grid 736 in January. The highest RMSE
and MAE metrics were also found in the JJA period in all grids, with the
highest value in grid 736. In general, the average STDE value for the seasonal
period at the three grid locations was below 0.5 m/s, while the MBE value
showed that ERA5-Land wind speed tends to be overestimated compared to
observational data.
2.
ERA5-Land Reanalysis Wind Speed
Extrapolation
ERA5-Land reanalysis estimation results for the
2001-2020 period for the entire grid in the Kolaka Regency area. Seasonal
increases across the ERA5-Land reanalysis grid generally occur at DJF and JJA with
the highest average wind speeds reaching 2.58 m/s and 2.68 m/s at grid
locations 736 and 621, respectively.
Seasonal
declines occurred in MAM and SON, as seen in Figure 4.5b.
Next, the ERA5-Land reanalysis wind speed at a height
of 10 meters is extrapolated for heights of 30, 50, 80, 100, and 150 m using
equations (2.4) and (2.7). Average wind
speed ERA5- reanalysisLandThe extrapolation results were analyzed based on monthly and seasonal
variations during the 2001-2020 period. In this study, the average wind speed
at altitude30,
50, 80, 100 and 150 meach is denoted by ,
a.
Monthly
average wind speed
Extrapolated monthly average wind speed at heights of
30, 50, 80, 100 and 150 m during the 2001-2020 period. The highest average wind
speed in January and March at heights of 30, 50, 80, 100, and 150 moccurred at grid
location 736.
The highest average wind speed from April
to June during the 2001-2020 period at heights of 30, 50, 80, 100, and 150 m
occurred at grid location 621. The average wind speed in April reached 2.41
m/s, 2 .82 m/s, 3.27 m/s, 3.51 m/s, and 3.99 m/s for , , , , and
For November, the average wind speed values
reached 2.82 m/s, 3.28 m/s, 3.77 m/s, 4.03 m/s, and 4.55 m/s
respectively for
b. Seasonal average wind speed
Histogram during the DJF period, the highest ERA5-Land
reanalysis seasonal average wind speed in the Kolaka Regency area for heights
of 30, 50, 80, 100, and 150 m occurred at grid location 736 with , , , , and
each reached an average value -averages of 3.48 m/s, 4.01 m/s, 4.56 m/s, 4.85
m/s, and 5.43 m/s.
Meanwhile, , , , and the lowest occurred at grid
location 506 with seasonal average wind speeds reaching 1.20 m/s, 1.46 m/s,
1.75 m/s, 1.91 m/s, and 2 .23m/s. For the MAM period, the lowest and highest
seasonal average wind speeds also occur at the same grid locations as the DJF
period, namely grids 506 and 736. During the MAM period, the lowest average
wind speeds are at heights 30, 50, 80, 100, and 150 meters were recorded at
1.18 m/s, 1.44 m/s, 1.72 m/s, 1.88 m/s, and 2.19 m/s respectively, while the
highest speed at the same height the same reaching 2.71 m/s, 3.16 m/s, 3.64
m/s, 3.90 m/s, and 4.41 m/s. During the JJA period, there was an increase in
average wind speed, with the highest values at heights of 30, 50,
80, 100 and 150 meters reaching 3.63 m/s, 4.19 m/s, 4.77 m/s, 5.08 m/s, and
5.69 m/s, and the lowest at 1.45 m/s, 1.75 m/s, 2.08 m/s, 2.26 m/s, and 2.63
m/s. For the SON period, the average wind speed decreased compared to JJA, with
the highest values at 2.92 m/s, 3.39 m/s, 3.90 m/s, 4.16 m/s, and
4.69 m/s and the lowest at 1.39 m/s, 1.67 m/s, 1.99 m/s, 2.16 m/s, and 2.51
m/s.
3.
Wind Power Density at Height 10, 30, 50,
80, 100, and 150 m
In this research, the wind power density or WPD that
will be studied is
To calculate the WPD amount at a height of 10 meters
or
a.
Monthly average
The highest WPD in January and March occurred at grid
location 736.
Meanwhile, the highest WPD for the April-June period
occurred at grid location 621. April WPD reached 3.1 W/m2, 9.0 W/m2, 14.7 W/m2,
23.1 W/m2, 28.6 W/ m2, and 42.4 W/m2 respectively for
During the MAM period, the lowest average wind
speeds at heights of 30, 50, 80, 100, and 150 meters were recorded at 1.18 m/s,
1.44 m/s, 1.72 m/s, 1 .88 m/s, and 2.19 m/s, while the highest speed at the
same height reached 2.71 m/s, 3.16 m/s, 3.64 m/s, 3.90 m/s, and 4.41 m/s.
During the JJA period, there was an increase in average wind speed, with the
highest values at heights of 30, 50, 80, 100 and 150 meters
reaching 3.63 m/s, 4.19 m/s, 4.77 m/s, 5.08 m/s, and 5.69 m/s, and the lowest
at 1.45 m/s, 1.75 m/s, 2.08 m/s, 2.26 m/s, and 2.63 m/s. For the SON period,
the average wind speed decreased compared to JJA, with the highest values
at 2.92 m/s, 3.39 m/s, 3.90 m/s, 4.16 m/s, and 4.69 m/s and the
lowest at 1.39 m/s, 1.67 m/s, 1.99 m/s, 2.16 m/s, and 2.51 m/s.
4.
Spatial Distribution of Wind Energy
Potential at Height 10, 30, 50, 80, 100, and 150 m
The results of wind power density or WPD calculations
on each ERA5-Land reanalysis grid (Figure 3.1) are interpolated using the QQIS
application for heights of 10, 30, 50, 80, 100 and 150 m so that monthly
average spatial distribution patterns can be depicted. and seasonality of wind
energy potential in Kolaka Regency.
a.
WPD at a height of 10 meters
Spatially, most areas of Kolaka Regency show that the
monthly and seasonal average wind power density at a height of 10 meters is
below 10 W/m². The highest average, both monthly and seasonal, was identified
as reaching 10-20 W/m² in January, June, July and August as well as during the
DJF and JJA periods. Locations with wind power density of 10-20 W/m² in January
include Padamarang Island, Wundulako, Pomalaa, Tanggetada, Watubangga,
Polinggona and Toari Districts. In June, the area includes Padamarang Island,
Pomalaa Coast, Tanggetada Coast, and the Samaturu border with Latambaga. During
July, the area with dense wind power extends to the Samaturu Coast, Wundulako,
Padamarang Island, Pomalaa, Tanggetada, Watubangga, Toari, and the western part
of Polinggona. In August, these areas include the Toari Coast to Pomalaa, the
western part of Polinggona, Padamarang Island, and the Samaturu border with
Latambaga. For the DJF and JJA periods, the highest seasonal wind power density
reaches 10-20 W/m² on the Tanggetada Coast and the Watubangga, Tanggetada and
Pomalaa Coasts.
b.
WPD at a height of 30 meters
The monthly average wind power density at a height of
30 meters in Kolaka Regency reaches the highest 40-50 W/m² in January and July,
with the main areas on the Tanggetada Coast in January and the southern part of
the Pomalaa Coast as well as Padamarang Island to Maniang Island in Wundulako
District in July. Seasonally, the highest average wind power density of 20-30
W/m² occurs during the DJF and JJA periods, with distribution in the DJF
covering Padamarang Island, Maniang Island in Wundulako District, Pomalaa,
Tanggetada, Watubangga, Polinggona, and Toari, while in JJA, the area with this
value extends along the coast from Samaturu to Baula, and includes Padamarang
Island, Maniang Island, Pomalaa, Tanggetada, Polinggona, Watubangga and Toari.
c.
WPD at a height of 50 meters
At a height of 50 meters, the highest monthly average
wind power density occurs in January and July, reaching 60-70 W/m², with the
main areas on the Tanggetada Coast and around the Pomalaa border with
Tanggetada in January, as well as on Padamarang Island to Maniang Island in
Wundulako District, and the southern part of the Pomalaa Coast to Tanggetada in
July. Seasonally, the highest wind power density only reaches 40-50 W/m² in the
DJF and JJA periods, with distribution in the DJF covering the Pomalaa and Tanggetada
borders, the Tanggetada Coast to Watubangga, and in the JJA identified on the
Samaturu and Latambaga border coast, eastern part of the island Padamarang to
Maniang Island in Wundulako District, the southern part of the Pomalaa Coast,
as well as the Tanggetada Coastal area to Watubangga, the border of Watubangga
and Toari, and the western part of Polinggona.
d.
WPD at a height of 80 meters
There is a monthly average wind power density at a
height of 80 meters which reaches 90-100 W/m2, namely in January and July. The
average size in January reaches 90-100 W/m2 on the Tanggetada Coast. Apart from
the Tanggetada Coast, there are areas with an average of 90-100 W/m2 in July,
namely the southern Pomalaa Coast and Padamarang Island to Maniang Island,
Wundulako District.
The amount reaching 60-70 W/m2 occurs during the DJF
and JJA seasons. The area in Kolaka Regency which has the highest average of
60-70 W/m2 in both seasonal periods is the same as the area which has the
highest seasonal average wind power density at a height of 50 meters.
e.
WPD at a height of 100 meters
Based on the area in Kolaka Regency that has the
highest monthly average wind power density at a height of 100 meters is the
Tanggetada Coast which was identified in January. Meanwhile, locations
identified as having the highest average in July include the southern part of
the Pomalaa Coast and Padamarang Island to Maniang Island, Wundulako District
and the Tanggetada Coast, as shown in Figure 4.20. These locations were
identified as having an average of 110-120 W/m2.
For seasonal averages, the highest average in Kolaka
Regency reaching 70-80 W/m2 was identified as occurring during the DJF and JJA
seasons, as seen in Figure 4.21. Figure 4.21 shows that there are areas that
have an average of 70-80 W/m2 in the DJF period, including the southern part of
the Pomalaa Coast, the Tanggetada to Watubangga Coast, the border of Watubangga
and Toari, and the western part of Polinggona.
Meanwhile, during the JJA period, it was found on the
border coast of Samaturu and Latambaga, Padamarang Island to Maniang Island,
Wundulako District, the southern part of the Pomalaa Coast, the Tanggetada,
Watubangga and Toari Coasts, as well as the western part of Polinggona.
f.
WPD at a height of 150 meters
Based on spatial distribution maps
For areas in Kolaka Regency that are identified as
having
For regions that have
1.
Wind Speed
Data QualityReanalysisERA5-Land
Based on the
graph in Figure 4.1a, the monthly average fluctuation of wind speed at a height
of 10 meters for the three ERA5-Land reanalysis grid locations is different
from the observation results, namely from August to December. Figure 4.1a shows
a pattern of decreasing average wind speed at the three ERA5-Land reanalysis
grid locations which occurred from August to November and increased in
December. Meanwhile, data from the Sangia Nibandera Kolaka Meteorological
Station shows that the increase occurred from August to September and decreased
from October to December.
For the seasonal
pattern in graph Figure 4.1b, the average wind speed from the ERA5-Land
reanalysis data has a pattern almost similar to the distribution pattern from
the average wind speed data from the Sangia Nibandera Kolaka Meteorological
Station. Significant differences in average wind speed fluctuations occur
during the SON period, namely during the transition from the dry season (JJA)
to the rainy season (DJF).
Differences in
ERA5-Land reanalysis wind speed fluctuations compared to monthly and seasonal
average Sangia Nibandera Meteorological Station observations indicate the
inability of the ERA5-Land reanalysis model to capture topographic effects and
surface roughness that influence surface wind circulation patterns and local
weather interactions that occur in the Regency. Kolaka is entering the
transition from the dry season to the rainy season or during the period from
August to December.
The results of
the evaluation of wind direction in Kolaka Regency at a height of 10 meters are
dominated by the West and East directions. This can be seen from the windrose
diagram comparison between Sangia Nibandera Meteorological Station data and
ERA5-Land reanalysis data (Figure 4.2). The dominance of the two wind
directions is also reinforced by the high percentage of frequency distribution
in the West and East directions when compared to other directions.
Analysis of the
performance of the wind speed model at the ERA5-Land reanalysis grid locations,
namely grids 661, 699, and 736, the highest RMSE and MAE values
in the monthly and seasonal periods range from 0.50 m/s to 1.31
m/s respectively. and 0.46 m/s to 1.01 m/s. This value is still below the error
threshold for wind speed models of ≤ 2 m/s. The average MBE values
for the three ERA5-Land reanalysis grid locations tested were
0.12 m/s, 0.10 m/s, and 0.77 m/s, respectively. The MBE is positive, meaning
that the ERA5-Land reanalysis data tends to overestimate the observation data.
2.
Average
Wind Power Density at ERA5-Land Reanalysis Grid Locations
The wind speed distribution pattern in Kolaka Regency based on ERA5-Land
reanalysis wind speed shows that an increase in wind speed occurs in January
and July (Figure 4.1a). Meanwhile, the seasonal period occurs during DJF and
JJA (Figure 4.1b). This shows that the greatest potential for wind resources in
Kolaka Regency can be generated during that time period.
The largest monthly average wind power density at heights of 10, 30, 50,
80, 100, and 150 m from the ERA5-Land reanalysis grid data occurs in January
and July. The locations with the highest wind energy potential that month in
Kolaka Regency are located on grids 736 and 621.
The highest average wind power density in January at heights of 10, 30,
50, 80, 100, and 150 m respectively reached 16.7 W/m2, 40.3 W/m2, 60.9 W/m2, 89
.0 W/m2, 106.6 W/m2, and 147.9 W/m2 with average wind speeds of 2.87 m/s, 3.84
m/s, 4.40 m/s, 4, 98 m/s, 5.29 m/s, and 5.89 m/s. For July at the same
altitude, the highest average wind power density reached 14.1 W/m2, 35.2 W/m2,
53.7 W/m2, 79.4 W/m2, 95.6 W/m2 , and 133.9 W/m2 with average wind speeds of
2.82 m/s, 3.81 m/s, 4.38 m/s, 4.99 m/s, 5.30 m/s, and 5.93 m/s.
In the seasonal period, the largest wind energy potential in Kolaka
Regency at heights of 10, 30, 50, 80, 100 and 150 m is produced during the DJF
and JJA periods. The ERA5-Land reanalysis grid location which has the highest
average wind power density in the season period is located in the same grid
location as before, namely grids 736 and 621.
The average wind speed for the DJF period at heights of 10, 30, 50, 80,
100, and 150 m respectively reached 2.58 m/s, 3.48 m/s, 4.01 m/s, 4.56 m/s,
4.85 m/s, and 5.43 m/s which produces an average wind power density of 11.2
W/m2, 28.3 W/m2, 43.7 W/m2, 65, 2 W/m2, 78.8 W/m2, and 111.3 W/m2. In the JJA
period, the average wind power density reached 12.0 W/m2, 30.3 W/m2, 46.7 W/m2,
69.5 W/m2, 84.0 W/m2, and 118.5 W/m2 with an average wind speed at each height
of 2.68 m/s, 3.63 m/s, 4.19 m/s, 4.77 m/s, 5.08 m/s, and 5.69m/s.
Based on rThe lowest wind
power throughout the year in Kolaka Regency at altitudes of 10, 30, 50, 80,
100, and 150 m is in the northern region, precisely at grid location 504
located in Iwoimendaa District, grids 505, 506, 543, and 544 are located at
Wolo District, as well as grid 545 are located in Samaturu District. Meanwhile,
the highest wind power density is at grid locations 621 and 736 around the
central part of Kolaka Regency, respectively located in Latambaga and Pomalaa
Districts.
3.
Analysis
of the Spatial Distribution of Wind Energy Potential in Kolaka Regency
Based on spatial
distribution maps of monthly (Figures 4.13, 4.15, 4.17, 4.19, 4.21, and 4.23)
and seasonal (Figures 4.14, 4.16, 4.18, 4.20, 4.22, and 4.24) average wind
power density at heights 10, 30, 50 , 80, 100, and 150 m, it was identified
that the largest wind energy potential in Kolaka Regency occurs in January and
July and during the DJF and JJA seasons.
The wind power density
distribution map shows the highest monthly average WPD magnitudes in Kolaka
Regency at heights of 10, 30, 50, 80, 100, and 150 m respectively reaching10-20
W/m2, 40-50 W/m2, 60-70 W/m2, 90-100 W/m2, 110-120 W/m2, and 150-170 W/m2.
Meanwhile, during the season it reaches 10-20 W/m2, 20-30 W/m2, 40-50 W/m2,
60-70 W/m2, 70-80 W/m2, and 100-120 W/m2. In general, the height that has quite
large energy potential in Kolaka Regency is at an altitude of 80 to 150 meters
with an average WPD reaching 60 W/m2 to 170 W/m2.
The evaluation results based on wind energy potential
for heights of 10, 30 and 50 m in Kolaka Regency are classified as class 1 type
with the very poor category because the average WPD values at
these heights are respectively included in the 0-100 W class. /m2, 0-160 W/m2,
and 0-200 W/m2
From the monthly and seasonal average WPD spatial
distribution map at heights of 10, 30, 50, 80, 100, and 150 m, locations with
sufficient wind energy potential that are suitable for the development of
small-scale wind power plants in Kolaka Regency are located in the area
Southern Pomalaa Coast and Tanggetada Coast. Meanwhile, the northern areas of
Kolaka Regency, such as Wolo and Iwoimendaa, are less suitable for developing
wind power plants because they have low average wind speeds.
CONCLUSION
Based on the analysis of data
processing results, the conclusions of this research are: first, the ERA5-Land
reanalysis data is quite representative for the study of wind energy potential
in Kolaka Regency, with wind speed distribution patterns similar to Sangia
Nibandera Kolaka Meteorological Station data and adequate statistical metric
test results, although tends to overestimate. Second, the highest wind power
density is found at grid locations 736 and 621, with the highest values
at heights of 80, 100, and 150 m, indicating an increase in wind
power density as altitude and wind speed increase. Third, the greatest
potential for wind energy in Kolaka Regency occurs in January and July as well
as the DJF and JJA periods, with a class 1 or very poor category, so it is more
suitable for small-scale power generation, with the southern part of the
Pomalaa Coast and the Tanggetada Coast having more potential. compared to the
North. Suggestions for further research include using data with better
resolution and adding parameters that influence wind energy potential such as
air density, topography and land cover. This research can also be a basis for
consideration for planning the development of wind power plants in Kolaka
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