off-shore wind potential in cyprus: towards an integrated ...template design © 2008 4.7 4.9 5.1 5.3...
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35.75 4.7 4.9 5.1 5.3 5.4 5.7 5.8 5.5 5.1 4.9 4.7 4.7
35.50 5.0 5.1 5.4 5.2 5.1 5.1 4.8 4.5 4.7 4.7 4.6 4.6
35.25 4.8 4.8 4.3 3.7 2.8 2.4 2.2 2.5 3.9 4.3 4.5 4.6
35.00 4.6 4.1 3.0 2.0 1.8 1.8 2.0 2.8 4.2 4.6 4.6 4.7
34.75 4.8 4.3 3.3 2.5 2.6 3.5 4.1 4.7 4.9 4.8 4.9 4.9
34.50 5.1 5.0 4.9 4.4 4.5 4.7 5.2 5.1 5.2 5.0 5.0 5.1
32.00 32.25 32.50 32.75 33.00 33.25 33.50 33.75 34.00 34.25 34.50 34.75
1.50 2.05 2.60 3.15 3.70 4.25 4.80 5.35 5.90 6.45 7.00
wind speed average (m/s) at 10 m
Off-shore wind potential in Cyprus: Towards an integrated representative
geospatial database
Evangelos Akylas1,2, Elias Gravanis1,2, Andreas Nikolaidis1,3, Constantinos F. Panagiotou1,2, Christodoulos Mettas1,2, Phaedon Kyriakidis1,2 and Diofantos Hadjimitsis1,2
1 Cyprus University of Technology, Dept. of Civil Engineering and Geomatics, Limassol, Cyprus ([email protected]) , 2 Eratosthenes Centre of Excellence of the Cyprus University of Technology, 3 Oceanography Centre of the University of Cyprus
Introduction
Cyprus' energy balance today depends to a large
extent on imports of petroleum products for energy
production. This has an impact on both the economy
and the environment of the island. The contribution of
renewable energy sources (RES) in Cyprus, although
exhibiting considerable potential, still remains limited.
Specifically, renewable energy sources today account
for less than 9% of the country's total gross energy
consumption.
This work contributes to the study of the off-shore
wind power being present the island. It focuses on
the creation of an integrated geospatial database for
the study of wind characteristics above the coasts
and offshore of Cyprus using measurements from
meteorological stations, data from the European
database with horizontal analysis 25x25 km, and 24-
hour forecasts from the Open Skiron meteorological
model in 5x5 km spatial resolution. In particular, the
analysis take advantage of wind measurement from
meteorological stations in coastal Cyprus areas (fig.
1), as well as information on wind values from
forecasting models and databases (fig. 1) to record
an initial reference distribution in space and time.
Re-analysis data ERA5/ECMWF
The standard deviation of the wind speed is about half
the average value and the maxima about 10 m/s above
the land and 20 m/s above the sea. In fact, Cyprus is
located in the eastern Mediterranean between latitudes
of 34.6o and 35.6o north, and longitudes of 32o and 34.5o
east. During the rainy season (November to March)
Cyprus is frequently suffered by depressions moving
eastwards across the Mediterranean Sea, in addition to
troughs that extend from the continental depression
commonly centered over Asia during the dry season.
Prevailing winds in Cyprus are mostly low to medium in
speed; very strong winds (wind speeds faster than 34
knots) are rare, mainly seen in windward areas.
One of the main sources of information are the re-
analysis wind data obtained from ERA5/ECMWF. The
data covers the period from 2000 – present on an
hourly basis with a horizontal resolution of 25x25 km
(72 grid points within the analysis area), at 10 m AGL
as shown in the figures below. The typical average
speed is about 4.5 m/s above the sea and 2 m/s
above continental areas. The southern coastal parts
appear slightly more windy compared to the rest
areas.
Comparison with meteorological measurements
Selected bibliography and references
Regarding the mean wind speed over the sea, the
meteorological model provides fair predictions,
estimating 5 to 10% lower speed values, except for
the east coast where the model underestimates the
speed up to 20% compared to the re-analysis data.
In contrast to ECWMF estimations of higher values
at the North part of the sea region than the South
Part, Open-Skiron reveals a more uniform behavior.
However, much larger discrepancies are observed
over the land. Actually, an inverse behavior is
observed, in which the general circulation is very
high above the land and mildly weaken above
the sea. This picture has to be further tested
using meteorological observations in the future.
Comparisons with in-situ wind measurements by the
Cyprus meteorological service exhibits a reasonable
agreement in some cases, given the low spatial
resolution of the modeled data.
➡ Two (2) floats were operational:
OPTIONAL
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OPTIONAL
LOGO HERE
[1] Akylas E., Tombrou M., Panourgias J. and Lalas D. (1997). The use of common meteorological predictions in estimating short term wind
energy production in complex terrain. In: Watson R, editor. Proceedings of European wind energy conference, Dublin Castle, Ireland, 1997. p.
329-32.
[2] Akylas E., Lalas D. P., Pesmajoglou S., Sakellario N. and Tombrou M. (1999). Investigation of the effects of wind speed forecasts and
economic evaluation of the increased penetration of wind energy for the island of Crete. In EWEC’99, p. 1074-1077.
[3] Akylas E. and Tombrou M., Reconsidering a generalized interpolation between the Kansas type formulae and free convection forms,
Boundary-Layer Met. 15, 2005, 381
[4] Akylas E., Zavros P., Skarlatos D. and M. Fyrillas (2010). Weibull distribution and wind speed timeseries, 3rd International Conference of the
ERCIM, 10-12 December 2010, London, UK, abstract E756.
[5] Beller C. (2009). Urban wind energy-state of the art 2009. Danmarks Tekniske Universitet, Risø Nationallaboratoriet for Bæredygtig Energi.
[6] Chompoo-inwai C., Leelajindakrairerk M., Banjongjit P. F., and Wei-Jen L. (2008). Design optimization of Wind Power planning for a country
with low– medium–wind–speed profile. IEEETrans. Indus. Applic. 44:1341–1347.
[7] Cohen C., (1973). The Reflected Weibull Distribution. Technometrics,Vol. 15, No. 4 (Nov., 1973), pp. 867-873
[8] Jacovides C. P., Theophilou C., Tymvios F. S. & Pashiardes S. (2002). Wind statistics for coastal stations in Cyprus. Theoretical and applied
climatology, 72(3-4), 259.
[9] Kastanas I., Georgiou A., Zavros P. and E. Akylas (2014). An integrated GIS-based method for wind-power estimation: Application to
western Cyprus, in Open Geosciences 6(1):79-87 DOI: 10.2478/s13533-012-0162-3
Acknowledgment: This research is supported by the
project “Cross-Border Cooperation for Implementation of
Maritime Spatial Planning” referred as “THAL-CHOR 2”
and it is co-funded by the European Regional
Development Fund (ERDF) and by national funds of
Greece and Cyprus, under the Cooperation Programme
“INTERREG V-A Greece-Cyprus 2014-2020”.
Figure 3. Comparison between mean wind speed for 2017, as obtained by ECMWF re-
analysis data and Open-Skiron forecasts.
Figure 5. Comparisons of the Weibull distributions of two coastal –stations (green curves) with the
closest land (red curves) and sea (blue curves) grid point for 25km resolution.
Conclusions
➡ ECMWF re-analysis data show reasonable
agreement with forecasts of Open-Skiron and
meteorological stations in some cases
➡ Increasing the resolution through the use of the
5 km analysis data will provide more detailed
information in the future
➡ The inclusion of the in-situ measurements will be
extrapolated using flow models and used to increase
the accuracy of the picture.
34.375
34.625
34.875
35.125
35.375
35.625
35.875
31.875 32.375 32.875 33.375 33.875 34.375
Figure 1. Area of application and
positions of the meteorological
stations.
35.75 20.4 20.6 20.4 19.4 19.0 19.8 19.6 19.5 19.5 20.8 21.9 20.4
35.50 20.5 20.3 20.4 19.1 18.7 17.9 17.0 16.8 20.2 19.9 21.4 21.8
35.25 19.0 19.7 17.4 15.4 12.7 10.7 11.0 14.1 20.0 20.1 20.4 20.9
35.00 19.4 19.0 14.9 10.3 8.8 12.3 14.2 16.4 20.2 20.2 20.3 20.3
34.75 18.9 18.1 14.8 12.4 11.8 15.5 17.9 19.6 20.5 20.1 20.3 20.4
34.50 18.7 18.4 18.0 16.3 16.8 18.4 20.4 19.5 20.1 19.7 19.8 19.8
32.00 32.25 32.50 32.75 33.00 33.25 33.50 33.75 34.00 34.25 34.50 34.75
35.75 2.8 2.7 2.8 2.8 2.9 3.1 3.2 3.1 3.0 2.8 2.6 2.6
35.50 2.8 2.8 2.8 2.7 2.7 2.6 2.5 2.5 2.7 2.5 2.5 2.5
35.25 2.7 2.7 2.4 1.9 1.5 1.3 1.2 1.5 2.3 2.5 2.5 2.5
35.00 2.6 2.4 1.8 1.3 1.0 1.1 1.2 1.6 2.4 2.6 2.6 2.6
34.75 2.5 2.3 1.8 1.5 1.5 1.9 2.3 2.6 2.7 2.6 2.6 2.6
34.50 2.5 2.4 2.4 2.3 2.3 2.5 2.7 2.7 2.7 2.6 2.6 2.6
32.00 32.25 32.50 32.75 33.00 33.25 33.50 33.75 34.00 34.25 34.50 34.75
8.00 9.40 10.80 12.20 13.60 15.00 16.40 17.80 19.20 20.60 22.00
wind speed maximum (m/s) at 10 m
1.00 1.20 1.40 1.60 1.80 2.00 2.20 2.40 2.60 2.80 3.00
wind speed standard deviation (m/s) at 10 m
Figure 2. Average, maximum, and standard deviation of the wind speed (m/s) in the area of Cyprus
based on the hourly data of ECMWF (re-analysis data) with a spatial analysis of 25 km x 25 km.
General comparisons with data from the Open Skiron
35.75 4.5 4.7 5.0 5.2 5.3 5.6 5.6 5.3 5.0 4.7 4.6
35.50 4.7 4.8 5.1 5.0 5.0 5.0 4.7 4.4 4.6 4.5 4.4
35.25 4.6 4.5 4.1 3.5 2.7 2.3 2.1 2.5 3.8 4.1 4.2
35.00 4.3 3.8 2.9 1.9 1.7 1.8 2.0 2.7 4.1 4.3 4.4
34.75 4.5 4.1 3.2 2.4 2.5 3.4 3.9 4.5 4.7 4.5 4.6
34.50 4.8 4.7 4.7 4.3 4.3 4.5 4.9 4.9 4.9 4.7 4.7
32.00 32.25 32.50 32.75 33.00 33.25 33.50 33.75 34.00 34.25 34.50
35.75 4.2 4.4 4.7 5.1 5.3 5.3 5.2 5.0 4.7 4.3 4.1
35.50 4.4 4.6 4.8 4.9 5.1 4.8 4.3 4.0 3.6 3.4 3.7
35.25 4.4 4.4 4.3 3.9 3.1 3.2 2.7 2.3 2.8 3.4 4.0
35.00 4.1 3.7 3.2 3.1 2.7 2.7 2.5 2.9 3.5 4.1 4.4
34.75 4.2 3.9 3.6 3.4 3.1 3.5 4.0 4.3 4.4 4.5 4.6
34.50 4.6 4.6 4.8 4.9 4.8 4.9 4.9 4.8 4.7 4.7 4.6
32.00 32.25 32.50 32.75 33.00 33.25 33.50 33.75 34.00 34.25 34.50
1.50 2.05 2.60 3.15 3.70 4.25 4.80 5.35 5.90 6.45 7.00
wind speed average (m/s) at 10 m
35.75 -6 -7 -4 -1 -1 -5 -7 -7 -6 -8 -11
35.50 -6 -6 -7 -1 3 -4 -9 -8 -21 -24 -17
35.25 -4 -2 6 11 18 36 26 -6 -26 -17 -6
35.00 -4 -3 11 62 57 54 27 9 -15 -6 0
34.75 -7 -5 12 42 26 3 2 -4 -7 0 -1
34.50 -5 -3 3 15 12 8 -1 -1 -4 -2 -2
32.00 32.25 32.50 32.75 33.00 33.25 33.50 33.75 34.00 34.25 34.50
-26 -17 -9 0 9 18 26 35 44 53 62
relative differences (%)
In the figures below we compare basic statistics of
the wind speed as obtained from the 24 h forecasts
of the Open-Skiron meteorological model for the
year 2017. Open-Skiron operates on 5 km
resolution and results have been scaled to 25 km
for the needs of the present comparison.
Actual Weibull distributions reveal an intermediate
behavior between modelled sea and land points.
Figure 4. Hourly maximum, average and standard deviation of the wind speed (m/s) (top to bottom) for
the period 2002-2008, obtained from three meteorological stations (green curves) and the ECWMF.
With red curves the closest gird point over land and with blue curves the closest sea grid point.