Fourth Study Conference on BALTEX Scala Cinema Gudhjem

- 131 -
Wind Energy Prognoses for the Baltic Region
Sara C. Pryor 1,2 , Rebecca J. Barthelmie 2 and Justin T. Schoof 1
1 Atmospheric Science Program, Indiana University, Bloomington, IN 47405 (email: spryor@indiana.edu)
2 Department of Wind Energy, Risoe National Laboratory, Dk 4000 Roskilde, Denmark.
1. Introduction
In the context of wind farms which have typical lifetimes
≈30 years, the question is asked ‘what is a normal wind
year?’ (over the wind farm lifetime what is the average
expected energy production?). Recall energy density =
½ρU 3 , hence cumulative annual energy density is dominated
by the upper percentiles of the probability distribution. This
question can be extended to further encompass the
following; ‘will non-stationarities in the global climate
system cause the definition or magnitude of a normal wind
year to evolve on timescales of relevance to wind energy
developments?’
2. Objectives and data
<strong>Study</strong> objectives are to:
o Quantify the variability of the wind energy in the
twentieth century (C20th) (Pryor and Barthelmie 2003)
and compare the reanalysis data sets.
o Determine the degree to which a coupled Atmosphere-
Ocean General Circulation Model (AOGCM) captures
recent spatio-temporal variability of wind speeds and
extrapolate wind indices for the twenty-first century
(C21st).
Latitude (N)
65
64
63
62
61
60
59
58
57
56
55
54
53
B
A
D
C
F
E
4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Longtiude (E)
Figure 1. <strong>Study</strong> region
Historical data (1958-2001) are from the NCEP/NCAR
(Kalnay et al. 1996) and ECMWF (Simmons and Gibson
2000) reanalysis projects (Figure 1), while prognostic flow
is derived from daily output of the HadCM3 AOGCM (Pope
et al. 2000) for the transient simulation of the SRES A2
emission scenario (IPCC 2000).
H
G
3. Influence of normalization period on historical
wind indices
Wind indices are mechanisms for assessing inter- and intraannual
variability of wind energy. They are used here to
convert variability of wind speeds into a metric accessible to
wind energy developers and to provide an overview of
changes in the wind speed probability distribution.
n
3 (1)
U j
Index = ∑ * 100
j=
1
3
Ui...
k
j = 1, n indicates the time series from the period of interest
i…k indicates the normalization period
As shown by (1), wind indices exhibit intra- and interannual
variability and are determined in part by the
normalization period used.
J
I
L
K
N
M
Figure 2 shows the mean annual wind index for 1958-
2001 calculated for grid cells E, I and L presented as a
function of the normalization period. Due to the relatively
low wind speeds during the late 1950’s to 1970, mean
wind indices for these grid cells calculated using the
beginning of the record as the normalization interval
exhibit values above 100 %, while the converse is true for
the normalization by the latter portion of the period. For
example, using 1987-1998 for normalization (as in the
Danish wind index, www.emd.dk) gives a mean annual
wind index for grid cell E over 1958-2001 of 92-94 %,
indicating the mean wind energy resource over Denmark
for 1958-2001 is approximately 7 % lower than that
during 1987-1998. For the other two grid cells shown in
Figure 2 the 1987-1998 period also exhibited higher
average wind energy density than was typical of 1958-
2001. For grid cell L the maximum in wind indices was
observed for normalization periods focused on the late
1970s and early 1980s indicating this period was
characterized by atypically low wind energy. In summary,
for the grid cells considered here 1987-1998 does not
represent a robust wind energy climatology relative to the
entire period of 1958-2001, while 1969-1980 is arguably
the 12-year period that best represents the 1958-2001
period. Discrepancies between the reanalysis data sets as
evidenced in Figure 2 will be considered in more detail in
the presentation.
Mean annual wind index (1958-2001)
Mean annual wind index (1958-2001)
112
108
104
100
96
92
88
112
108
104
100
96
92
88
E
NCEP/NCAR
ECMWF
1960 1970 1980 1990
Year (begining of normalization period)
L
1960 1970 1980 1990
Year (begining of normalization period)
Mean annual wind index (1958-2001)
112
108
104
100
96
92
88
I
1960 1970 1980 1990
Year (begining of normalization period)
Figure 2. Mean annual wind index for data from 1958-
2001 and grid cells E, I and L presented as a function of
the normalization period (plotted at the year which begins
the normalization interval).
4. Evaluation of HadCM3: Comparison with
the reanalysis data sets for 1990-2001.
Prior to use of HadCM3 simulation output to develop
wind energy prognoses it is important to evaluate the
performance of the model during the period of overlap
with the reanalysis data (1990-2001). Hence, we evaluate:
o Mean wind speed fields derived from daily average
data and spatial correlations of the data.