S. C. Pryor

Prof. S. C. Pryor

orcid

Research Focus & Metrics

Academic Career Length

35Years (1992-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 January 2006 in Wind Energy
Verified
Journal Article
Closed access
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SFSten Frandsen
Sten Frandsen
RBRebecca J Barthelmie
Rebecca J Barthelmie
S. C. PryorS. C. Pryor
S. C. Pryor
OROle Rathmann
Ole Rathmann
SLSøren Larsen
Søren Larsen
MTMorten Thøgersen
Morten Thøgersen

1 October 2009 in Atmospheric Environment
Verified
Journal Article
Closed access
DFD. Fowler
D. Fowler
KPKim Pilegaard
Kim Pilegaard
MSM.A. Sutton
M.A. Sutton
PAPer Ambus
Per Ambus
MRM. Raivonen
M. Raivonen
JEJan Willem Erisman
Jan Willem Erisman

1 January 2010 in Renewable and Sustainable Energy Reviews
Verified
Journal Article
Closed access
S. C. PryorS. C. Pryor
S. C. Pryor
RBRebecca J Barthelmie
Rebecca J Barthelmie

1 August 2010 in Journal of Atmospheric and Oceanic Technology
Verified
Journal Article
Open access
RBRebecca J Barthelmie
Rebecca J Barthelmie
S. C. PryorS. C. Pryor
S. C. Pryor
SFS. T. Frandsen
S. T. Frandsen
KHK. S. Hansen
K. S. Hansen
JSJ. G. Schepers
J. G. Schepers
SNS. Neckelmann
S. Neckelmann
There is an urgent need to develop and optimize tools for designing large wind farm arrays for deployment offshore. This research is focused on improving the understanding of, and modeling of, wind turbine wakes in order to make more accurate power output predictions for large offshore wind farms. Detailed data ensembles of power losses due to wakes at the large wind farms at Nysted and Horns Rev are presented and analyzed. Differences in turbine spacing (10.5 versus 7 rotor diameters) are not differentiable in wake-related power losses from the two wind farms. This is partly due to the high variability in the data despite careful data screening. A number of ensemble averages are simulated with a range of wind farm and computational fluid dynamics models and compared to observed wake losses. All models were able to capture wake width to some degree, and some models also captured the decrease of power output moving through the wind farm. Root-mean-square errors indicate a generally better model performance for higher wind speeds (10 rather than 6 m s−1) and for direct down the row flow than for oblique angles. Despite this progress, wake modeling of large wind farms is still subject to an unacceptably high degree of uncertainty.

28 April 2013 in Nature Geoscience
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Journal Article
Closed access
Pauli PaasonenPauli Paasonen
Pauli Paasonen
AAAri Asmi
Ari Asmi
TPTuukka Petäjä
Tuukka Petäjä
MKMaija K. Kajos
Maija K. Kajos
MÄMikko Äijälä
Mikko Äijälä
MKMarkku Kulmala
Markku Kulmala

20 October 2020 in Nature Reviews Earth & Environment
Verified
Journal Article
Closed access
PDF file
S. C. PryorS. C. Pryor
S. C. Pryor
RBRebecca J Barthelmie
Rebecca J Barthelmie
MBMelissa Sue Bukovsky
Melissa Sue Bukovsky
LLLai Yung Ruby Leung
Lai Yung Ruby Leung
KSKoichi Sakaguchi
Koichi Sakaguchi