dirk cannon a , david brayshaw a , john methven a , phil coker b ,
DESCRIPTION
A 33 yr climatology of extreme wind power generation events in Great Britain EMS Annual Meeting & ECAM (2013). Dirk Cannon a , David Brayshaw a , John Methven a , Phil Coker b , David Lenaghan c , Andrew Richards c , David Mills c , David Bunney c [email protected] - PowerPoint PPT PresentationTRANSCRIPT
PowerPoint Presentation
A 33 yr climatology of extreme wind power generation events in Great Britain
EMS Annual Meeting & ECAM (2013)Dirk Cannona, David Brayshawa, John Methvena, Phil Cokerb,David Lenaghanc, Andrew Richardsc, David Millsc , David Bunneyc
a Department of Meteorology, University of Reading, UKb School of Construction Management and Engineering, University of Reading, UKc National Grid, Wokingham, Berkshire, RG41 5BN, UK
MotivationNeeds of transmission system operators (TSOs) to understand the frequency and severity of extreme wind power generation events
Needs of transmission system operators (TSOs) to understand the frequency and severity of extreme wind power generation events
Motivation
Persistent windpower generationNeeds of transmission system operators (TSOs) to understand the frequency and severity of extreme wind power generation events
Motivation
Rapid changes in windpower generationWind speed record from reanalysis data(MERRA, Rienecker et. al., 2011. J. Clim. 24, 36243648)
Long time series (19802012)Consistent assimilation of observations Gridded data (can be used with any wind farm distribution)Reproduces majority of observedvariability in 10 m wind speed onspatial scales > 200300 km, time scales > 36 hoursMethodology
Methodology | 33 yr climatology | Summary and future work
1. Wind farm distribution as of September, 2012; bi-linearly interpolated2. Log-height extrapolation to turbine hub height3. Transformation to Load Factor (LF) using idealised power curve
Conversion to power
Methodology | 33 yr climatology | Summary and future work
GB-aggregated over 215 wind farms: LF
Note: MERRA-derived LF assumes constant wind farm distribution, whereas the real distribution constantly evolvesComparisons with NG data
Methodology | 33 yr climatology | Summary and future work
r = 0.96Comparisons with NG data
Methodology | 33 yr climatology | Summary and future work
r = 0.73
r = 0.91Persistent low wind
How often do persistent low wind power generation events occur in an average year?Methodology | 33 yr climatology | Summary and future work
Persistent high wind
How often do persistent high wind power generation events occur in an average year?Methodology | 33 yr climatology | Summary and future work
Rapid changes
For how many hours in an average year is there a subsequent rapid change in wind power generation?Methodology | 33 yr climatology | Summary and future work
Inter-annual variability
E.g., LF 6.3 % for persistence time 24 hr: Mean: 10 yr-1Range: 2-18 yr-1 Methodology | 33 yr climatology | Summary and future work
Seasonal variability
E.g., LF 2.2 % for persistence time 12 hr:Mean: 0.5 /seasonRange: 0.15 /winter1.4 /summer Methodology | 33 yr climatology | Summary and future work
13Summary
Estimated the frequency and severity of extreme wind power generation events in Great Britain over the last 33 yr.
Considered three extremes:Persistent low wind power generationPersistent high wind power generationRapid changes in wind power generation
Return periods show large variations from year-to-year and season-to-season
Quantitative results sensitive to power curve (not shown)
Methodology | 33 yr climatology | Summary and future work Future work
Predictability of extreme wind power events
GB-wide scalesOn time scale of hours to daysStatistical and case study analysis
Regional scalesDownscale to km-scaleInvestigate extreme generation events & large forecast errors
Methodology | 33 yr climatology | Summary and future work
Predictability of extreme wind power events
GB-wide scalesOn time scale of hours to daysStatistical and case study analysis
Regional scalesDownscale to km-scaleInvestigate extreme generation events & large forecast errors