The contribution of wind to
securing electricity demand
David Brayshaw
NCAS-Climate and Department of Meteorology
d.j.brayshaw@reading.ac.uk
University of Reading
With Chris Dent, Stan Zachary, Giacomo Masato,
Alberto Troccoli, John Methven, Rachael Fordham
Introduction
Increasing deployment of renewable energy systems in UK (mostly wind)
From the UK government (DECC renewable energy strategy 2009)
• 5.5% electricity from renewables in 2008
• 30% electricity from renewables by 2020
Weather impact: supply becomes more volatile
Introduction
Increasing deployment of renewable energy systems in UK (mostly wind)
From the UK government (DECC renewable energy strategy 2009)
• 5.5% electricity from renewables in 2008
• 30% electricity from renewables by 2020
Weather impact: supply becomes more volatile
Questions:
1. How much power can we get from a wind turbine once its installed?
2. How much is the output from a wind turbine worth in money terms?
3. In times of peak demand, how much wind power can be expected?
Brayshaw et al 2011 (Renewable Energy)
Introduction
Increasing deployment of renewable energy
in UK (mostly
wind) on largeMean systems
output depends
heavily (~10%)
scale atmospheric
circulation
state
From the UK government (DECC renewable
energy strategy
2009)
• 5.5% electricity from renewables in 2008
Example:
• 30% electricity from renewables
by 2020
Winter 2009/10 saw very low UK winds AND
cold temperatures from December – March,
Weather impact: supply becomes moreassociated
volatile with persistent atmospheric
circulation pattern (NAO-)
Questions:
1. How much power can we get from a wind turbine once its installed?
2. How much is the output from a wind turbine worth in money terms?
3. In times of peak demand, how much wind power can be expected?
Brayshaw et al 2011 (Renewable Energy)
Introduction
Increasing deployment of renewable energy
in UK (mostly
wind) on largeMean systems
output depends
heavily (~10%)
scale atmospheric
circulation
state
From the UK government (DECC renewable
energy strategy
2009)
• 5.5% electricity from renewables
in 2008
PhD project
for Oct 2011
Example:
• 30% electricity from renewables by 2020
Winter 2009/10 saw very low UK winds AND
Explore
use of climate
variability
in – March,
coldthe
temperatures
from
December
Weather impact: supply becomes more
volatile
estimating
forward
contract
prices
associated
withenergy
persistent
atmospheric
at monthly
timescales
circulation
pattern (NAO-)
Questions:
1. How much power can we get from a wind turbine once its installed?
2. How much is the output from a wind turbine worth in money terms?
3. In times of peak demand, how much wind power can be expected?
Brayshaw et al 2011 (Renewable Energy)
Introduction
Increasing deployment of renewable energy
in UK (mostly
wind) on largeMean systems
output depends
heavily (~10%)
scale atmospheric
circulation
state
From the UK government (DECC renewable
energy strategy
2009)
• 5.5% electricity from renewables
in 2008
PhD project
for Oct 2011
Example:
• 30% electricity from renewables by 2020
Winter 2009/10 saw very low UK winds AND
Explore
use of climate
variability
in – March,
coldthe
temperatures
from
December
Weather impact: supply becomes more
volatile
estimating
forward
contract
prices
associated
withenergy
persistent
atmospheric
at monthly
timescales
circulation
pattern (NAO-)
Questions:
1. How much power can we get from a wind turbine once its installed?
2. How much is the output from a wind turbine worth in money terms?
3. In times of peak demand, how much wind power can be expected?
This talk
Focus on winter season in UK
Brayshaw et al 2010 (Renewable Energy)
Introduction
Increasing deployment of renewable energy
in UK (mostly
wind) on largeMean systems
output depends
heavily (~10%)
scale atmospheric
circulation
state
From the UK government (DECC renewable
energy strategy
2009)
• 5.5% electricity from renewables
in 2008
PhD project
for Oct 2011
Example:
• 30% electricity from renewables by 2020
Winter 2009/10 saw very low UK winds AND
Explore
use of climate
variability
in – March,
coldthe
temperatures
from
December
Weather impact: supply becomes more
volatile
estimating
forward
contract
prices
associated
withenergy
persistent
atmospheric
at monthly
timescales
circulation
pattern (NAO-)
Questions:
1. How much power can we get from a wind turbine once its installed?
2. How much is the output from a wind turbine worth in money terms?
3. In times of peak demand, how much wind power can be expected?
This talk
Focus on winter season in UK
Disclaimer:
Nowhere suggesting that meteorological concerns will
dictate renewable deployment but, once deployed,
climate variability will become significant factor.
Wind availability during peak demand
Prevailing view:
• The “low wind cold snap”
Conceptual picture tends to
describe an anticyclone system
sitting over the UK
UKERC 2006
James 2007
Based on the “GWL” weather
classification system
Peak demand 2006: a low-wind event
Peak demand 2006
Oswald et al 2008
Peak demand 2006: a low-wind event
What I hope to do is convince you that:
• This is not a particularly “good” representation of the real peak-demand situation
• Enhanced meteorological understanding will help in quantifying the relationship
between wind and demand
NB: This is a work-in-progress
Peak demand 2006
Oswald et al 2008
Wind output
(fraction of maximum)
The good news…
Sinden (2007)
Quantity of wind power
generally increases with
demand even at
moderately high demand
levels (>80% of maximum)
Hourly demand level
Demand is expressed as
rank-within-year
Wind output
(fraction of maximum)
The good news…
Sinden (2007)
Quantity of wind power
generally increases with
demand even at
moderately high demand
levels (>80% of maximum)
Hourly demand level
Demand is expressed as
rank-within-year
Wind output
(fraction of maximum)
… and the bad
Sinden (2007)
Quantity of wind power
generally increases with
demand even at
moderately high demand
levels (>80% of maximum)
Hourly demand level
Power
Demand is expressed as
rank-within-year
Oswald et al (2008)
• At the half-hour of annual-peak
demand in each year (~0.005%
frequency) quantity of wind power
available can be very low
Wind output
(fraction of maximum)
… and the bad
Sinden (2007)
Quantity of wind power
generally increases with
demand even at
moderately high demand
levels (>80% of maximum)
Hourly demand level
Power
Demand expected in
“low wind cold snap”
Demand is expressed as
rank-within-year
Oswald et al (2008)
• At the half-hour of annual-peak
demand in each year (~0.005%
frequency) quantity of wind power
available can be very low
BUT
• The total demand at the peak halfhour appears positively related to wind
Sinden/Oswald
Three general points:
• Wind positively related to demand
• No real surprise as demand related to “effective” temperature and wind-chill
• Highest demand in any given year frequently occurs in conjunction with low-wind
• Very high demand events generally have higher wind-speeds
Question:
• How can we quantify the wind-resource during peak demand events?
Quantifying wind during peak demand
Direct use of energy system data problematic (analysis by Dent and Zachary)
• Peak demand extremes are rare
• Energy system (demand, supply) are:
• short (~10-20 years)
• inhomogeneous (system evolves in time)
 Estimates dominated by properties of few events
• Recorded wind-supply is function of existing wind-farm deployment
Brayshaw, Dent, Zachary (Submitted to J. Risk & Reliability)
The use of meteorological information
Many of properties we are concerned about relate to meteorological behaviour:
• Demand = f(temperature, wind-speed, ....) + human “noise” + met-human interactions
• Wind-supply = f(wind-speed)
E.g., Taylor and Buizza 2000
E.g., time of day, day of week,
what’s on TV, etc...
The use of meteorological information
Many of properties we are concerned about relate to meteorological behaviour:
• Demand = f(temperature, wind-speed, ....) + human “noise” + met-human interactions
• Wind-supply = f(wind-speed)
E.g., Taylor and Buizza 2000
E.g., time of day, day of week,
what’s on TV, etc...
Linking to meteorological properties desirable because:
• Longer, approximately homogeneous datasets (~30-60 years+)
• Link to climate model simulations for future changes (months-seasons-decades)
Questions:
• What does a low-wind event look like?
• What does a high-demand event look like?
• How far do the two event types overlap?
• How can we objectively identify these events in meteorological records?
Extreme peak demand in Jan 2010
Temperature (every 6h)
Metered demand
(every 1h)
Metered wind
(Solid line: every 1h)
Observed wind (broken blue lines):
Northern GB (Dashed: every 6h)
Southern GB (Dotted: every 6h)
Extreme peak demand in Jan 2010
Temperature (every 6h)
Temp
Metered demand
(every 1h)
Demand
S wind
Metered wind
(Solid line: every 1h)
N wind
Metered
Observed wind (broken blue lines):
Northern GB (Dashed: every 6h)
Southern GB (Dotted: every 6h)
Extreme peak demand in Jan 2010
Temp
Demand
S wind
N wind
Metered
Contours – Sea level pressure
Colours – temperature
Hatching – low wind (< -1 s.dev.)
Dots – high wind (> +1 s.dev.)
Extreme peak demand in Jan 2010
Temp
High pressure to north, low to south: “Blocking”
Easterly wind moderate in south, weak in north
Very cold temperature ~ -2oC
Demand
S wind
N wind
Metered
Contours – Sea level pressure
Colours – temperature
Hatching – low wind (< -1 s.dev.)
Dots – high wind (> +1 s.dev.)
Peak demand in Feb 2006 (as Oswald 2006)
Temperature (every 6h)
Observed wind (broken blue lines):
Northern GB (Dashed: every 6h)
Southern GB (Dotted: every 6h)
Peak demand in Feb 2006 (as Oswald 2006)
Temp
N wind
S wind
Contours – Sea level pressure
Colours – temperature
Hatching – low wind (< -1 s.dev.)
Dots – high wind (> +1 s.dev.)
Low wind everywhere
High pressure over GB
Moderate temperature ~ +2oC
Circulation typing (GWL)
Easterly flow into GB (N-S pressure dipole) is key
One possible approach to identify this is “circulation typing”
“Prevailing”
weather type
Time-filtered daily-mean
circulation fields
Figure from Gerstengarbe et al 1999
Objective correlation to 29 canonical weather types
James (2006) following Hess and Brezowsky (1952)
Less extreme peak demand
Circulation types of most extreme demands
One “event”
Red = Dipole “Blocking” types
Blue = High-over-Britain
Circulation types: GB Wind vs Temperature
High-over-Britain
Low wind
Moderate temperature
Circulation types: GB Wind vs Temperature
NE Atlantic high patterns
Moderate wind
Very low temperature
Expect much higher demand
High-over-Britain
Low wind
Moderate temperature
Caution: the classification of blocks vs troughs is
somewhat ambiguous, especially for TM and HNZ
Circulation types: GB Wind vs Temperature
NE Atlantic high patterns
Moderate wind
Very low temperature
Expect much higher demand
High-over-Britain
Low wind
Moderate temperature
Blocking patterns
After Hess et al 1951
Caution: the classification of blocks vs troughs is
somewhat ambiguous, especially for TM and HNZ
Circulation types: GB Wind vs Temperature
NE Atlantic high patterns
Moderate wind
Very low temperature
Expect much higher demand
Trough patterns
Many seem to be associated
with passage of a low-pressure
system across mid-Europe
High-over-Britain
Low wind
Moderate temperature
Blocking patterns
After Hess et al 1951
Caution: the classification of blocks vs troughs is
somewhat ambiguous, especially for TM and HNZ
One possible interpretation of Sinden and Oswald
Sinden: in general wind increases with increasing demand
• As wind increases, wind-chill (and therefore demand) increases
• Thus demand and supply positively related over all
One possible interpretation of Sinden and Oswald
Sinden: in general wind increases with increasing demand
• As wind increases, wind-chill (and therefore demand) increases
• Thus demand and supply positively related over all
Sinden: at fairly high demands (>80%), wind still increases with demand
• As above, but in Met terms moving right to left along line
One possible interpretation of Sinden and Oswald
Sinden: in general wind increases with increasing demand
• As wind increases, wind-chill (and therefore demand) increases
• Thus demand and supply positively related over all
Sinden: at fairly high demands (>80%), wind still increases with demand
• As above, but in Met terms moving right to left along line
Oswald: at peak demand in year, wind may be very low
• Corresponds to years where the lowest T is quite moderate => picks out HB-like types
One possible interpretation of Sinden and Oswald
Sinden: in general wind increases with increasing demand
• As wind increases, wind-chill (and therefore demand) increases
• Thus demand and supply positively related over all
Sinden: at fairly high demands (>80%), wind still increases with demand
• As above, but in Met terms moving right to left along line
Oswald: at peak demand in year, wind may be very low
• Corresponds to years where the lowest T is quite moderate => picks out HB-like types
Oswald: in years with very high peak demand, wind is quite good
• Corresponds to years where the lowest T is extreme => move left on line
Conclusions
Characteristics of (at least) three types of features need to be understood:
• High-over-Britain (low-wind cold-snap)
• Benchmark scenario with high-ish demand and no wind
• Demand must be met by some other means
• Blocked types bringing cold continental air into UK from East
• Most extreme demand levels likely but some wind
• Dry continental air, stable system
• Trough types bringing cold martime air into UK from North
• Very high demand levels possible but some wind
• Moist maritime air, transient system
Brayshaw, Dent, Zachary (Submitted to J. Risk & Reliability)
Next steps
Simply the meteorological detection method (with Giacomo Masato):
• Less GWL types
• Blocking indices
Quantitative analysis of wind & temperature distributions within each type
• NCAS, Leeds University and UK Met Office downscaling (to 4km)
• MSc student #1 to start in April 2011
Relationships to changing climate system:
• C21 climate simulations from IPCC-type models (Giacomo)
• Climate variability at seasonal-to-decadal timescales
• Implications for finance (weather derivatives, energy futures contracts)
• MSc student #2 to start April 2011
• PhD student to start October 2011
Papers and contact:
• d.j.brayshaw@reading.ac.uk
• Brayshaw, Dent, Zachary, J. Risk & Reliability (submitted)
• Brayshaw, Troccoli, Fordham, Methven, Renewable Energy (2011)
Storm tracks and the NAO
Positive
Negative
37
Figs: http://www.ldeo.columbia.edu/res/pi/NAO/
Storm tracks and the NAO
Positive
Negative
Path of weather systems affecting GB
influenced by “slow” climate variations
38
Figs: http://www.ldeo.columbia.edu/res/pi/NAO/
NAO, surface temperature and wind
Correlation strength:
January surface temperature vs NAO
High NAO = warm windy winters
Low NAO = cold still winters
Left: from NOAA CPC website
NAO, surface temperature and wind
Correlation strength:
January surface temperature vs NAO
Brayshaw et al 2011 (Renewable Energy) demonstrates:
Prevailing NAO state affects wind-speed distribution at timescales hours – years
This information can be used to improve forecasts of wind-energy output at
monthly-timescales
Implications for finance:
initial resource assessment
weather derivatives
longer-term energy futures contracts
High NAO = warm windy winters
Low NAO = cold still winters
Left: from NOAA CPC website
Winter 2010: a strong NAOClimatology
Surface
wind
Winter 2010 anomaly
Less wind
More wind
Cold
Surface
temperature
Warm