The contribution of wind to securing electricity demand
David Brayshaw NCAS-Climate and Department of MeteorologyUniversity of Reading [email protected]
With Chris Dent, Stan Zachary, Giacomo Masato,Alberto Troccoli, John Methven, Rachael Fordham
IntroductionIncreasing 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
IntroductionIncreasing 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?
IntroductionIncreasing 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)
Mean output depends heavily (~10%) on large-scale atmospheric circulation state
Example: Winter 2009/10 saw very low UK winds AND cold temperatures from December – March, associated with persistent atmospheric circulation pattern (NAO-)
IntroductionIncreasing 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)
Mean output depends heavily (~10%) on large-scale atmospheric circulation state
Example: Winter 2009/10 saw very low UK winds AND cold temperatures from December – March, associated with persistent atmospheric circulation pattern (NAO-)
PhD project for Oct 2011
Explore the use of climate variability in estimating forward energy contract prices at monthly timescales
IntroductionIncreasing 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)
Mean output depends heavily (~10%) on large-scale atmospheric circulation state
Example: Winter 2009/10 saw very low UK winds AND cold temperatures from December – March, associated with persistent atmospheric circulation pattern (NAO-)
PhD project for Oct 2011
Explore the use of climate variability in estimating forward energy contract prices at monthly timescales
This talk
Focus on winter season in UK
IntroductionIncreasing 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 2010 (Renewable Energy)
Mean output depends heavily (~10%) on large-scale atmospheric circulation state
Example: Winter 2009/10 saw very low UK winds AND cold temperatures from December – March, associated with persistent atmospheric circulation pattern (NAO-)
PhD project for Oct 2011
Explore the use of climate variability in estimating forward energy contract prices at monthly timescales
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 2007Based on the “GWL” weather classification system
Peak demand 2006: a low-wind event
Oswald et al 2008Peak demand 2006
Peak demand 2006: a low-wind event
Oswald et al 2008Peak demand 2006
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
The good news…
Hourly demand level
Wind output(fraction of maximum)
Sinden (2007)
Quantity of wind power generally increases with demand even at moderately high demand levels (>80% of maximum)
Demand is expressed as rank-within-year
The good news…
Hourly demand level
Wind output(fraction of maximum)
Sinden (2007)
Quantity of wind power generally increases with demand even at moderately high demand levels (>80% of maximum)
Demand is expressed as rank-within-year
… and the badSinden (2007)
Quantity of wind power generally increases with demand even at moderately high demand levels (>80% of maximum)
Demand is expressed as rank-within-year
Power 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
Hourly demand level
Wind output(fraction of maximum)
… and the badSinden (2007)
Quantity of wind power generally increases with demand even at moderately high demand levels (>80% of maximum)
Demand is expressed as rank-within-year
Power 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 half-hour appears positively related to wind
Hourly demand level
Wind output(fraction of maximum)
Demand expected in “low wind cold snap”
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?
Sinden/Oswald
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)
Quantifying wind during peak demand
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)
The use of meteorological information
E.g., time of day, day of week, what’s on TV, etc...
E.g., Taylor and Buizza 2000
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)
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?
The use of meteorological information
E.g., time of day, day of week, what’s on TV, etc...
E.g., Taylor and Buizza 2000
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)
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)
N wind
S wind
Temp
Demand
Metered
Extreme peak demand in Jan 2010
Contours – Sea level pressureColours – temperatureHatching – low wind (< -1 s.dev.)Dots – high wind (> +1 s.dev.)
Temp
N wind
S wind
Demand
Metered
Extreme peak demand in Jan 2010
Contours – Sea level pressureColours – temperatureHatching – low wind (< -1 s.dev.)Dots – high wind (> +1 s.dev.)
TempHigh pressure to north, low to south: “Blocking”Easterly wind moderate in south, weak in northVery cold temperature ~ -2oC
N wind
S wind
Demand
Metered
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)
N wind
S wind
Temp
Contours – Sea level pressureColours – temperatureHatching – low wind (< -1 s.dev.)Dots – high wind (> +1 s.dev.)
Low wind everywhereHigh pressure over GBModerate temperature ~ +2oC
Circulation typing (GWL)
Figure from Gerstengarbe et al 1999
“Prevailing” weather type
Time-filtered daily-mean circulation fields
Objective correlation to 29 canonical weather typesJames (2006) following Hess and Brezowsky (1952)
Easterly flow into GB (N-S pressure dipole) is keyOne possible approach to identify this is “circulation typing”
Circulation types of most extreme demands
Red = Dipole “Blocking” typesBlue = High-over-Britain
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One “event”
Circulation types: GB Wind vs Temperature
High-over-BritainLow wind
Moderate temperature
Circulation types: GB Wind vs Temperature
High-over-BritainLow wind
Moderate temperature
NE Atlantic high patternsModerate windVery low temperatureExpect much higher demand
Caution: the classification of blocks vs troughs is somewhat ambiguous, especially for TM and HNZ
Circulation types: GB Wind vs Temperature
High-over-BritainLow wind
Moderate temperature
NE Atlantic high patternsModerate windVery low temperatureExpect much higher demand
Blocking patternsAfter 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
High-over-BritainLow wind
Moderate temperature
NE Atlantic high patternsModerate windVery low temperatureExpect much higher demand
Blocking patternsAfter Hess et al 1951 Caution: the classification of blocks vs troughs is
somewhat ambiguous, especially for TM and HNZ
Trough patternsMany seem to be associated with passage of a low-pressure system across mid-Europe
One possible interpretation of Sinden and OswaldSinden: 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 OswaldSinden: 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 OswaldSinden: 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 OswaldSinden: 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
ConclusionsCharacteristics 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:• [email protected]• Brayshaw, Dent, Zachary, J. Risk & Reliability (submitted)• Brayshaw, Troccoli, Fordham, Methven, Renewable Energy (2011)
Positive Negative
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Storm tracks and the NAO
Figs: http://www.ldeo.columbia.edu/res/pi/NAO/
Positive Negative
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Storm tracks and the NAO
Figs: http://www.ldeo.columbia.edu/res/pi/NAO/
Path of weather systems affecting GB influenced by “slow” climate variations
Correlation strength: January surface temperature vs NAO
Left: from NOAA CPC website
NAO, surface temperature and wind
High NAO = warm windy wintersLow NAO = cold still winters
Correlation strength: January surface temperature vs NAO
Left: from NOAA CPC website
NAO, surface temperature and wind
High NAO = warm windy wintersLow NAO = cold still winters
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 assessmentweather derivativeslonger-term energy futures contracts
Winter 2010: a strong NAO-
Surface wind
Surface temperature
Climatology Winter 2010 anomaly
Less wind
Cold
More wind
Warm