Transcript Slide 1
WIND INSIGHT
a wind power forecasting tool for
power system security management
21 March 2013
Dr Nicholas Cutler
[email protected] www.roamconsulting.com.au
What is power system security management?
• Ensuring supply = demand at all times
Mostly controllable
=
Uncontrollable
variable source
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What is power system security management?
• Ensuring supply = demand at all times
Mostly controllable
=
Uncontrollable,
variable
3
What is power system security management?
• Short-term forecasts of wind generation up to 48 hours
ahead can help power system operators manage power
system security
• This includes forecasting large rapid changes (ramps) in
wind power generation
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Wind power forecasting
• Wind power forecasting systems are in use around the
world, e.g.:
– Australian Energy Market Operator (AEMO), Australia
– Many European countries and U.S. States
• Large rapid change forecasting not widely used yet
– Not so critical in many power systems now – but will be
• Eastern Australia has 2,500 MW wind now, but 10,000 MW in 2020
– It is extremely difficult to forecast large rapid changes
• Power system operators need to start learning now and
using large rapid change forecasts so they’ll know how to
respond in the near future
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Causes of large rapid changes
• Studied wind power, wind speed and direction from various
wind farms in Australia
• Large rapid changes commonly caused by horizontally
propagating synoptic phenomena
– Cold fronts
– Low pressure systems
• It is a similar story for New Zealand
• Their predictability?
– Weather forecasting models generally predict these phenomena well,
and their effect of near-surface winds (hub height)
– However there is uncertainty with their timing / precise position
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Wind Insight
• Novel approach comes from research by Dr Nicholas Cutler
at the University of New South Wales (2006-2009)
• Prototype tool developed for the Australian Energy Market
Operator (AEMO) in 2010
– Final report: http://www.aemo.com.au/electricityops/0269-0001.pdf
• Now commercial system, currently being used in:
– India: operational forecasts for 16 wind farms (as of 10th March
2014), using real-time observations for accurate point forecasts
from 15 minutes to 48 hours ahead
– All wind farms in the National Electricity Market out to 7 days
ahead
– Trialled on wind farms in Western Australia
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Overview of Wind Insight
• Wind Insight provides:
– Point forecasts of wind power
(“expected generation”, or
single time-series)
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Overview of Wind Insight
• Wind Insight provides:
10% POE
– Point forecasts of wind
power
– Probability of exceedence
(POE) forecasts
90% POE
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Overview of Wind Insight
• Wind Insight provides:
(%)
– Point forecasts of wind
power
– Probability of exceedence
(POE) forecasts
– Large rapid change
forecasts: alerts with
likelihood of event occurring
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Overview of Wind Insight
• Wind Insight provides:
– Point forecasts of wind
power
– Probability of exceedence
(POE) forecasts
– Large rapid change
forecasts: alerts with
likelihood of event
occurring
– “Wind power field”
forecast animations
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Wind power field forecast animations
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Wind speed forecasts are transformed
• Local elevation and surface roughness affect local wind speeds
– Displacing wind features is not trivial
• Wind power fields use transformed wind speed forecasts
– Local modelled terrain effects are made ‘equivalent’ to the terrain of the wind farm site
Raw wind speedwind
Site-equivalent
forecasts
speeds
Wind speeds over the
ocean are reduced
Wind speed transformation
over land is more complex
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Forecasting large rapid changes
in South Australia – training result
• Large rapid change defined as > 200 MW change in 30 mins or less.
• System trained on 2011 (48 events) and tested on 2012 (62 events)
• Two Wind Insight methods compared on forecasts ~1 day ahead
Training result (2011)
Method
Number forecast
correctly
(out of 48)
Percentage
forecast
correctly
Percentage
of time
alerted
Wind Insight –
using point forecast
27
56%
10%
Wind Insight –
using wind power fields
30
63%
10%
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Forecasting large rapid changes
in South Australia – test result
2012 had more events than 2011, and a higher average wind speed
in general. Thus Wind Insight raises more alerts than 2011 (a higher
percentage of time alerted), and correctly captures the same or
slightly better rate of actual events (percentage forecast correctly)
Testing result (2012)
Method
Number forecast
correctly
(out of 62)
Percentage
forecast
correctly
Percentage
of time
alerted
Wind Insight –
using point forecast
35
56%
14%
Wind Insight –
using wind power fields
41
66%
13%
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A practical example
(%)
• Point forecast
• POE forecast
• Large rapid change
alerts
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A practical example
• What actually
happened?
(%)
-211 MW
+238 MW
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An example for a single wind farm cluster
• The time is midnight on
12th October 2010
• Wind power production
is around 270 MW
• Point forecast shows
rapid decrease at
around 4:00
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An example for a single wind farm cluster
• The time is midnight on
12th October 2010
• Wind power production
is around 270 MW
• Point forecast shows
rapid decrease at
around 4:00
• High wind speed alert
raised with 10%
likelihood at midnight to
1:00
• Change in wind speed
alert raised for period
2:00 to 5:00 with 40%
likelihood around 2-3:00
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• A rapid decrease in wind power occurred 1-2 hours earlier and more
rapid than the point forecast suggested
• However the alerts and wind power fields did suggest this possibility
• During the 10% likelihood high wind speed cut-out alert, an actual
event did not occur this time
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Summary
• Forecasts of large rapid changes in wind power will be
needed soon by power system operators
• Point forecasts may not capture large rapid changes that
are suggested by NWP systems
• Wind Insight raises alerts with likelihoods of large rapid
changes and provides wind power field forecast
animations to inform decision-makers
Thank you!
Dr Nicholas Cutler. [email protected]
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Wind power field forecast animations provide insight into
potential scenarios for wind power production
Wind farm location
Estimated speed and
direction of the most
prominent moving
wind features
Forecast hub height
wind directions
Australian coastline
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Wind power field forecast animations
• Can immediately visualise impact of displacement
upon wind farm generation
2D wind power format
Coloured changes format
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Two types of large rapid changes
• Change in wind speed (CWS)
• High wind speed cut-out (HWS)
• Both event types may contribute to an aggregated change
in wind power from multiple wind farms
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