WIND INSIGHT a wind power forecasting tool for power system security management

1. WIND INSIGHTa wind power forecasting tool for power system security management Dr Nicholas Cutler 21 March 2013 nicholas.cutler@roamconsulting.com.au www.roamconsulting.com.au

2. What is power system security management? Ensuring supply = demand at all times Mostly controllable = Uncontrollable variable source 2

3. What is power system security management? Ensuring supply = demand at all times Mostly controllable = Uncontrollable, variable 3

4. 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 4

5. 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 5

6. 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 6

7. 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 7

8. Overview of Wind Insight Wind Insight provides: Point forecasts of wind power (“expected generation”, or single time-series) 8

9. Overview of Wind Insight Wind Insight provides: Point forecasts of wind power Probability of exceedence (POE) forecasts 10% POE 90% POE 9

10. 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 (%) 10

11. 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 11

12. Wind power field forecast animations 12

13. 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 speed forecasts Site-equivalent wind speeds Wind speeds over the ocean are reduced Wind speed transformation over land is more complex 13

14. 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) 14

15. 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) 15

16. A practical example • Point forecast • POE forecast • Large rapid change alerts (%) 16

17. A practical example • What actually happened? +238 MW -211 MW (%) 17

18. 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 18

19. 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 19

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21. 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 21

22. 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. nicholas.cutler@roamconsulting.com.au 22

23. 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 23

24. Wind power field forecast animations • Can immediately visualise impact of displacement upon wind farm generation 2D wind power format Coloured changes format 24

25. 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 25