WIND INSIGHT a wind power forecasting tool for power system security management Dr Nicholas Cutler 21 March

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

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

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

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 theyll know how to respond in the near future 5

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

Wind Insight Novel approach comes from research by Dr Nicholas Cutler at the University of New South Wales ( ) Prototype tool developed for the Australian Energy Market Operator (AEMO) in 2010 –Final report: Now commercial system, currently being used in: –India: operational forecasts for 16 wind farms (as of 10 th 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

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

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

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 (%)

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

Wind power field forecast animations 12

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

Forecasting large rapid changes in South Australia – training result 14 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 MethodNumber forecast correctly (out of 48) Percentage forecast correctly Percentage of time alerted Wind Insight – using point forecast 2756%10% Wind Insight – using wind power fields 3063%10% Training result (2011)

Forecasting large rapid changes in South Australia – test result 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) MethodNumber forecast correctly (out of 62) Percentage forecast correctly Percentage of time alerted Wind Insight – using point forecast 3556%14% Wind Insight – using wind power fields 4166%13% Testing result (2012)

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

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

The time is midnight on 12 th October 2010 Wind power production is around 270 MW Point forecast shows rapid decrease at around 4:00 18 An example for a single wind farm cluster

The time is midnight on 12 th 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 An example for a single wind farm cluster

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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 21

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. 22 Summary

Estimated speed and direction of the most prominent moving wind features Australian coastline Forecast hub height wind directions Wind farm location 23 Wind power field forecast animations provide insight into potential scenarios for wind power production

Wind power field forecast animations Can immediately visualise impact of displacement upon wind farm generation Coloured changes format2D wind power format 24

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