Jake Mittelman James Belanger Judith Curry Kris Shrestha EXTENDED-RANGE PREDICTABILITY OF REGIONAL WIND POWER GENERATION

With increases of wind penetration into energy grids, there is need for extended range forecasts to plan for reserve margins and for natural gas trading and sales. A key issue on these timescales is the volatility of the wind power supply and large-scale power ramps We investigate the prediction skill of wind power using ECMWF extended range 100m wind (1 to 32 day) forecasts for Texas (ERCOT) Operational Wind Power Forecasting Objectives Title Image Source:

7 Day Integrated Power Production Against Observations: Apr – Nov Shows good skill for Weeks 1-2 Weeks 3-4 show little skill JAMES CAN YOU HELP WITH THIS SLIDES CONCLUISONS

Large-Scale Power Ramp Ramp: sudden or large change in wind power generation. Large-scale ramp: typically associated with a frontal passage Operational definition for medium range forecasts: minimum 10% change over a 6 hour period in the % of rated power over a region, beyond the expected diurnal cycle. Ramp forecasts are crucial to the large-scale integration of wind energy into electricity grids and to the risk involved in energy trades/ purchases at times of high variability Image Source:

9 Days Prior

5 Days Prior

3 Days Prior

1 Days Prior

Deterministic predictability of individual ramp events Critical Success Index (Threat Score) CSI = hits / (hits + misses + false alarms) Equation Source: Wilks 2011, his Eq. (8.8)

Challenges for extended-range ramp prediction Individual large-scale ramps are predictable up to 7-10 days At longer time horizons, statistical measures of ramp likelihood or wind volatility are desired, over some period

Impact of averaging period: Skill Score relative to climatology

Ramping Likelihood Index (RLI)

Example RLI Calculation The total area between the two curves (shaded above) is the RLI

RLI results for 4/05/12 – 9/20/12 The RLI typically ranges between -5% and 5% for Weeks 3-4 Calibration of the forecasts could help Weeks 3-4

Temperature Volatility Index (TVI) and Wind Volatility Index (WVI): integral over the forecast period of normalized standard deviation of each ensemble member. Forecast evolution of the covariability between the TVI and WVI as a function of forecast week in advance, using the monthly hindcasts. Volatility Indices There is moderate forecast covariability between TVI and WFI, during Week 3 and 4. Week 1 is more likely to characteristic of the actual extreme temperature and wind covariability.

CONCLUSIONS ROC conclusion Individual large-scale ramps are predictable up to 7-10 days in advance, with low false alarm rates up to 5 days Averaging periods of 5-7 days provide improved skill scores for regional wind power forecasts A new metric Ramp Likelihood Index (RLI) is introduced for extended range wind power forecasts Image Source: