Load Forecasting Process Review Calvin Opheim Generation Adequacy Task Force October 7, 2013

ERCOT PUBLIC10/7/2013 1

Load Forecasting Process Review

Calvin Opheim Generation Adequacy Task ForceOctober 7, 2013


Outline

• Long-Term Load Forecast Process Review

• Previous Model – Approach– What we’ve learned

• New Modeling Approach– Approach– Weather Normalization

• 4 Coincident Peak Analysis

• Questions


Weather Zones


Previous Model

• 2-3 weather stations per weather zone

• Used non-farm employment to capture future growth

• Weather Zone Forecasts– Daily Energy Per Job = f(weather, season, day type, daylight)– Hourly Demand = f(temperatures, previous hour’s load)

• ERCOT Forecast– ∑ eight weather zone loads


Previous Model Forecast Accuracy

Summer Peak MW Percent ErrorForecast Vintage 2011 2012 2013 2011 2012 2013

2012 Forecast 67,998 -1.1%

2011 Forecast 66,195 67,168 0.5% 0.1%

2010 Forecast 65,206 66,658 68,265 4.5% -0.2% -1.5%

Actual Peak 68,305 66,548 67,245


Previous Model – What we’ve learned

• Historical values of economic data are subject to significant revision for two years

– During the first quarter of 2013, the Bureau of Labor Statistics increased non-farm employment values by 1% in 2011 and 2% in 2012.

• While values may seem small, relative impacts are significant.

– Changing historical data compromises the accuracy of the model as “historical” relationships are subject to change.

– Model was based on the assumption that non-farm employment values were stable.



• Historical revisions impact forecast years– Moody’s forecast for CY2013 was increased by 2% in order to

align with the revised historical values for CY 2012.• Did load suddenly increase by 2% due to these revisions?

• Economic forecasts have been trending high, resulting in forecasts that reflect overly optimistic growth scenarios.




What’s new?

• Daily energy forecasts are now based on Neural Network Models.– Growth is determined by multiple factors (premise growth rates,

weather variables, day types, and their interactions).

– A single economic variable has less influence on forecast outcome.

• Benefits– ERCOT can determine/account for variable interactions more

robustly, compared to linear regression models.

– All predictor variables are used as inputs in each network node.

– This approach produces more detailed/precise model formulation.


Neural Network Model Diagram


What’s new?

• Forecasts will now be based on many model simulations instead of being based on a single linear model.– Neural Network models were developed with 33% of the

historical data being withheld from model development.– The data being withheld was determined randomly.– Randomly withholding data mitigates over-fitting of the data.– The model’s accuracy was determined based on how well it

predicted the sample holdout data.– Process was repeated hundreds of times (model convergence).

• Benefits– In statistics, repeated sampling gives a more accurate estimate

than a single sample.– The result is a more robust forecast.


What’s new?

• Historical energy relationships will now be based on premise counts by customer class (residential, commercial and industrial).– Historical energy relationships will no longer be based on non-

farm employment values.

• Benefits– Historical premise accounts will be very stable and will not be

subject to the significant changes exhibited by non-farm employment revisions.

– “Historical values are actually historical.”


What’s new?

• The determination of 15-year normal forecast will now be based on model output using the most recent 15 years of historical weather data.– Will no longer create a synthetic weather file for use in the model– Will no longer time align weather conditions for time of peak

• Benefits– More accurately reflects historical weather patterns– More accurately reflects load diversity at time of peak


2011 Summer Peak – Impact of 4 CP load reduction

• 4 CP impact shown is based on aggregated transmission load values for ~430 premises.

• Estimate is not based on an analysis of individual premises.

• Difference represents the 4 CP impact of ~600 MW on an aggregated basis.

• 4 CP impact would likely be greater if analysis were performed on individual premises.

4 CP impact


2012 Summer Peak – 4CP Impact

4 CP impact






2013 Summer Peak - 4CP Impact





4 CP Impact


Questions

ON

OFF

Documents

Load Forecasting Process Review Calvin Opheim Generation Adequacy Task Force October 7, 2013