Market analysts Derek Salvino and Chris Handwerk presented on their efforts and the results of using AURORAxmp to carefully incorporate historical data and appropriate model assumptions to perform a very accurate backcast and help the company gain confidence in the team’s forecasting ability going forward with the use of the model. AURORAxmp’s speed, transparency and data import flexibility enabled Exelon to successfully accomplish this goal in a reasonable time frame. This presentation contains insights and helpful recommendations to anyone seeking to improve their modeling accuracy.

1. Using Historical Data to Fine-
tune Aurora Predictive
Capability and Gain Insights
into Market Behavior
Chris Handwerk and Derek Salvino
October 16, 2009

2. Motivation
Models are great at giving insights, but are only
as good as:
Their capabilities
The data that you feed into them
AURORAxmp® is an excellent power price
forecasting tool, with lots of advanced and
detailed functionality.
Like a fine racing car, it needs to be tuned up
before it can be used to race competitively
How do we gain confidence in the model?
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3. Data 2
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Having reliable and accurate data is essential Data infrastructure and organization is key
http://celebrity-babies.com/2007/09/09/tina-fey-and-da/

4. Key Input Data (SFELT) 3
Stack
(generation characteristics)
Fuels
EmissionsLoad
Transmission

5. Data sources
EPIS database
Excellent for resource constrained organizations
Publicly available
CEMS (Continuous Emissions Monitoring System - EPA)
FERC Forms
EIA
ISO
Proprietary sources
Energy Velocity
Platt’s
SNL
IIR (Industrial Information Resources)
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6. Suggested Metrics for Comparison
– Stack Matching
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7. Suggested Metrics for Comparison
– Unit Operation
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8. Suggested Metrics for Comparison
– Transmission Flows
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9. Suggested Metrics for Comparison
– Zonal LMP (basis)
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10. Zonal LMP challenges in Aurora zonal
Marginal cost of
marginal unit
Bid adder
of marginal unit
LMP
Energy
Congestion
Loss
Energy
Between zone loss and
congestion
Within zone loss and
congestion
Between zone loss and
congestion
Within
Aurora
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11. Things worth investigating
Generator characteristics
Start-up costs
Ramp rates
# of bidding segments (upper bidding block)
Emissions (seasonality)
Outage behavior
Minimum uptimes/downtimes
Reliability Must Run (RMR)
Transmission link limits/wheeling charges
Fuel costs – burner tip v. market price
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12. Backcasting challenges
How close is good enough?
Transmission
Financial v. physical behavior
Behavior of border regions
Incorporating regulatory considerations
Data management and availability
Resources
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13. 12
Finely tuning your racing car will put
you in the winner’s circle!
http://www.autobahnmag.com/wp-content/uploads/2009/05/59b48c3fd7circle.jpg