1. PJM©2015 Updates to PJM Load Forecast Model OPSI Annual Meeting October 12, 2015 Tom Falin Manager – Resource Planning www.pjm.com

2. PJM©2015 2 Why is the Load Forecast Important? The PJM load forecast is a key input to two PJM processes: Regional Transmission Expansion Plan (RTEP) Determines need for transmission upgrades Reliability Pricing Model (RPM) Determines amount of resources required to ensure reliability PJM is also required to provide its load forecast to several entities FERC, NERC, SERC, ReliabilityFirst, State Commissions, etc.

3. PJM©2015 3 Load Forecast Model Changes Addition of an Energy Efficiency and Saturation Variable –Historical and forecast efficiency data is obtained from Itron based on EIA data Shortened weather simulation –A summer warming trend justifies shortening the weather history from 40 years to 20 years More granular treatment of weather –To recognize that the relationship between load and weather varies across weather ranges ----------------------------------------------------------------------------------------------------------- Updated Weather Stations and Metro Areas New Load Adjustments for gain or loss of a major customer

4. PJM©2015 4 Preliminary RTO Summer Forecast Newest results are 2.8% lower than the official 2015 forecast for 2018

5. PJM©2015 5 Weather-Normalized (W/N) Peak Loads W/N peaks represent what the load would have been under typical annual peak day weather conditions –Calculated for the RTO and for individual zones W/N peaks can be used to measure load growth trends To compute the W/N peaks, PJM examines the recent relationship between load and weather and evaluates that relationship at typical peak day weather conditions.

6. PJM©2015 6 Decomposition of Forecast Changes - Summer

7. PJM©2015 7 Accuracy PJM conducted accuracy analysis on the top 10 load days (10 CPs) from each year using forecasts constructed with July 2015 vintage economics and Equipment Saturation/Efficiency data as of 2014. Forecasts were produced with estimation periods ending August 2008 through ending in August 2014 Analysis was conducted for years 2009 through 2015 –2015 analysis conducted using posted metered data and only uses data through July 31, 2015

8. PJM©2015 8 Accuracy – PJM RTO

9. PJM©2015 9 Accuracy – PJM RTO

10. PJM©2015 10 RTO Accuracy Summary Developing Equipment Index trends have only recently started to become a valuable tool in the PJM forecasting model. Prior to 2011 or 2012, the model may not have had enough information on equipment trends to make proper forecasting judgments. The New Specification has shown a tendency to get better as it gets more information, whereas the Current Specification is getting worse. On a three-year out basis the mean absolute percent error of the New Specification is 1.5% versus 6.6% for the Current Specification (an improvement of roughly 75%).

11. PJM©2015 11 Additional Information Additional information can be found on the Load Analysis Subcommittee website: http://www.pjm.com/committees-and-groups/subcommittees/las.aspxhttp://www.pjm.com/committees-and-groups/subcommittees/las.aspx –More detailed findings –Description of Weather Normalization approach –Zonal forecasts

12. PJM©2015 12 Remaining Work What is presented is NOT the 2016 Official Forecast –2015 summer load and weather data will be rolled in –Economics will be updated again –Equipment index trends will be updated with 2015 data And any additional zonal saturation data if supplied and appropriate –Any additional model changes Inclusion of annual BTM Solar Generation additions Manual language changes will be reviewed at stakeholder meetings in October and November. New load forecast will be published by end of year and will be used for 2016 RTEP and for all RPM auctions conducted in 2016.