1. NRG Comments/Concerns with HIP Assumptions January 21, 2014 RPG Meeting NRG Comments/Concerns with HIP Assumptions - January 21, 2014

2. 1 The Coastal region load (and Houston particularly) is likely to continue growing in the foreseeable future. Like the Coastal region, there are other regions in the state that are also expected to see continued load growth thanks to Texas’ growing economy (west Texas, D/FW metroplex, regions in the south and central portions of the state such as Corpus Christi, Austin/San Antonio corridor, and the Rio Grand valley.) There is not enough generation to meet the Planning load in 2018. A planning assumption of reduced load in one area of the state is electrically equivalent to adding that same amount of generation in that one area. The assumptions used in any planning scenario are the key drivers for the results. Baseline – Planning Assumptions We Should all Agree On

3. 2 Assumptions Used in ERCOT’s HIP Analysis Appear to be Pushing Towards a Particular Result SE Case Peak Planning Peak SE/PlanningPlanning - SE COAST 26,355 100% - EAST 3,088 100% - FAR_WEST 2,775 3,17687% 401 NORTH 1,473 1,74784% 274 NORTH_CE 21,924 29,51274% 7,587 SOUTH_CE 14,401 100% - SOUTHERN 7,103 100% - WEST 1,897 2,23085% 333 Total Load 79,016 87,611 Note: Planning Peak is the higher of SSWG load or the 90/10 load. Table 1: Load Reduction Assumptions Utilized in HIP Analysis

4. 3 The data in the previous slide shows that ERCOT reduced the load by greater than 8,000 MWs in the North Central, North, West and Far West weather zones, while holding the Coastal, East, South Central and South weather zones at the planning case levels. Electrically, this added 7,587 MWs of generation in the North Central load zone (a 26% reduction in load), primarily in the D/FW metroplex. Electrically equivalent to adding X amount of “zero-cost, must run” generation at each load bus where load was reduced. The size of the generation is a percentage of the peak load at the bus. The percentage was determined by how much is needed to have a “solvable” case. Note: In addition to reducing load in the North Central, North, West and Far West weather zones, the HIP analysis included mothballed generation outside the Houston region, but excluded mothballed generation inside the Houston/coastal region. This is equivalent to adding 1,273 MWs in the North and removing 206 MWs of generation from Houston and the South. What do these Assumptions Mean?

5. 4 Load Assumptions Ensure Large Quantities of Transmission are Needed to Serve Houston Reduced load 274 MW Reduced load 7,587 MW - electrically equivalent to adding a 7,587 MW unit, mainly in DFW. Also added an additional 1,273 MWs of mothballed gen. Reduced load 333 MW Reduced load 401 MW =2018 Planning peak load Undoubtedly, these types of assumptions would lead to a conclusion that major transmission infrastructure is needed into Houston from the North.

6. 5 The Assumptions Are Not Supportable For any type of HIP transmission expansion to work there has to be something to import! Is it proper to assume that generation is never added in the coastal region or the south, but approximately 10 GW is added in the North, mostly in DFW? [Load reduction plus mothballed units] Would an assumption of “any” level of generation (or load reduction) in the southern and coastal region significantly change the HIP results? The HIP assumption that load is growing in Houston and nowhere else is not supported by other Planning data. For example, ERCOT’s December 2013 Report on Existing and Potential Electric System Constraints and Needs discusses in detail the large load growth expected to continue in far west Texas and in the Denton/DFW area. North Central load in the HIP (SE) case is lower than the actual peak in 2013. A review of other data elements provided by ERCOT’s Planning Group indicates modifications to the assumptions should be made that are better supported by the data.

7. 6 If Load Reduction is Required for Planning, What is the Proper Criteria? At 10/22/13 RPG meeting, ERCOT stated that “Decreasing the loads in North, North Central, West and Far West Weather zones is reasonable because they are geographically & electrically far from the Coast Weather zone, and historical data … indicates the loads in the weather zones do not experience peaks load at the same time as the Coast weather zone. Questions: Should peak loads in other regions be based on “average” coincident peaks? A closer review shows maximum coincident peaks are closely aligned. Isn’t the HIP analysis supposed to be a “peak” case? How can an assumption of a 26% reduction of load in the North Central weather zone be justified based on the above numbers? Table 2: ERCOT Data from October 22, 2013 RPG

8. 7 ERCOT’s SGIA Data Doesn’t Support the Load Reduction Assumptions Source: ERCOT System Planning Monthly Status Report – December, 2013, Renewables Removed. Total by RegionMW% Coastal234031.4 West5707.6 North107914.5 North Central322643.3 Far West2403.2 Total7455100 Table 3 Table 4: IAs by Region Generation Interconnection Agreements as of December 31, 2013 INRSite NameCountyCODFuelMW For Grid Change from Last Report Zone 14INR0016 Channel Energy Center 138/345kV CT Harris14-JunGas190 Coastal 14INR0015Deer Park Energy CenterHarris14-JulGas190 MW for Grid Coastal 13INR0021 Ferguson Replacement Project Llano14-JulGas570 West 13INR0040Rentech ProjectHarris14-AugGas15 Coastal 10INR0021Panda Sherman PowerGrayson14-AugGas720 North 10INR0020aPanda Temple PowerBell14-AugGas717 North Central 10INR0020bPanda Temple PowerBell15-AugGas717 North Central 13INR0049 Friendswood Energy Generation Harris15-SepGas316 Coastal 13INR0023 Texas Clean Energy Project Ector16-JanCoal240 Far West 13INR0028Antelope StationHale16-JunGas359 North 06INR0006Cobisa-GreenvilleHunt16-DecGas1792 Projected COD North Central 10INR0022 Pondera King Power Project Harris16-DecGas1629 MW for Grid,Proj. COD Coastal

9. 8 Source: ERCOT System Planning Monthly Status Report – December, 2013, Renewables Removed. ERCOT’s Full Interconnect Study Data Doesn’t Support the Load Reduction Assumptions Table 5 1.1 Generation Projects Undergoing Full Interconnection Studies Interconnection Database Reference Number CountyFuel Capacity to Grid (MW) Commercial Operation (from resource developer) Zone 14INR0069MilamCoal3014-MarSouth Central 14INR0040HidalgoGas22514-JunSouth 14INR0059KaufmanGas5214-AugNorth Central 14INR0066LamarGas13014-NovNorth 13INR0054BeeGas2514-DecSouth 14INR0039EctorGas45015-MarFar West 14INR0038GalvestonGas39015-AprCoastal 15INR0053WinklerGas12315-MayFar West 15INR0054ReevesGas12315-MayFar West 15INR0055AustinGas14215-MaySouth Central 15INR0027HidalgoGas7915-JunSouth 15INR0028FreestoneGas16015-JunEast 15INR0042HoodGas46015-JunNorth Central

10. 9 Source: ERCOT System Planning Monthly Status Report – December, 2013, Renewables Removed. ERCOT’s Full Interconnect Study Data Doesn’t Support the Load Reduction Assumptions, Cont. Table 6 Table 7: Total FIS’s by Region 1.1 Generation Projects Undergoing Full Interconnection Studies Interconnection Database Reference Number CountyFuel Capacity to Grid (MW) Commercial Operation (from resource developer) Zone 15INR0023WhartonGas70015-JunCoastal 16INR0010MitchellGas79916-FebWest 16INR0009CalhounGas51016-AprCoastal 16INR0006AngelinaGas78516-JunEast 16INR0003BrazoriaGas1116-JunCoastal 16INR0004CameronGas73016-JunSouth 16INR0005CameronGas87116-JunSouth 16INR0007HidalgoGas9516-JunSouth 17INR0004HaleGas20216-JunNorth 15INR0032HaleGas19716-JulNorth 15INR0033HaleGas19716-JulNorth 16INR0013NacogdochesGas21516-JulEast 17INR0002HendersonGas48917-JunNorth Central 17INR0003JacksonGas96517-JunCoastal 17INR0007WhartonGas117717-JulCoastal 11INR0040FreestoneGas64018-MarEast Total by Region MW% C + S + SC + E W + N + NC + FW Coastal375334.23753 West7997.3 799 North7266.6 726 North Central10019.1 1001 Far West6966.3 696 South202518.52025 South Central1721.6172 East180016.41800 Total109721007,7503,222

11. 10 If There Isn’t Enough Generation, Aren’t These Load Reductions More Supportable Based on FIS Data (Table 7)? Reduce 6.6% Reduce 9.1% Reduced 7.3% Reduce 6.3% = Reduce 16.4% Reduce 34.2% Reduce 1.6% Reduce 18.5%

12. 11 If FIS Data Isn’t Considered, Then Shouldn’t Load Reductions be Closer Aligned with Actual SGIA Data (Table 4)? Reduce 14.5% Reduce 43.3% Reduced 7.6% Reduce 3.2% = Reduce 9.1% Reduce 31.4% No Change

13. 12 ERCOT’s December 17, 2013 Update on the HIP Project to the RPG included an evaluation of the impact of retirement of older than 50 year old generation “inside Houston area”. 11 units (total 1939 MW) are more than 50 year old by 2018 Sam Bertron G1, G2, G3, G4 and GT2; T.H. Warton GT1; W.A. Parish G1, G2, G3, G4, and GT1 However, if the HIP projects are dependent on imports from the north, why ignore units that will be greater than 50 years old in the North zone? The North zone contains 17 units more than 50 years old by 2018 for a total of 2,857 MW. Handley 3, Mountain Creek 6, Mountain Creek 7, Mountain Creek 8, Powerlane Plant 2, Ray Olinger 1, Spencer 4, Stryker Creek 1, Stryker Creek 2, Atkins G3, Atkins G4, Atkins G5, North Texas 1, North Texas 2, North Texas 3, Valley Unit 1, Valley Unit 2. What is basis for assumption that only >50 year old units in the Houston area will retire and others outside of Houston won’t? Other Questionable Assumptions

14. 13 The load reduction (generation addition) assumptions used to make the HIP analysis “solvable” are questionable, not supported by other available data, and can only lead to one conclusion – build major transmission infrastructure from the North into the Houston area. Approximately 10,000 MWs of new, low cost generation added in the North, primarily in the DFW metroplex. No generation added in the Coastal weather zone or in the South. Older units retire only in the Houston area, nowhere else. Mothballed generation is only available if it’s outside of Houston. Building a major transmission corridor with nothing to import could lead to stranded, costly transmission investments placed on the backs of consumers. NRG believes that more supportable assumptions would significantly alter the HIP results and likely result in a more cost-effective utilization of consumer dollars. Conclusions