5001 NASA Boulevard Famnont, WV 26554

Gary A. Jack Senior Corporate Counsel

Telephone 304 534 7409 Fax 3303159939

gack@firstenergycofp corn

March 9,2016

VIA FEDEX OVERNIG

John R. Auville, Staff Attorney Public Service Commission of West Virginia PO Box 812 Charleston, WV 25323

Re: ~onongahela Power Company and The Potomac Edison Company Case No. 15-2002-E-P

Dear Mr. Auville:

Enclosed please find a copy of ~onongahela Power Company and The Potomac Edison Company's Response to Staffs First Data Request in the above-referenced matter.

Please note that the Confidential Exhibits are in a sealed envelope and should be treated according to the Protective Agreement.

Sincerely,

Senior Corporate Counsel WV State Bar No. 1855

GA J : bsm

Enclosure

cc: Certificate of Sewice Ingrid Fenell, Executive Secretary (via FedEx wienc.)

Y

Staff requests the following:

QUE$TION NO. 1.1

Given the “significant uncertainties related to draft and final regulations issued by the United States Environmental Protection Agency (EPA) governing air, water and solid waste” (IRP, page 4):

a. Please explain why the Company’s only options for increasing generation is to purchase another coal fired generation plant?

h. Has the Company considered the risks and future costs associated with the significant uncertainties alluded to in the Executive Summary of the IRP?

c. Please provide, for the worst-case scenario, the additional costs that would be required to retrofit a supercritical, coal-fired plant equipped to mitigate the minimal EPA current (2016) requirements for future full load operation?

RESPONSE:

a. It is not the only option. Section 7 of the IRP lists and discusses many options for increasing generation and Section 7.5, page 57, of the IRP, specifically lists the lowest cost solutions which is existing coal.

b. Those risks were considered as described in Section 6 of the IRP.

c. The costs, if any, have not been developed for these potential regulations, which remain under litigation, and whose rules and requirements have yet to be defined in the state implementation plans.

Y

UESTION NO. 1.2

Provided that the load forecasting chart on page 6 of the IRP is accurate, please provide substantive data supporting how an existing coal-fired unit can provide the required generation for a deficit in generation (starting sometime in 2016) when each of the five coal-fired units currently in the generating fleet will require a substantial outage to preserve the output of those plants by retrofitting them with co-fired natural gas burners?

a. How can the Company remain in compliance with PJM requirements when at any given outage to retrofit a generating unit with co-fired natural gas burners, generation will he down by at least 546 MW?

SPONSE:

Plant outages are scheduled and approved by PJM to assure reliability is maintained. Efforts to convert for co-firing would likely be done on a unit hy unit basis which minimizes the generation that is unavailable. Additionally, these outages would he scheduled, to the extent possible, for periods during the spring and fall where usage is lowest.

a. A retrofit would be scheduled for a planned outage, usually in the spring or fait, and would be approved by PJM. Planned outages that are approved by PJM assure a plant operator remains in compliance with their requirements. There is no non- compliance with PJM requirements if a unit is not running during a planned outage for retrofits or any other maintenance or capital project.

Y

Regarding the “seasonal peak demand models” used in determining the energy sales and peak demand forecasts for the total connected and retail load (IRP, page 14):

a. What statistical model(s) idare being used for this forecast?

b. Please provide independent, documented studies indicating the accuracy of the projected outcomes of the identified model(s).

c. Do other electric utilities utilize the identified model(s) for projecting energy sales and peak demand forecasts?

RESPONSE:

a. FirstEnergy uses Itron’s MetrixND software for its statistical models for its residential, commercial and industrial customers and energy sales, and its peak demand forecasts for total connected and retail load. The model setups were done in conjunction with ITRON’s forecasting group in 2007.

Jurisdictional peak demands are forecasted using monthly regression models. The monthly peak forecasts are developed by constructing end-use appliance and equipment stock estimates from the energy models to capture end-use and class load diversity on peak demand. The regression models include both temperature sensitive (heating and cooling) and temperature insensitive (base) components as variables to capture variation in growth rates from these determinants of load. Linking the peak demand regression models to the monthly energy sales models through end-use stock estimates helps to ensure that changes in economics along with equipment saturation and efficiency levels from the energy sales models flow through to the peak forecasts.

The temperature-insensitive (base) component variable captures the impact of long- term load diversity since differences in end-use growth and customer load growth across classes impact the level and timing of peak demand.

The temperature sensitive component variables (heating and cooling) capture temperature sensitivity (megawatts per degree-day) in the respective seasons. Peak loads are driven by hot days or a series of hot days in summer and cold days in winter. It is impossible to predict exactly when these patterns will occur, but they do occur every year. In some years, the high and low temperatures are more extreme than in other years. In some years, the extremes occur on weekends, and do not produce peak energy use. For these reasons, the forecasted peak demands are based on an assumption of “normal” peak-setting temperatures, computed in terms of degree days. Future peak-setting temperatures are expected to occur such that 50% of

the values will be higher than normal and 50% will be lower. The average peak- setting conditions are the average over a historical interval.

h. In 2015, ltron conducted its “2015 Forecast Accuracy: Benchmarking Survey and Energy Trends”, which is provided as Confidential Exhibit 1.3a. FirstEnergy was one of the utilities that participated in the study.

c. Yes. Other electric utilities in the US and Canada use energy sales and peak demand forecast models similar to those used by FirstEnergy. PJM also began using Itron’s models for its most recent forecast published in January 201 6. Also, FirstEnergy staff periodically attend Itron-sponsored wehinars, training, and user group meetings, in order to network with other electric utilities and ISOs, and to keep up-to-date on current forecasting methodologies used across the US and Canada.

Regarding the “industrial sales” models used in determining the energy sales and peak demand forecasts for the major North American Industry Classification System (NAICS) (IRP, page 14):

a. What statistical model(s) islare being used for this forecast?

b. Please provide independent, documented studies indicating the accuracy of the projected outcomes of the identified model(s).

c. Do other electric utilities utilize the identified model(s) for projecting energy sales and peak demand forecasts?

a. Using Itron’s MetrixND software, the industrial sales are forecasted using multiple monthly econometric regression models. The industrial NAICS sector sales models forecast the electricity consumption by each of the major manufacturing groups; these groupings have been developed in order to reflect the most significant primary customer segments. For Monongahela Power, the major industrial groupings are “Coal Mining”, “Lumber and Wood Products”, “Chemicals”, “Glass”, “Primary Metals”, “Fabricated Metals, Machinery and Equipment”, and “Other Manufacturing”. For Potomac Ellison, the major industrial groupings are “Paper”, “Rubber & Plastics”, “Stone, Clay & Glass”, “Non-electrical Machinery, Electrical Machinery, and Transportation Equipment”, and “Other Manufacturing”. Each of the major manufacturing groups is modeled separately, while the smaller NAICS sectors are grouped together in an “Other Manufacturing” category.

In the industrial models, energy sales for each manufacturing group are forecasted using a separate, single econometric regression equation. The general specification for the econometric equations for each industrial sector is the same, although the final equations may differ because of industry-specific characteristics. Since electricity is primarily a factor input to production, its use is heavily tied to the level of production activity. Production appears as the main economic driver of electricity consumption in all the industrial model equations. The models typically use county or state-level NAICS specific gross-product as the main economic exogenous drivers. Moody’s Economy.com provides the economic series that are used as inputs to the energy sales regression models.

b. Please see response to 1.3(b). c. Please see response to 1.3(c).

Y

Regarding forecasted annual weather normalized peak growth rate (IRP, page 15):

a. In layman’s terms, please explain how “growth in the natural gas sector” primarily influences the “actual annual weather normalized peak growth rate”.

b. Please provide the supportive data and calculation in an Excel spreadsheet indicating that the actual annual weather normalized peak growth rate from 2010 through 2014 is 3.1% per year.

c. Please provide the supportive data and calculations in an Excel spreadsheet indicating that the actual annual weather normalized peak growth rate from 2015 through 2020 is 2.2% per year.

d. What is the estimated error in the model used in projecting the annual weather normalized peak growth rate (f or - of a YO)?

e. Please expand Figure 4 - Mon Power’s Historical Loads (IRP, page 16) to include years starting in 2005 through 2015. The accompanying data table shall be submitted in Excel format and in printed hardcopy.

RESPONSE:

a. The Marcellus Shale gas boom in FirstEnergy’s region has resulted in the drilling of wells, the construction of gas processing facilities and the installation of other associated equipment, especially pipelines which rely on electric compressor stations to transport gas. Accompanying this new infrastructure is an increased demand for electricity. Before it is used by consumers, the natural gas extracted from underground deposits must be processed. Gas processing plants are midstream facilities that “clean” raw natural gas by separating it into dry and liquid components to produce “pipeline quality” dry natural gas. The plants also are used to recover natural gas liquids ( i s . , natural gasoline, liquefied petroleum) and sometimes other substances, such as sulfur. These refinement and separation processes typically require large amounts of electricity.

Prior to the development of the shale natural gas industry in its West Virginia territory, FirstEnergy’s West Virginia territory experienced slower growth historically, in both MWh sales and peak demand,. This can be seen when comparing growth in the WV industrial MWh sales, the total WV weather normalized MWh sales, and weather normalized peak MW demands before and after 201 3. Prior to 2013, between 2006 and 2012, the West Virginia territory experienced -1.1% overall average annual decline in industrial MWh sales, +0.3% growth in total weather

normalized retail MWh sales, and +0.5% growth in weather normalized peak MW demands. Over the past 3 years, between 2012 and 2015, since the shale-related natural gas industry expanded in the FirstEnergy West Virginia area, the West Virginia territory saw +5.3% overall average annual growth in industrial MWh sales, and +2.4% growth in total weather normalized retail MWh sales. Between 2012 and 2014, the West Virginia area experienced +4.9% growth in weather normalized peak MW demands (2015 normalized winter seasonal peak data is not yet available).

See Exhibit 1.5a which provides supportive data and calculations.

b. The historical actual combined 3-company retail annual weather normalized peak growth rate from 2010 through 2014 is 3.3%. See Exhibit 1.5b which provides the requested supportive data and calculations. The 201 0-2014 previously used to calculate the 3.1% growth rate has been updated to correctly provide retail peak data for the combined West Virginia territory, which includes Monongahela Power-West Virginia, Potomac Edison-West Virginia, and Monongahela Power-West Virginia Power.

c. The forecasted actual combined 3-company retail annual weather normalized peak growth rate from 2015 through 2020 is 2.2%. See Exhibit 1 . 5 ~ which provides the requested supportive data and calculations.

d. Mean Absolute Deviation

MPWV 56.4 MW PEWV 18.6 MW MPWVP 3.1 MW

Mean Absolute ?A Error 3.43% 3.08% 3.87%

It should be noted that the peak models are monthly in frequency. Therefore, the Mean Absolute Deviations (MADS) and Mean Absolute Percent Errors (MAPEs) aren’t solely based on the seasonal summer and winter peak months, but include the errors in the shoulder months as well.

It is possible to compare these MAPEs to the other utilities that participated in Itron’s “201 5 Forecast Accuracy: Benchmarking Survey and Energy Trends” that was discussed and provided in response to 1.3(b). The regression models used by FirstEnergy are built using actual peaks, and actual peak-setting weather variables. Therefore, these MAPE’s compare favorably to the average MAPEs (5.05%) of the responding electric utilities in the ltron study, which is shown in the table below.

Y

e. See Exhibit 1.5d which provides the requested supportive data and calculations for the expanded Figure 4 - Mon Power’s Historical Loads (IRP, page 16), shown below. The 2010-2015 previously provided has been updated to correctly provide retail peak data for the combined West Virginia territory, which includes Monongahela Power- West Virginia, Potomac Edison-West Virginia, and Monongahela Power-West Virginia Power.

HISTORIC F ~ R ~ C A S T A D ACTUAL LOADS 3500

3030

2500

5 I 1500

1030

5W

0 2W5 2W6 2007 2W8 2029 2010 2011 2012 2013 2014 2015

Forecasted Sumrnei Peak (MW)

Actual Sununer Peak Actual Summer Peak (weather normalized)

Forecasted Winter PeaklMW)

---Actual Winter Peak - - - Actual Winter Peak (weather norrnal!red)

Note: The seasonal winter peak follows the seasonal summer peak. The summer season is June through September and the winter season is December through March of the following year. For example, the 2015 summer peak period is June

Y

1,2015 thru September 30,2015, and the 2015 winter peak period is Dec 1,2015 thru Mar 31,2016.

Date 2006 2006 2006 2006 2006 2006 2006 2006 2006 2006 2006 2006 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 2008 2008

2008 2008

2008

2008 2008

1 2 3 4 5 6 7

9 10 11 12 1 2 3 4 5 6 7 8 9

10 11 12 1 2 3 4 5 6 7

a

391.222 318.442 323,073 189,640 241,029 244,905 304,409 294,582 236,766 231,472 265,643 357,790 378.733 310.726 329,876 248,751 230.338 253,966 324.025 322,701 245,266 250,806 271,889 368.554 361,840 346,053 326,485 249,303 232,215 261,977 320,940

Comm 213.175 187,497 206.964 190.438 200,600 220,432 237.186 232,743 222,892 210,272 199.737 229,544 216.927 219.189 204,595 201,706 202,518 242,209 250,640 260,134 212,628 214,285 218,883 226,784 224,114 214,035 206,956 192,236 217,639 227,090 246,602

- Ind 354,864 369,472 370,549 363,820 384,925

370,997 41 1,300 334.974 409,816 376,803 388,563

382,035 352,825 396,048 413,150

362,413 429,763 329,494 410,247 390,060 388,244 387,154 364,055 374,723

378,796

380,745

389,352

377,748 382,248 384,608 356,034

I ,788 1,843 2,054 1,950 2,143 1,985 1,779 2,334 4,471 2,574 1,613 2,526 1,561 2.274 1,587 2,301 1,736 2,480 I ,608 2,485 1,642 2,154 2,078 2,080 1,950 1.91 9

1,957 2,160 2,013 2,038

I ,980

961,049 877,254 902,640 745,847 828,697 846,117 914,371 940,959 796,103 854,135 843,796 978,423 977,966 914,223 888,882 848,806 847,743 888,007 938,685

789,031 877,492 882,910 985,662 975,058 926,062 910,144 821,245 834,262

925,614

1,015,083

875,688

202,409 166,745 148,528 113.411 106,595 106,504 134,844 131,203 102.812 1 12,277 131,150 182,128 195.313 184,530 165,578 132,458 105.278 109,259 125,595 136.589 11 7,673 111,827 135,550 187,575 194,825 178,502 168,423 147,596 111,857 119,544 128,990

CQmm 63,465 61,272 59.616 51,690 58,672 62,638 70,532 66,409 56.990 61,014 57.819 68,317 65,879 68,283 62.373 57,506 59,890 67.804 65,125 70,042 68,956 61,811 61,209 70.769 68,046 66,092 57,118 60,923 64,858 67,499 72,873

In - 58,679 67,906 62,401 64,710 68,982 67,228 68,366 68,731 60,752 73,008 67,272 64,737 60,420 66,496 57,883 64,347

68,009 65,782

69,384

68,513 68,763

69,518 68,364

62,943 58,975 62,652 54,368 64,636 66,162 65,174 65,638

2008 2008 2008 2008 2008 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 2011 2011 2011 2011 2011

a 9

10 11 12 1 2 3 4 5 6 7 a 9

10 11 12 1 2 3 4 5 6 7

9 10 11 12 1 2 3 4 5

a

306,824 253.952 233,448 292,026 388,425 382.585 350,002 338,225 263,193 232,002 248,471 303,523 304,223 245,866 267,413 288,313 353,582 394.556 351,644 343,517 259,944 223,171 260,980 330,801

265,554 265,201 287,001 366,437 414,322 369,383 329.570 261,522 227,315

330,858

243,361 225.342 215,256

233.278 237,149 197.458 212,140 229,501 210,714 227.141 250,864 248,175 224.948 215,409 203,533 217,077 232.779 204,500 223,374 209,129 220,428 240,140 258,493 255,258 223,516 212,563 202,700 223,447 231,419 232,780 195,724 212,953 215,850

356,279 337,222 385,107

352,377 342,259 303,559 336,309

297,557 301,235 301,960 334,985 309,444 339,819 3 2 9 , a ~

339,968

375,998

298,105

326,870 341,959

357,834 326,547 347,173 333,535 335,953 364,414 329,745 358,264 343,594 351,303 333,654 346,821 355,497

327.081 395,982

2,012

2,117 2,107 I ,898 1,977 1 ,638 2,040 1,337 1,963 1,936 1,957 1,969

1,963 1,950 1,942 1,945 1,917 1,957 1,942 1,941 1,940 1,947 1,940 1,935 1,950 1,922 1,926 1,591 2,041 1,934 1,791 2.192

1,814

I ,938

908,476 819,340 835,927 892,577 975,979 963,970 852,658 888,715 792,136 742,236 778,789 858,303 889,352 782,196 824,604 823,650 899,570

898,028 971,249

926,682 797,562 792,713

927,194 953,470

836,595

820,750 837,978 835,217 943,113

951,025 980,986

883,726 872,348 772,438

124,757 11 0,365 111,963 146.804 207.822 204,958 192,171 161.584 124.346 104.330 106,122 129.446 125,997 113,355 123,341 135,803 185,194 216,087 191.433 185.891 127,692 93.561

105.661 133,929 138,258 118.459 126,957 136,325 186,391 232.212 212,582 172,544 413.857 109,726

66,532 66.014 60.519 64,106 73,991 75,745 G4.073 64,058 65,322 62,232 55,926 73.748 73,725 65,405 52.545 62,370 69,330 78,275 68.029 68,941 59,664 60,823 66,803 71,342 73.513 64,809 64,489 51,424 75,142 79,781

69.736 62,153 57,154

70,832

61,480 60,555 66,363 65,444 56,876 53,653 51,145 53,126 50.259 52,540

55,674 59,474 54,831

53,723 52,603 55.414 51.289 56,665 55,375 58,011 60,126 65,579 64,945 67,184 67,810 65,332 60,090 62,424 56,137

59,670

53,058

57,048

73,985

69,881

2011 2011 2011 2011 2011 2011 2011 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2014 2014 2014

6 7 8 9

10 11 12 1 2 3 4 5 6 7 8 9

10 11 12 1 2 3 4 5 6 7 8 9

10 11 12

1 2 3

258,091 312,604 368,249 277.164 226,370 304,657 357,953 400.353 349,596 302.484 252,766 208,053 277,979 277.289 319,848 256,570 255,236 283,035 393,084 373,753 354,477 343,923 262,274 227,845 312,250 317.218 278,970 268,600 247,251 285,884 359,651 454,552 360,959 329,481

226,572 250,807 283,785 221,046 207,750 206.519 225,253 244,904 221,929 229.234 205,487 210,987 251,973 204,810 293,613 196,395 222,390 221,696 234,729 216,858 222,162 227,415 196,940 193,351 258,249 273,627 232,938 242.678 222,645 210,411 245,433 264.860 223,335 221,137

326,129 319,982 315,048 393,288 340,969 385.219 310.621 359,981 375,630 330,601 390,242 376,819 286,747 369,210 380,936 250,669 369,779 326,106 339,179 410,239 334,438 423.945 307,127 381,410 370,752 352,950 372,539 356,199 378,595 384,282 379,867 395,174 387,175 406,466

1,753 1,755 2,192 1.968 1,714 2,066 1,849 1,693 2,104 1,985 1,596 1,796 1,775 2,694 1,799 1,759 1,578 1,879 1,879 1,884 1,686 1,886 1,640 1,890 2,001 1,866 1,865 1,866 1,863 1,760 1,854 1,835 1,720 1,715

812,545 885,148 969,273 893,463 776,803 898,461 895,676

1,006,931 949,259 864,304 850,092 797,655 818,474 854,003 996,196 705,394 848.984 832,717 968,872

1,002,734 892,963 997,169 767,982 804,496 943,252 945,661 886,311 869,343 850,354 882,337 986,804

1 ,I 16,421 973,189 958.799

Gal etail 108,293 128.989 140.200 118,509 11 0,936 152,474 202,563 211,242 196,448 173,287 11 1,453 96,580

113,899 129,184 135,503 110,060 117,571 142,613 205,912 203,862 189,755 177,061 151.785 111,905 125,554 130,008 135,135 105,795 118.71 1 149,721 196,658 245,678 186,121 183,481

74.096 67,805 75,644 69,563 58,156 65.620 73,698 75,614 74,278 71,254 50.843 68,691 72.477 71,700 75,691 72,060 69,672 63,815 73,872 74,228 70,929 77,975 57,125 57,572 78,187 77,831 76,300 65,674 67,543 70,189 77,550 81,260 73,753 75,269

70,090 68,833 80,690 63,613 73,745 66,789 63,771 62,254 71.487 56,327 44,293 72,504 82.542 64,651 54,398 96,398 76,750 56,956 64,706 69,560 60,283 74,543 44,771 81,010 66,820 78,692 69,107 68,820 72,317 68.931 66,450 64,268 60,143 65,390

2014 2014 2014 2014 2014 2014 2014 2014 2014 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015

4 5 6 7

9 10 11 12 1 2 3 4 5 6 7

9 10 11 12

a

a

265,359 256,103

315,607 31 9,703 239.321

306,194

281,752

244,887

380,580 399,018 359,327 305,009 235,314

290,074 301,661 336,003 234,549

247.804

2 3 0,7 3 a 287,351 381,227

3,398,973

3,573,498 3,535,631

3,577,499 3,679,674 3,707,297 3,576,293 3,612,095 3,754,498 3,608,076

203,224 226,107 248, I 24 264,825

212,528

240,825

226,618

206,128 228,452

255,576 232,344

227,473

242,500

220,290

250,294 248,971 266,946 226,649 219,947

242,460 214,878

2,551,480

2,669,355 2,674,115 2,707,327

2,670,498

2,711,458 2,738,147

2,820,356 2,742,709

2,794,133

383,732 381 .I 52 385,294 400,581

397,863 408,057

417,838 448,674

412,570

394,709

415,093 454,766 41 1,036 422,811 403,368

381,481 456,111

404,045 406,356 376,295 391.776

4,514,877

4,433,554 3,821,955 4,130,289

4,624,375

4,150,292 4,155,901 4,452,343 4,770,611 4,971,812

I ,852 I ,850 1 ,851 I ,854 I ,851 I ,855 1,851 1,851 I ,847 1,852 I ,853

I ,853 I ,850 I ,855 I ,853 I ,857 I ,854 I ,853 1,851 I ,826

2,099

24,060

23,965 22,609 23,263

23,986

22,846 22,538 22,261 21,931 22,455

854, I 68 865,213

982,866 989,700 871,382 867,322

917,020

930,226 1,041,090 1,092,044 1,002,892

982,164 854,331 900,917 945,591

1,008,596 986,287 867,097 858,893 880,376

1,017,290

i0,489,39i i0,854,490 10,700,372 10,096,178 10,540,552 10,591,892 10,492,879 10,829,407 11,367,397 11,396,477

Cal 133,091 113,112 119,534

130,915

113,722 154,756

251,517 203,096 163,376 129,006

124,941

128,735

98,679

209,861

100,681

135,887 146,498 103,829

145,582 213.780

107,707

1,638,606

1,751,448 1,707,231

1,706,647 1,760,644 1,801,885 1,743,752 1,795,949 1,817,686 1,825,900

62,261 67,514 73,498 76,892

67,087

69,881 78,055 82,864

73,912

66,091

77,526 71,799 62,293 67,656

74,073

67,334 65,776 64,435 77,024

73,278

7 8 , ~ I

7 3 a ~ 4 3 4

788,571 804,479 813,554

839,967 851,102 865,472 862,969

779,647

824,248

64,421 70, I 89 68,599 73,094 72,507 70,099 73,399 70,128 67,233 62,796 61,325 59,687 67,484 70,321 71,647 75,101 73,546 70,265

66,315 70,346

70,786

792,772 790,391 748,321 647,134

809,629 727,820

803,266 821,305 819,469 819,621

Cal etail

CAGRs 2006-2012 0.9% 1.2% -1.4% -1.1% 0.0% 1.0% 2.2% 0.2% 2012-2014 2.5% 1.5% 7.1% -1.4% 4.1% 2.1% 1.5% 1.0% 2012-2015 0.3% 0.7% 6.2% -0.1% 2.8% 1.5% 0.9% 0.7%

Gal

Total - PSHL Total Retail Tot Res Comm - Ind - PSHL Total Retail

391 409 422 405

439 445 435 403 492 437 455

420

447 490 471 447 463 460 494 467 470 452

397 496 525 51 3

468

484

428

480

483

324,944 296,333 270,967 230,216 234,717 236,809 274,186

220,958 266,778

246,791 256,679 315,637 322,096 319,730 286,262 254,757 235,042 245,543 256,950 275,607

242,495 266,744 321,727

255,857

322,298

280,306 307,726

273,651 243,402 252,731 267,984

593.631 485,187 471,601 303,059 347,624 351,409 439.253 425,785 339,578 343,749 396,793 539,918 574.046 495,256 495.454 381,209 335,616 363,225 449,620 459,290 362,945 362,633 407,439 556,129 556,665 524,555 494,908 396,899 344,072 381.521 449,930

246,769 266.580 242,128 259,272 263,070 307.718 299,152 279,882 271,286 257,556 297.861 262,806 287,472 266,968 259.212 262,408 310,013 315,765 330,176 281,584 276,096 280,092 297,553 292,160 280,127 264,074 253,159 282.497 294,589 319,475

___ 413,543 437,379 432,950

453,907 446,023 439,362

395,726

444,075 453,299 441,165

41 0,707 460,395

457,360

428,530

480,031

482,824

448,531

482,534

428,195 498,276 398,257 478.61 I 459,578 451,157 446,129 426,707 429,091 442,384 448,410

421,672 449,783

2,179 1,285,993 2,252 2,476 2,355 2,611 2,424 2,224 2,769

3,067 2,050

2,045 2,694 2,015 2,747 2,227 2,952 2,055 2,948 2,102 2,648 2,545 2,550 2,402 2,400 2,377 2,454

2,526 2,520

I ,875

2,981

2,685

1,173,587 1,173,608

976,064 1,063,414 1,082,926 1,188,558 1,207,737 1,017,061 1,100,926 1,100,474 1,294,060 1,300,062 1,233,953 1,175,145 1,103,563

1,133,550 1,195,635 1,290,690

1,082,785

1,044,888 1,119,988

1,307,389

1,233,788

1,094,895

1,128,419

1,149,653

1,297,356

1,190,450

1,077,664

1,193,597

464

536 392 567 455 396 467 337 492 441

506 453 500 462

458

486

448 509 424 508 502 474 474 512 52 1 452 516 444 476

505 432 530

480

488

253,233 237,391

276,746 339,257

239.380

334,811 307,784 279,235 240,264 219,594 225,546 259,354 259,703 234,045 243,434 252,357 307,574 350,285 311,176 312,005 243,233

233,064 271,662 277,237 250,904 259,772 263,525 322,099

340,056 316,697 236,210 237,259

212,869

374,897

431,584 364,327 345.411 438,830 596,247 587,543 542,173 499,810 387.539 336,332 354,593 432,969 430,220 359,221 390,754 424,116 538.876 610,653 543,077 529,408 387.636 316,732 366,641 464,730 469,116 384,013 392,158 423,326 552,828 646,534 581,965 502,114 375,479 337.041

309,893 292,356 275.775 286.552 307,269 312,894 261.531 276,198 294,823 272.946 293,073 324,612 321,900 290,353 277,954 265,903 286,407 31 1,054 272,529 292,315 268,793 281,251 306,943 330,135 329.771 288,325 277,052 264.124 298.589 311,200 303,612 266,460 275,106 273,014

417,758 397,777 451,469 441,442 409,253 395,912 354.704 389,436

350,097 354,293 357,634 394,459 364,276 396,867 383,577 379.472 397,373 391,257 414,499

405,184 393,661 402,532 429,359 396,929 426,074

41 1,392

402,958

455,652 396,962

38,364

381,922

408,927

396,078

429,483

2,476 2,272 2,653 2,499 2,466 2,432 2,034 2,507 1,673 2,455 2,377 2,443 2,475 2,391 2,463 2,411 2,389 2,454 2,541 2,465 2,444 2,416 2.413 2,459 2,461

2,466 2,366 2,402 2,071 2,546 2,366 2,321 2,680

2,388

i,i61,708

1,075,308

1,298,781

1,056,732

1,169,323 1,315,235

1,160,442 1,167,951 1,032,399

1,004,336 1,117,657 1,149,054 1,016,241

1,076,007 1,207,145 1,321,534 1,209,204

1,040,795

961,830

1,068,038

1,238,687

1,005,583 1,069,658 i,iga,as6 1,230,707 1,071,654 1,097,750

1,265,211

1,291,081 1,200,423

1,009,697

1,098,743

1,355,883

1,108,559

430 51 9 508 454 524 501 400 506 467 515 519 367 498 637 533 451 362 457 507 483 454 470 51 8 507 452 488 481 48 1 481 481 481 483 446 452

252,909 266,146 297,042 252,139 243,361 285,384 339,432 349,616 342,681 301,383 207,108 238,141 269,416 266,171 266,124 278,968 264,355 263,842 344,997 348,133 321,421 330,048 254,199 250,993 271,013 287,018 281,023 240,769 259,053 289,321 341,139 391,689 320,464 324,592

366,384 441,593 508,449 395,670 337,306 457.131 559,516 611,595 546,044 475.771 364,219 304,633 391,878 406,472 455,351 366,630 372,807 425,649 598,996 577,615 524,231 520,983 414,059 339,750 437,803 447,225 414,105 374,396 365,962 435,605 556,309 700,231 547,080 512,962

300,668 318,612 359,429 290,609 265,906 272.139 298,951

296,207 300.488 256,330 279,677 324,450 276,509 369,304 268,455 292,063 285,511 308,601 291,085 293,092 305,390 254,065 250,923 3 3 6,4 3 7 351,458 3 0 9,2 3 8 308,352 290,189 280,600 322,983 346,120 297,088 296,406

320,518

396,219 388,815 395,738 456,900 414,715 452,009 374,392 422,235 447,117 386,928 434,535 449,322 369,289 433,861 435,334 347,067 446,528 383,063 403,886 479,800 394,722 498,489 351,898 462,419 437,573 431,642 441,645 425,018 450,913 453,213 446,317 459,442 447,318 471,856

2,183 2,274 2,699 2,422 2,238 2,567 2,249 2,198 2,571 2,500 2,115 2,163 2,273 3,331 2,332 2,210 1,940 2,336 2,385 2,367 2,340 2,355 2,158 2,397 2,453 2,354 2,346 2,347 2,344 2,241 2,335 2,318 2,166 2,167

1,065,455 1,151,294 1,266,315 1,145,601 1,020,164 1,183,845 1,235,108 1,356,546 1,291,940 1,165,687 1,057,200 1,035,796 1,087,890 1,120,174 1,262,320

984.362 1 , I 13,338 1,096,559 1,313,869 1,350,867 1,214,384 1,327,217 1,022,180 1,055,489 1,214,265 1,232,679 1,167,334 1,110,113 1,109,407 1,171,659 1,327,943 1,508.1 10 1,293,652 1,283,391

480 487 483

489 484 483

483

477

483

474 491 53 1

476

495

462 473 443 509

488

481

482

5,203 5,542 5,764 5,442 5,813 5,770 5,818 5,776 5,729 5,804

260,253 251,302 262,114

277,822 236,350 253,694 295,248 355,632 397,652

295,392 259,271 239,134

279,i 98

342,438

270,348 285,556 299.438 241,890 244,742 276,775 361,659

3,175,015

3,294,104 3,163,702 3,307,831 3,441,532 3,392,803 3,474,131 3,508,356 3,514,295

3,282,811

398,450 369,215

444,341 401,286

450,618 338,000 358,608 460,950 590,441 650,535 562,423

364,320

415,015

468,385

348,484

437,548 482,502 338,378 338,445 432,933 595,007

5,037,579 5,242,862 5,324,946 5,284,146 5,440,318

5,320,045 5,509,182

5,408,043 5,572,184 5,433,977

265,485 448,154 293,621 451,342 321,621 453,893 341,717 473,675 329,488 485,077 299,431 467,962 278,619 481,456 297,354 464,836 318,880 485,070 325,365 511,471 304,145 476,419 292,089 514,452 268,421 478,521 296,108 493,132 323,572 475,015 323,044 531,212 345,856 455,027 293,983 474,310 285,723 477.142 279,314 442.610 319,484 462,122

3,289,914 3,450,145 3,457,926 3,478,594

3,535,706 3,578,114

3,685,829 3,657,103

3,520,881

3,593,811

5,307,649 5,414,766

4,469,089 4,858,109 4,959,920 4,959,167 5,273,647 5,590,081 5,791,433

5,181,875

2,332 2,337 2,334 2,331 2,340 2,339 2,333 2,334 2,330 2,326 2,344 2,630 2,341 2,326 2,337

2,339 2,316 2,325 2,294 2.335

2,348

29,264

29,728 28,052 29,076 28,616 28,356 28,036 27,660 28,260

29,528

1,114,421 1,116,515 1 ,I 79,134 1,262,064 1,267,522 1 ,I 07,731 1,121,016 1,225,474 1,396,721

1,345,330 1,277,556 1 ,I 13,602 1,140,050 1,215,939 1,294,152

I ,489,696

1,285,725 I ,108,987

1,378,948

1 ,I 03,635 1 ,I 57,151

13,664,406 14,137,301 13,994,475 13,259,881

14,033,425 13,848,383

13,885,682 14,303,538 14,875,753 14,910,772

1.9% -0.8% -0.1%

1.1% 1.7% 1.2%

0.9% 2.3% 0.7%

1.4% -1.1% 1.5% 6.2% 0.7% 5.3%

Cat

-0.5% 0.3% -1.2% 3.5% -0.1% 2.4%

- Year 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Summer Season 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Actual Summer Pk 2,459 2,623 2,613 2,506 2,375 2,555 2,718 2,617 2,654 2,516 2,614

WN Summer Pk 2,413 2,546 2,543 2,543 2,537 2,545 2,549 2,562 2,587 2,657 2,635

istorical - Year Winter Season

2005 2005106 2006 2006107 2007 2007108 2008 2008109 2009 2009110 2010 2010/11 2011 2011112 2012 2012113 2013 2013114 2014 2014115 2015 2015116

CAGRs 2006-2012 2012-2014

0.1% 1.8%

Actual Winter Pk WN Winter Pk 2,404 2,604 2,761 2,639 2,523 2,625 2,723 2,722 2,587 2,700 2,657 2,634 2,631 2,719 2,744 2,725 3,032 2,843 3,147 2,997

N/A N/A

0.5% 4.9%

WN Annual Pk 2,604 2,639 2,625 2,722 2,700 2,634 2,719 2,725 2,843 2,997

N/A

0.5% 4.9%

- Year Summer Season Actual Summer Pk WN Summer Pk 2010 2010 2.555 2.545 2011 2011 2,718 2,549 2012 2012 2,617 2,562

2014 2014 2,516 2,657 2013 2013 2,654 2,587

CAGRs 2010-2014 1.1%

Exhibit 1.5b Historical Peak Growth Rates

Winter Season Actual Winter Pk WN Winter Pk WN Annual Pk 2010 2010/11 2,657 2,634 2,634 2011 2011112 2,631 2,719 2,719 2012 2012113 2,744 2,725 2,725 2013 2013114 3,032 2,843 2,843 2014 2014115 3,147 2,997 2,997

3.3% 3.3%

2015 2016 2017 2018 2019 2020

2015.2020 Compound Average Annual Growth Rate

Summer %awn PeaklMW1 CHYA ShCHYA 2853 2967 114 4.0% 3047 81 2.7% 3150 103 3.4% 3275 125 4.0% 3283 8 0.3%

2.8%

Winter Season Peak CMWl CHYA %CHYA 3OQO 3071 71 2.4% 3156 85 2.8% 3300 144 4.6% 3342 42 1.3% 3344 2 0.1%

2.2%

Exhibit 1 . 5 ~ WV Peak Forecast Growth

Annual Peak CMW) CHYA %CHYA 3000 3071 71 2.4% 3156 85 2.8% 3300 144 4.6% 3342 42 1.3% 3344 2 0.1%

2.2%

Exhibit 1.5s 2015-2030 Peak Forecast

2014 9+3 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 14 15 16 17 18 19 20 21 22

PeakMW C 0 rn p a n y MP

2015 2016 ,urirdiction I llan Feb Mar Apr May ,Jn 1uI Aug Sep On No" Oer (Total .an Fen Mar Apr May . ~ n JLI Aug - wv IP fa iMW 11.980 1.900 1,806 1.635 1756 2.015 2.116 2.116 1.906 1.693 1.764 1.94012.116 2.075 ?.m9 1.920 1,750 1.870 2.118 2.221 2,221 lil"P I P B ~ ~ M W I 139 117 110 94 83 88 93 95 90 91 106 1241 139 136 121 110 94 84 89 94 96

Summerpeak hwinter PeakMW Annual Peak M W 2015 2853 3,OW 3000 2016 2967 3,071 3071 2017 3047 3,156 3156 2018 3150 3,300 3300 2019 3,275 3,342 3342 2020 3,283 3,344 3344

Exhibit 1 . 5 ~ 2015-2030 Peak Forecast

23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51

Exhibit 1 . 5 ~ 2015-2030 Peak Forecast

Fen Mar AQr May 1un Jut Aug Seo O n NOv Oec Ilotal 2,312 2,282 2.085 2,204 2.328 2 821 2.510 2.364 2,136 2.196 2.2901 2.821 123 112 98 86 90 96 97 92 93 108 1261 138

I

52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 2020 2021

Jan Feo Mar Apr May Iun I d A L ~ Sep OR hov Uec l i m a Ian feo 2.416 2.341 2,270 2.094 2.212 2.432 2.528 2.817 2,367 2,139 2.198 2,292) 2.828 2,419 2,344 138 123 112 96 86 W 96 97 92 92 107 1261 138 138 123

I

Exhiblt 1.Jd Table

' A I d M presented in this table 111 forthe cambinad MP-WesI vlqimla and PE-West Vlqlnla and MPWest Wqlnla Pomr I & q .

20042014 Weather-normalized data estimated at this time, should be available mid-March 2016 20042015 Weather-normalized data should be available mid-May2016.

HISTORIC FORECAST AND ACTUAL LOADS 3iw

Exhibit 1.5d WV Hist Peaks-Estimat WN 3.1.16

Alternative Weather+&&& Peab for WV INCLUDING WVP

wv excl WVP Retail Summer

Winter

winter

WVP Retail summer

winter

Actual MW Date Hour Weather-Adjusted Adjustment

Actual Date Hour Weather-Adjusted Adjustment

ActualMW Date

Weather-Adjusted Adjustment

Actual Date now Weather-Adjusted Adjustment

now

ActualMW Date H0"r Weather-Adjusted Adjustment

Actual

12/3/2015 Values (MWI 2002 2003 2004 2005 2006 2 W 7 2008 2009 2010 2011 2012 2013 2014 2015

2,275.7 2.232.6 2,149.4 2,370.7 2,531.1 2,516.9 2,416.3 2.287.4 2,457.5 2,615.5 2,519.4 2.567.0 2.430.9 2,528.3 7/22/02 8/21/03 6/9/04 8/12/05 8/3/06 8/24/07 6/9/08 8/17/09 7/7/10 7/21/11 7/26/12 7/18/13 7/22/14 8/17/15 16 16 16 16 15 16 16 16 16 17 16 16 17 17

2,256.5 2,285.9 2,252.8 2,322.8 2,454.2 2,450.5 2,447.2 2,440.2 2,450.0 2,455.7 2.471.4 2.504.7 2.571.6 2,549.2 (19.2) 53.4 103.4 (47.9) (76.8) (66.5) 30.8 152.8 (7.5) (159.8) (48.0) (62.3) 140.8 20.9

2,329.3 2,268.1 2,446.4 2,305.9 2,637.7 2,406.9 2,587.9 2,478.3 2,539.5 2.511.3 2.619.4 2,889.6 2,993.5 1/23/03 1/23/04 1/18/05 12/14/05 2/6/07 1/4/08 1/16/09 1/29/10 1/24/11 1/3/12 1/23/13 1/29/14 2120115

20 9 9 8 8 8 9 8 a 19 8 8 8 2,270.6 2,324.7 2,386.9 2,497.4 2,518.7 2.503.6 2.589.3 2,591.5 2,512.0 2.590.4 2,595.5 2,718.5 2,857.1 (58.6) 56.6 (59.5) 191.5 (118.9) 96.6 1.4 113.3 (27.41 79.1 (23.9) 1171.21 1136.41

2.310.6 2,267.2 2,181.2 2,4092 2,571.0 2.554.2 2,456.0 2,327.7 2,497.7 2,652.9 2,556.4 2,602.5 2.469.3 2,562.2 7/22/02 8/21/03 6/9/04 8/12/05 8/3/06 8/24/07 6/9/08 8/17/09 7/7\10 7/21/11 7/26/12 7/18/13 7/22/14 8/17/15

16 16 16 16 15 16 16 16 16 17 16 16 17 17 2,291.9 2,317.7 2,288.0 2,359.7 2.492.7 2,489.0 2.487.7 2,481.9 2,491.0 2,490.6 2,507.2 2,539.6 2.609.3 2,584.2 (18.8) 50.4 106.8 (49.4) (78.2) 165.31 31.7 154.2 (6.7) (162.3) (49.2) (62.9) 139.9 22.0

2,363.7 2,299.2 2,478.7 2,335.6 2,674.6 2,440.1 2,627.1 2,512.6 2,568.7 2,541.2 2,650.2 2,924.8 3,028.3 1/23/03 1/23/04 1/18/05 12/14/05 2/6/07 1/4/08 1/16/09 1/29/10 1/24/11 1/3/12 1/23/13 1/23/14 2/20/15 . . . . . . . . . . 20 9 9 8 8 8 9 8 8 19 8 8 8

2,291.8 2,358.4 2.427.3 2,531.1 2,552.8 2.536.6 2,626.4 2,629.2 2.550.6 2.618.2 2,625.2 2.749.8 2.888.9 (71.9) 59.2 (51.4) 195.5 (121.8) 96.5 (0.7) 116.6 (18.1) 77.0 (25.0) (175.0) (139.3)

81.4 80.5 79.8 89.2 94.3 100.8 90.0 87.9 98.5 104.0 103.1 94.0 92.8 93.9 8/5/02 8/28/03 7/6/04 7/25/05 8/2/06 8/9/07 6/9/08 8/17/09 8/4/10 7/22/11 6/29/12 7/16/13 7/2/14 7/20115 15 16 17 17 16 17 17 16 16 16 17 16 15 17 81.2 80.3 87.1 91.3 93.9 96.7 96.1 96.8 96.5 95.3 96.1 89.3 93.0 93.6 (0.21 (0.21 7.3 2.1 (0.3) (4.2) 6.1 8.9 (1.9) (8.7) (7.0) (4.71 0.3 10.31

109.0 103.2 110.7 108.9 123.0 118.9 134.7 135.0 133.1 122.5 124.9 152.8 153.9

Date H0”C

Weather-Adjusted Adjustment

Zonal Summer Actual MW Date Hour Weather-Adjusted Ad)urtment

Winter Actual Date H O W

Weather-Adjusted Adlustment

wv lncl WVP Retail Summer

Estimated

Winter

E ~ ~ i ~ ~ ~ ~ ~

zonal Summer

Estimated

winter

Actual MW Date HI)”( Weather-Adjusted Adjustment

Actual Date HOW

Weather-Adjusted Adjustment

Actual M W Date H O W

Weather-Adjusted Adjustment

Actual

1/23/03 1/23/04 12/20/04 12/21/05 19 9 9 8

104.5 108.2 110.9 116.6 (4.41 5.0 0.2 7.7

81.4 80.5 79.8 89.2 8/5/02 8/28/03 7/6/04 7/25/05

15 16 17 17 81.2 80.3 87.1 91.3 (0.2) (0.2) 7.3 2.1

109.0 103.2 110.7 108.9 1/23/03 1/23/04 12120l04 12/21/05 19 9 9 8 104.5 108.2 110.9 116.6 (4.4) 5.0 0.2 7.7

2/6/07 8

120.5 (2.51

94.3 8/2/06

16 93.9 10.3)

123.0 2/6/07 8 120.5 12.51

1/21/08 1/16/09 1/11/10 12/14/10 9 9 9 9

124.3 132.8 134.7 137.8 5.3 (1.9) (0.3) 4.7

100.8 90.0 87.9 98.5 8/3/07

17 96.7 (4.21

118.9

9 124.3 5.3

1/21/08

6/9/08 17

96.1 6.1

134.7 1/16/09

9 132.8 (1.9)

8/17/09 8/4/10 16 16

96.8 96.5 8.9 (1.9)

135.0 133.1 1/11/10 12/14/10

9 9 134.7 137.8 (0.3) 4.7

Exhibit 1.5d WV Hist Peaks-Estimat WN 3.1.16

1/4/12 1/23/13 1/7/14 2/20/lS 8 8 8 8

131.3 129.0 134.9 139.9 8.7 4.1 117.9) (13.9)

104.0 103.1 94.0 92.8 93.9 7/22/11 6/29/12 7/16/13 7/2/14 7120115

16 17 16 15 17 95.3 96.1 89.3 93.0 93.6

0.3 10.3) (8.7) (7.0) (4.7)

122.5 124.9 152.8 153.9 1/4/12 1/23/13 1/7/14 2/20/15 8 8 8 8 131.3 129.0 134.9 139.9 8.7 4.1 117.9) (13.9)

2.353.7 2.308.5 7/22/02 8/21/03 16 16

2,334.2 2,361.7 (19.5) 53.2

2,437.3 2,371.3 1/23/03 1/23/04 20 9

2,374.3 2,432.9 (63.1) 61.6

2,388.6 2,343.2 7/22/02 8/21/03

16 16 2,369.6 2,393.5

(19.0) 50.3

2.471.7 2,402.4

16 16 15 16 16 16 16 17 16 16 17 16

1107 (459) (772) (706) 370 1616 (9 4) (1684) (550) (670) 141 1 20 6 23344

2,553 8 1/18/05 12/14/05 2/6/07 1/4/08 1/16/09 1/29/10 1/24/11 1/3/12 1/23/13 1/29/14 2120115

0 II II II 9 U U 19 U R U - I - - - - _ _ - 2 494 5 (593) 1992 (1214) 1020 (05) 1130 (227) 878 (198) (1891) (1504)

2.255.7 2,497.3 2,663.2 2,650.8 2,545.3 2,415.7 2.594.9 2,755.0 2,653.5 2,689.5 2,554.1 2,648.8 8/19/04 8/12/05 8/3/06 8/24/07 6/9/08 8/17/09 7/7/10 7/21/11 7/26/12 7/18/13 7/22/14 9/8/15 16 16 15 16 16 16 16 17 16 16 17 16

2,369.9 2,450.0 2,584.6 2,581.3 2,583.1 2,578.7 2,586.3 2,584.0 2,597.4 2,622.0 2,694.3 2,670.5 114.2 (47.3) (78.6) (69.4) 37.8 163.0 (8.6) (171.0) (56.1) (67.6) 140.2 21.7

2,586.1 2,434.1 2,797.6 2,555.9 2,761.8 2,621.5 2,686.1 2,660.6 2,775.1 3,067.1 3,182.1

Exhibit 1.5d WV Hist Peaks-Estimat WN 3.1.16

Date 1/23/03 1/23/04 1/18/05 12/14/05 2/6/07 1/4/08 1/16/09 1/29/10 1/24/11 1/3/12 1/23/13 1/29/14 2/20/15 Hour 20 9 9 8 8 8 9 8 8 19 8 8 8

Estimated Weather-Adjusted 2,395.4 2,466.5 2,534.9 2,637.3 2,673.3 2,657.7 2,759.2 2,737.8 2,672.7 2,746.3 2,754.2 2,874.2 3,028.9 Adjustment (76.3) 64.1 (51.2) 203.2 (124.3) 101.8 (2.71 116.3 (13.4) 85.7 (20.91 (192.9) (153.3)

William Moll 3/1/2016

Exhibit 1.M WV3 Peaks @ PJM Peak Hr

Allegheny Retail Loads at Time of PIM Peaks (MW)

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 7/26/2WS 5PM (EFT) 8/2/2W6 5PM (EPT) 8/8/2W74PM (EPT) 6/9/2008 5PM (Em 8/10/20094PM ( E m 7/7/2010 5PM (EPT) 7/21/2011 5PM (Em) 7/17/2012 5PM (EPT) 7/18/2013 5PM (Em) 6/17/2014 6PM (EPT) 7/28/2015 5PM (EPT)

AYE (w WVP) AYE (wo WVP) WPP MP WVP PEWV PEMD

1.692 I 88

562

.,a95 1,810 1,824 1,558 1,816 1.952 1,848 1.897 1.758 1 95 96 89 83 97 101 93 87 87

624 595 592 580 642 659 661 670 601

..818 90

610

PEVA wv (W WVP) wv (WO WVPI

2,352 2,613 2.562 2,506 2,221 2,555 2,712 2,601 2.654 2,446 2,518

WCMoll 2/29/1016

Summer Peak Forecasts LFWW

2005 MPWV 1,815 MPWVP 86 P E W 540 Sum 2,441 3Co Peak 2,446 Diversitv 0.9981

LFOSCI~ 2006 1,842

85 543

2,470 2,446

1.0100

LFO693 2007 1,814

86 606

2,506 2,481

1.0100

LFO793 2008 1,901

89 646

2,636 2,575

1.0238

LF0893 2009 1,9W

93 632

2,625 2,593

1.0122

LFO9Q3 2010 1,759

94 611

2,463 2,447

1.0067

LF1093 2011 1,836

95 622

2,553 2,534

1.0076

LF1193 2012 1.877

98 644

2,619 2,601

1.0067

LF1293 2013 1.877

97 649

2,622 2,602

1.0078

LF130.3 2014 1,973

95 664

2,732 2,711

1.0076

LF1493 2015 2,148

94 675

2,917 2,896 1.0074

Winter Peak Forecasts LFOSCM LFo6CU LFO793 LFOSQ3 LM993 lF1093 LFllQ3 LF-1293 LF1393 LF1493 LF1593

MPWV 1,740 1,765 1,802 1,785 1,667 1,780 1,824 1,842 1,837 1,953 2,075 MPWVP 105 110 113 115 118 127 131 131 131 136 136 PEWV 589 690 769 750 763 775 814 819 834 840 850 Sum 2,434 2,564 2,684 2,651 2,548 2,682 2,769 2,792 2,802 2,929 3,061 3Co Peak 2,410 2.548 2,606 2.584 2,509 2,648 2,728 2,754 2,768 2,889 3,019 Diversitv 1.0100 1.0065 1.0298 1.0257 1.0154 1.0129 1.0149 1.0140 1.0122 1.0140 1.0139

2005106 2006107 200710s 2008109 20091lO 2010111 2011112 2012113 2013114 2014115 2015116

~xhibi t 1.56 F o ~ c a s ~

Ailegheny Power Electric Default Service Forecast - Peak 2004 Base Case Load Forecast (LF0410)

1,628 1,605 1.414 1,498 1,

2,595 2,539 2,400 2,063 2,028 2,318 2,439 2,439 2,162 2,014 2,111 I w PURPA

I DPURPAl - - I -

Exhi~it 1.5d

Alleghefly Power Electric Default Service Forecast - Peak 2006 Final Load Forecast (LF05Q4)

w 1,636 1,627 l A O l 1,496 1,763 1.842 1,635 1,477 1,541 Total 1,636 1,627 1,401 1,496 1,763 1,842 1.635 1.477 1,541

M PURPA

1,184 1,052

Exhibit 1.56

Exhlbit 1.5d LF06Cl3 DS WV Peaks

Allegheny Power Default Service Load Forecast - Peak 2006 Fin& Load Foremst (LF0603) Actuds Thmugh April 2 w 6

Exhibit 1.5d LFOGQ3 OS WV Peaks

Exhibit i.5d LFO703 DS WV Peaks

Allegheny Power Default Sewice Load Forecast. Peak MW 2008 Susiimsl Plan Load Fonnsl (LFO7Q3) Acbslrmmughl\[xil2WT

M a dfPnk MW

Exhibit t.5d LFOBQ3 DS WV Peaks

Allegheny Power Default Service Load Forecast. Peak MW 2009 Budgat L w d FoRead (LF08W A~"slarnm"gh~"ns 2oQa

Exhibit 4.w LFWEI3 DS WV Peaks

Allegheny Power Default Service Forecast Peak MW

A ~ W I ~ mmgh A U ~ U S ~ zw9 ZQOSThirdQusner Load Fomcsli~(LFW3)

WinterPBsk MW

Exhlblt l.M LFIOQ3 DS WV Peaks

Allegheny Power Default Selvlce Forecast Peak MW MIOThid Qvansr Load Foncelt (LFIWB) Aduais mmugn May 2010

..~ .........

Summerpeak MW

Winter Peak MW

Allegheny Power Default Service Forecast Peak Mw ~ ~ ~ ~ m m ~ g b ~(lyz011 2011 Thim OUBner Load Fommd lLFliQ3)

Summer Peak Mw

winter Peak Mw

Exhlblt 1.5d LFIiQ3DSWVPeeks

Exhibit 1.5d LF1295 DS WV Peaks

.... . ....... ,~. .,. ~ ~

.rear.. . .YO!!! ......... ........................ .Msxof Peak MW . ..

....,. .... .....

Summer Peek MW

....

Winter Peak NMI

....... ___ ............... 1163 2447.22 2499j

WV Summer DS Peak Forecasts (MW) Year MPWV PEWV MPWVP WV 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

1.660 1,745 1,807 1,764 1,661 1,803 1,913 1,942 1,824 1,732 1,841 1,969 1,888 1,972 1,973

449 513 513 506 527 586 626 622 595 582 648 694 677 669 664

74 79 81 80 80 89 94 101 90 88 98 104 103 95 2,716 95

WV Winter DS Peak Forecasts (MW) MPWV PEWV MPWVP WV 1,597 1,582 1,710 1,665 1,757 1,678 1,836 1,733 1,768 1,764 1,720 1,769 1,836 1,837 1,871

548 536 640 640 700 707 802 732 828 754 852 813 826 834 845

93 94 109 103 111 109 123 119 137 135 133 123 125 131 132 2,813

Exhibit 1.Sd

LF13Q3 Total WV forecasted peaks calculated using historical diversity factors (year 2000 thru 2013)

Exhibit 1.5d

Year MPWV.APeakDS.SumPeak MPWV.APeakDS.WinPeak WVP.APeakDS.SumPeak WVP.APeakDS.WinPeak PEWV.APeakDS.SumPeak PEWV.APeakDS.WinPeak MPWVcPEWV.APeakDS.SumPeak 2014 2,472 2015 2016 2,311 2,198 9s 138 689 857 2,978

. .. .

MPWV+PEWV+WVP.APeakDS.SumPe k

3,011 3,073 3,149

~xhibit 1.56

Exhibit 1.5d

Year MPWV.APeakDS.SumPeak MPWV.APeakDS.WinPeak MPWVP.APeakDS.SumPeak MPWVP.APeakDS.WinPeak PEWV.APeakDS.SumPeak PEWV.APeakDS.WinPeak 2015 2016 2017 2,230 96 137 fiaa a53

MPWV+PEWV+WVP.APeakDS.SumPe k MPWV+PEWV.SumDSPeak.WVPea

3,040 3,062 3,177 2,965

Exhibi~ 1.5d

Y

Regarding Forecast Loads, please provide the following information (IRP, page 17):

a. Please provide the actual data used in developing Figure 5 - PEAK FORECAST. The data should be provided in Excel format and in printed hardcopy.

b. Provide data supporting the statement that “the summer peak demand [is] generally consistent with PJM’s peak demand”.

RESPONSE:

a. See Exhibit 1.6a which provides the requested supportive data and calculations.

b. A direct comparison for WV is not available since PJM does not forecast state- specific peak demands. Also, FirstEnergy’s Monongaheia Power and Potomac Edison‘s West Virginia territory is part of PJM’s APS zone, but the West Virginia Power portion of Monongahela Power’s territory is part of the AEP zone in PJM. PJM’s winter and summer peak forecast trends and growth rates are generally consistent, but less than, the WV portion of FirstEnergy’s territory.

For its 2016 Load Forecast, PJM solicited input for large changes in load from all the member utilities. FirstEnergy submitted various recommended load changes, including additions for the Monongahela Power territory related to the additional demand expected by the Marcellus Shale growth. Both PJM and Monongahela Power are consistent in that they show growth, although Monongahela Power’s growth is larger than PJM’s overall predicted growth.

Over the next four years (2016-2019), FirstEnergy is projecting average annual growth rates of 3.3% for the summer peaks and 2.9% for the winter peaks for its combined West Virginia territory plus a loss of capacity due to PJM’s capacity performance rules.

It is possible to compare the forecasted longer-term 10-year average annual growth rates of the other utilities that participated in Itron’s “2015 Forecast Accuracy: Benchmarking Survey and Energy Trends” that was discussed and provided in response to 1.3(b), which are shown in the table below.

Y

Figure 15: Peak Grwth

See Exhibit 1.6b which provides the requested supportive data and calculations.

Annual Peaks Annual Peaks Forecasted Summer Peak (MW) Forecasted Winter Peak (MW)

2016 2967 3000 2017 3047 3071 2018 3150 3156 2019 3275 3300 2020 3283 3342 2021 3291 3344 2022 3304 3353 2023 3320 3364 2024 3338 3379 2025 3348 3385 2026 3362 3394 2027 3375 3403 2028 3393 3416 2029 3406 3424 2030 3418 3433

Exhibit 1.6a 2016.2030 Calendar Peaks Chart

FORECASTED LOADS - CALENDAR YEARS

3100

3400

3300

3200

3100

3000

2900

2800

2700 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2078 2029 2030

m Forecasted Summer Peak (MW) Forecaiied winter Peak(MW)

Exhibit 1.6a 2Q~5-2Q30 Peak Forecast

2014 9+3 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 14 15 16 17 18 19 20

I 1 1 p o t a : IPeak MW 12,777 2,637 2,466 2,124 2,280 2,644 2.771 2,742 2.480 2,231 2,350 2.6301 2,77712,883 2,751 2.584 2.242 2,397 2,757

Summer Peak h Winter Peak MW 2015 2853 3,000 2016 2967 3,071 2017 3047 3,156 2018 3150 3,300 2019 3.275 3,342 2020 3,283 3,344

Annual Peak M W 3000 3071 3156 33cD 3342 3344

Exhibit 1.6a 2015-2030 Peak Forecast

21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

Exhibit 1.6a 2015-2030 Peak Forecast

NOV Dec !Total 2,128 2,23612,402

107 1261 137

49 50 51 52 53 54 55 56 57 58 59 60 6 1 62 63 64 65 66 67 68 69 70 7 1 72 73 74 75 2019 2020 2021

Ian Feb Mar Apr May lun JuI Aug Sep Oct NOV Dec Total Jan Feb Mar Apr May lun lul Aug Sep Oct Nov Dec Total Jan 2,375 2,312 2.252 2.085 2.204 2,425 2,521 2.510 2,364 2.136 2.196 2,290 2,521 2,416 2.341 2,270 2,094 2,212 2.432 2,528 2.517 2,367 2,139 2,198 2,292 2.528 2.419

138 123 112 95 86 90 96 97 92 93 108 126 138 138 123 112 96 86 90 96 97 92 92 107 126 138 138

Exhibit 1.6a 2015-2030 Peak Forecast

76

Exhibit 1.6a 2015-2030 Peak Forecast

I I

I I 667 622 586 643 7551 8581 861 793 709 543 570 668 707 671 627 590 647 759

Exhib~t 1.6a 2Q~5-2Q30 Peak F o ~ c a ~ t

Exhibi~ 1.6a 2015-2030 Peak Forecast

Exhibit 1.6a 2015-2030 Peak Forecast

Exhibit 1.6a 2Ql5-2030 Peak Forecast

I I 3,158 3,009 2.662 2.832 3,179 3,308 3,261 3,040 2,755 2.860 3.0591 3,981 3,305 3,165 3,016 2,670 2.841 3,191

3,286 3,125 2,754 2,943 3,259 3,393 3,361 3,127 2,819 2,942 3.19J1 3,4161 3,424 3,294 3,132 2,762 2,952 3.271

Exhibit 1.6a 2015-2030 Peak F o ~ c a s ~

I 7030

Exhibit 1.6a 2015-2030 Peak Forecast

Exhibit 1.Bb COm1381190"

Comparison of 2015 FE WV and 2015 FE APS YI 2016 PJM A S Peak Forecast Growths

2015 WN 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

U G R 20162019

2,635 W N k 1 3,000 Foreun 2.967 12.6% 3,071 2.4% 3.047 2.7% 3,156 2.8% 3,150 3.4% 3,300 4.6% 3,275 4.0% 3.342 1.3% 3,283 0.2% 3,344 0.1% 3,291 0.2% $353 0.3% 3.3w 11.4% 3.3m 0.3% 3.320 0.5% 3,379 0.4% 3,338 0.5% 3,385 0.2% 3,348 0.3% 3,394 0.3% 3,362 0.4% 3,403 0.3% 3,375 0.4% 3,416 0.4% w 9 3 0.5% 3.424 0.2% 3,406 U.4X 3,433 0.3% 3,418 0.4%

3.3% 2.9%

2015 WN 8.499 W N M 2016 9.029 6.2% 2017 9,238 2.3% 2018 9.471 2.5% 2019 9.708 2.5% 2020 9,739 0.3% 2021 9,782 01% 2022 9,844 0.6% 2023 9.908 0.7% 2024 9.981 0.7% 2025 10,030 0.5% 2026 10,090 0.6% 2027 10.158 0.7% 2028 102m 0.8% 2029 10.310 0.7% 2030 10.379 0.7%

8,911 Forecast 9,067 1.7% 9,261 2.1% 9,513 2.7% 9.581 0.7% 9.600 0.2% 9,645 0.5% 9,696 0.5% 9,757 0.6% 9.795 04% 9,839 0.5% 9,888 0.5% 9,953 0.7%

10,004 0.5% 10.061 0.6%

1.W

2015WN 8.480 WNAd 2016 8,817 4.0% 2017 9,014 2.2% 2018 9.127 1.3% 201s 9,215 1.0% 2020 9.248 0.4% 2021 9,266 0.2% 2012 9.314 0.5% 2023 9,350 0.4% 2024 9,413 0.7% 2025 9.497 0.9% 2026 9.514 0.6% 2027 9,612 0.8% 2028 9.665 0.6% 2029 9.734 0.7% 2030 9,814 0.8%

8.640 8,526 8,778 9.m9 9.149 9.200

9,256 9.306 9,373 9,412 9,494 9,557 Q,M2 9,680

9,201

FOrnCaSt

-1.3% 3.0% 2.6% 1.6% 0.6% 0.0% 0.6% 0.5% 0.7% 0.7% 0.6% 0.7% 0.9% 0.4%

2O15WN 8,480 WNAcf 2016 9034 6.5% 2017 9,223 2.1% 2018 9,356 1.4% 2019 9.458 1.1% 2020 9,491 0.3% 2021 9,519 0.3% 2022 9,577 0.6% 2023 9.613 0.4% 2024 9,686 0.8% 2025 9,780 1.0% 2026 9,847 0.7% 2027 9,905 0.6% 2028 9,968 0.5% 2029 ,*,w, o.*x 2030 10.127 0.8%

c4GR 20162019 1.5%

8.640 Forecast 8.743 1.2% 8.987 2.8% 9.238 2.8% 9.392 1.7% 4693 0.5% 9,454 0.1% 9,519 0.7% 9,569 0.5% 9.646 0.8% 9,725 0.8% 9,787 0.6% 9,850 0.6% 9,915 1.0% 9,993 0.5%

2.4%

Exhibif 1.Sb Comllariron

I

SummeiPeak Growth

Summer Peak MW

Winter Peak Growth /o*

Winter Peak MW 12 mo

AYE Fracking MWs to PJM

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

2026

2027

2028

2029

2030

Submitted

337 429 479 523 523 523 523 523 523 523 523 523 523 523 523

PIM Used % Used

120 220 250 280 280 270 260 260 250 240 230 230 220 210 210

36% 5 1% 52% 54% 54% 52% 50% 50% 48% 46% 44% 44% 42% 40% 40%

PJM Unused

STAFF’S FIRST REQUEST FOR INFORMATION MONONGAHELA POWER COMPANY and THE POTOMAC EDISON COMPANY

CASE NO. 15-2002-E-P

Regarding Coal Fired Units (IRP, page 30):

a. Please provide the current amount of coal stockpiled at First Energy’s West Virginia coal fired units. This shall include: the facility name and location, the number of tons stockpiled, number of days this stockpile will fuel the plant at full load, the cost to maintain that coal annually, the origin(s) of the stockpiled coal.

b. Please provide the amount of coal stockpiled at First Energy’s West Virginia coal fired units on an annual basis from December 31,2005 through December 31,2015. This shall include: the facility name and location, the number of tons stockpiled, number of days this stockpile will fuel the plant at full load, the cost to maintain that coal annually, the origin(s) of the stockpiled coal.

c. Over the past 10 years, provide when, where (unit location) and why the coal stockpiles were used at all First Energy’s West Virginia coal fired units. Please include the cost savings associated with each incident.

d. Please provide a cost savings analysis study regarding the stockpiling of coal at First Energy’s West Virginia facilities with the data provided in items 1.7.b and c. Tables shall be in both Excel format files and printed.

a. See Confidential Exhibit 1.7a. Additionally, the annual cost to maintain fuel stock is a component of the rate base and the carrying cost is the Companies’ weighted average cost of capital. Also, the Haywood Storage Site includes an estimated cost to lease the off-site storage of $240,000 for 2016.

b. See Confidential Exhibit 1.7b. Additionally, the annual cost to maintain fuel stock is a component of the rate base and the carrying cost is the Companies’ weighted average cost of capital. Also, the Haywood Storage Site included the cost to lease the off-site storage in the amount of $190,000 in 2012, $344,000 in 2013, $522,000 in 2014, and $395,000 in 2015.

c. Coal has always been stored on site at the Harrison and Fort Martin power stations. Additionally, beginning in 2012, coal was and continues to be stored at an additional location (“Haywood Stockpile”) near the Harrison power station.

The coal stored at the plants is used to ensure a consistent and reliable supply of fuel for the generation of electricity. This is necessary to assure adequate coal supplies are available at all times. Both the coal usage and the supply of coal to the plants can

vary so the plants rely on the ability to store excess coal received when deliveries exceed usage or to draw down the storage during times where usage exceeds deliveries. Additionally, the supply chain of coal can, from time to time, be interrupted due to mine shutdowns, problems with delivery systems and routes, weather conditions, unloading issues, etc.

This approach results in not only a consistently available supply of coal, but also allows for lower cost contracts. Coal suppliers would require Mon Power to pay a premium if deliveries had to vary day-to-day, exactly matching the plant usage. Those suppliers would experience higher costs as their mines would experience non- productive down times coupled with other periods of high output. These costs would be passed on to Man Power. Suppliers prefer to ship on a ratable basis ensuring consist operation of their mine(s) which allows the negotiation of better coal prices.

Just-in-time delivery also significantly increases the risk that the plant would experience periods of no available fuel causing generation output to cease. Because of Man Power’s capacity and energy obligations to PJM, this would likely result in charges for failure to perform, some of which could be significant.

d. A cost saving analysis of the stockpiles at the FirstEnergy’s West Virginia facilities has not been performed.

Y

Please provide all worksheets, exact references and data used in determining the Levelized Cost of Electricity (LCOE) used in developing the chart in Figure 16 - Levelized Cost for Power Generation Technologies (IRP, pages 53):

a. The data shall be provided in Excel Format and in printed hardcopy.

~ S P O N S E :

a. The data is being provided in an Excel Format as Confidential Exhibit 1.8a.

Y

Please provide all worksheets, exact references and data used in determining the Levelized Cost Electricity (LCOE) used in developing the chart in Figure 17 - Levelized Cost Sensitivities - Combined Cycle (IRP, page 54):

a. The data shall be provided in Excel Format and in printed hardcopy

h. Explain how the capacity factor of 67% was determined.

RESPONSE:

a. Same as 1.8a (‘Combined Cycle COE’ tab)

b. The Companies used the capacity factor for existing coal plants for the capacity factor for combined cycle units in order to have an “apples-to- apples” comparison. However, according to recent operating statistics, the capacity factor for a combined cycle is lower. PJM recent data shows that combined cycle units had a capacity factor of 61.5 percent in the first nine months o f 201 5, compared to a capacity factor of 55.4 percent in the first nine months of 2014 (Monitoring Analytics “PJM State o f the Market Report, 43 20 1 5”, page 2 1 2)

Regarding Alternative Generation wind options, (IRP, page 5 5 ) :

a. What have the Companies determined to be the LCOE for wind projects?

b. What is the current LCOE for Wind Projects with and without a production tax credit?

c. The data shall be provided in Excel Format and in printed hardcopy.

~ S P O N S E :

a. $124.20/MWh @ 28% capacity factor (Note: Discovered error in the IRP and it is corrected here)

b. $124.20/MWh with PTC and $164.24/MWh without PTC, both @ 28% capacity factor. (IRP was in error and corrected here.)

c. Same as 1.8a ‘Wind (Inc PTC’) and ‘Wind (No PTC’ tabs)

Y

Regarding Alternative Generation solar options, (IRP, page 55):

a. What have the Companies determined to be the LCOE for solar projects?

b. What is the current LCOE for Solar Projects with and without a production tax credit (if any exist)?

c. The data shall be provided in Excel Format and in printed hardcopy.

~ S P O N S E :

a. $209.63/MWh @ 18% capacity factor (Discovered error in IRP and corrected it here)

b. $209.63MWh with ITC and $291.35/MWh without ITC, both @ 18% capacity factor (Discovered error in IRP and corrected it here.)

c. Same as 1.8a (‘Solar PV (Inc ITC)’ and ‘Solar PV (No ITC’ tabs)

Please provide all worksheets, exact references and data used in determining the Levelized Cost of Electricity (LCOE) used in developing the chart in Figure 18 - Levelized Cost Sensitivities - Existing Supercritical Pulverized Coal (IRP, page 56):

a. Explain how the cost of $57/MWH was determined for the acquisition of existing plants.

b. Does the cost of $57/MWH include the cost of retrofitting an existing supercritical pulverized coal with natural gas co-firing capabilities and all possible increased costs due to current, proposed and future environmental regulations and other risks?

1. If not, please recalculate the LCOE with all engineering, material and labor costs reflecting these additions and all possible increased costs due to current, proposed and future environmental regulations and other risks (identified in IRP, page 5, section 2).

2. Resubmit Figure 16 - Levelized Cost for Power Generation Technologies (IRP, pages 53).

3. Resubmit Figure 18 - Levelized Cost Sensitivities - Existing Supercritical Pulverized Coal (IRP, page 56).

c. Has the Company evaluated and/or included the availability of natural gas supplies in their LCOE calculations regarding the retrofitting of current and/or an existing supercritical pulverized coal-fired unit with natural gas co-firing capabilities?

d. The data shall be provided in Excel Format and in printed hardcopy.

RESPONSE:

a. Same as and see 1.8a ('Existing Coal COE tab) Utilized ABB Energy Velocity data. ABB Energy Velocity is a subscription data service that relies on government sourced (DOE, EIA, EPA) and its own industry experience to provide operational data as well as fuel, variable, and fixed cost information of US electric generating plants. These costs were utilized to develop the LCOE for the existing coal option.

b. The cost does not include cost of retrofitting natural gas co-firing capabilities and all possible increased costs due to existing and future unknown regulation. The cost does include expected C02 costs.

1. The Companies do not possess this information nor are they able to calculate it.

2. See 1.12bl

3. See 1.12bl

c. No

d. See 1 . 1 2 ~

Re: onongahela Power Corn any and The Potornac Edison Company Case No. 15-2002-E-P

I~ICATE OF SE

I hereby certify that on this 9" day of March, 2016, a copy of the foregoing was sent

by U.S. Mail, First Class, to:

Jacqueline Roberts, Esq. Consumer Advocate Division

700 Union Building 723 Kanawha Boulevard, East

Charleston, WV 25301