A. Leo Silvestrini Joseph F. Gredder. Book 4

Transcription

1 Niagara Mohawk Power Corporation d/b/a National Grid PROCEEDING ON MOTION OF THE COMMISSION AS TO THE RATES, CHARGES, RULES AND REGULATIONS OF NIAGARA MOHAWK POWER CORPORATION FOR ELECTRIC AND GAS SERVICE Testimony and Exhibits of: A. Leo Silvestrini Joseph F. Gredder Book 4 April 2012 Submitted to: New York State Public Service Commission Case 12-E- Case 12-G- Submitted by: Niagara Mohawk Power Corporation

2 Testimony of A. Leo Silvestrini

3 Before the Public Service Commission NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Direct Testimony Of A. Leo Silvestrini 1

4 Testimony of A. Leo Silvestrini Table of Contents I. Introduction and Qualifications...1 II. Purpose of Testimony... 2 III. Gas Sales Forecast... 4 a. Residential Heating b. Residential Non Heating c. Commercial/Industrial Heating d. Commercial/Industrial Non Heating IV. Conclusion

5 Testimony of A. Leo Silvestrini I. Introduction and Qualifications Q. Please state your name and business address A. My name is A. Leo Silvestrini. My business address is 40 Sylvan Road, Waltham, Massachusetts, Q. By whom are you employed and in what capacity? A. I am employed by National Grid Corporate Services LLC as the Manager of Gas Load Forecasting and Analysis. I am responsible for supervising the development of the gas load forecasts for National Grid s eight legacy gas utilities, including the Niagara Mohawk Power Corporation d/b/a National Grid ( Niagara Mohawk or Company ) Q. Please describe your educational background and experience. A. I received a Bachelor of Arts Degree in History in 1973 from the State University of New York at Albany and a Master of Arts Degree in Economics from Tufts University in I also received a certificate from the Northeastern University School of Business Management for the completion of the Management Development Program in In 1978, I joined Boston Gas Company as an economic analyst in the Rate Department. In 1980, I was promoted to Manager of Rates and Revenue Analysis and, in 1985, to the position of Director of Rates and Economic Page 1 of 21 3

6 Testimony of A. Leo Silvestrini Analysis. Over the next several years, I held a similar position in Market Planning and Development, Corporate Strategic Planning and Gas Resource Planning and Rates and Regulatory Affairs. I am currently the Manager of Gas Load Forecasting. 5 6 II. Purpose of Testimony Q. What is the purpose of your testimony? A. The purpose of my testimony is to provide historical and forecast customer and customer demand data that is used by the Company to prepare the forecast of gas revenues for the twelve months ending March 31, 2014 ( Rate Year ). This data is also used to prepare the Company s forecast of gas costs for the Rate Year. The data includes historical data for the twelve months ended December 31, 2011 ( Historic Test Year ), and forecast data for the Rate Year and the following two years ending March 31, 2015 and March 31, 2016 ( Data Year 1 and Data Year 2 ) Q. Are you sponsoring any exhibits in support of your testimony? A. Yes, I am sponsoring the following exhibits, which were prepared by me or under my direct supervision: Exhibit (ALS-1) Calendar Year Deliveries by Service and Revenue Class for the Period Page 2 of 21 4

7 Testimony of A. Leo Silvestrini Exhibit (ALS-2) Exhibit (ALS-3) Exhibit (ALS-4) Exhibit (ALS-5) Exhibit (ALS-6) Exhibit (ALS-7) Exhibit (ALS-8) Exhibit (ALS-9) Average Annual Calendar Year Use-Per-Customer Based on Total Residential Deliveries for the Historical Period and the Forecast Period End of Year Customer Count by Service and Revenue Class for the Period Forecast Fiscal Year Ending March 31 Deliveries by Service and Revenue Class for the Period 2012 through 2016 in MDth Forecast Fiscal Year Ending March 31 Customer Counts by Service and Revenue Class for the Period 2012 through 2016 Effects of the Energy Efficiency Programs Sponsored by the Company and New York State Energy Research and Development Administration ( NYSERDA ) for the Period 2012 through 2016 Upstate New York Historical and Projected Economic Indicators Used to Develop the Forecast Models Historical Actual Billed Sales Data by Month and by Class for the Period January 2007 through March 2012 Historical Weather Normalized Actual Billed Sales Data by Month and by Class for the Period January 2007 through March 2012 Exhibit (ALS-10) Historical Actual Customer Counts by Month and by Class for the Period January 2007 through March 2012 Exhibit (ALS-11) Delivery Forecast Model Specifications Exhibit (ALS-12) Design Day Forecast Methodology Page 3 of 21 5

8 Testimony of A. Leo Silvestrini 1 III. Gas Delivery Forecast Q. Please provide an overview of the Company s historical gas deliveries from 1993 through the Historic Test Year, as shown in Exhibit (ALS-1). A. In the past nearly two decades, the total annual deliveries to customers across all rate classes peaked in 1997 at 231,447 MDth. In the Historic Test Year, the total delivery volume was 145,128 MDth. The majority of the decline was concentrated in the special contract category and is the result of Niagara Mohawk s Master Restructuring Agreement with the Independent Power Producers in July 1997, the start up of the New York Independent System Operator, and the subsequent decline in natural gasfired electric generation on the Niagara Mohawk system. Excluding special contract deliveries, annual deliveries in 1997 totaled 115,367 MDth. For the Historic Test Year, the comparable quantity was 108,367 MDth. Between 2007 and 2011, deliveries grew an average of 1,760 MDth per year, a compound annual growth rate of 1.7%. Until recently, higher and more volatile gas prices and the replacement of older equipment with newer, more efficient equipment have led to increased conservation and the resulting declines in the average residential use-percustomer. However, this trend has stabilized over the past several years, Page 4 of 21 6

9 Testimony of A. Leo Silvestrini 1 2 as gas prices have declined and stabilized. This result is shown on Exhibit (ALS-2) Q. Please provide an overview of the Company s historical number of customers from 1993 through the Historic Test Year. A. As shown on Exhibit (ALS-3), on December 31, 1997, the total customer count for all rate classes was 532,828. The year-end customer count for December 31, 2011 was 588,452. The customer count data presented are monthly bill counts. There are no customers billed on a bimonthly basis. The modest growth in customer counts over this period and the relatively flat natural gas delivery quantities are consistent with the long term economic and demographic trends in Upstate New York. The decline in manufacturing and the weak demographic underpinnings of the regional economy have led to a slowing of the growth in population in the Central New York and Mohawk Valley regions. As a consequence, the rate of total customer additions has slowed from 6,000-10,000 per year in the 1990 s to 2,000-6,000 per year over the past eleven years. Between 2007 and 2011, customer growth averaged 3,561 per year, a compound annual growth rate of 0.6%. Over the forecast period , as the regional economy recovers from the recent recession, customers are Page 5 of 21 7

10 Testimony of A. Leo Silvestrini 1 2 projected to increase around 3,910 per year, a compound growth rate of 0.7% Q. Please describe the Company s individual service and revenue class distinctions. A. The Company s gas tariff (PSC No. 219) includes the following service classifications: SC1, SC2, SC3, SC4, SC5, SC6, SC7, SC8, SC9, SC10, SC12 and SC13. In addition, the Company has an SC11 service class that sets forth the terms and conditions that apply to other service classes for load aggregation and balancing services under the Company s retail choice and transportation programs. Within certain service classifications are distinct revenue classes. These are Residential Non-Heat, Residential Heat, Commercial Non-Heat, Commercial Heat, and Industrial. For these revenue classes, the Company developed forecast models at the rate code level. For example, for the residential heating class, there are separate models for SC1 Residential Heat, SC1 Residential Heat Monthly Balancing, SC2 Residential Heat, and SC2 Residential Heat Monthly Balancing. In addition to the distinct revenue classes named above, there are four other special categories that are forecast: deliveries to New York State Electric and Gas Company ( NYSEG ) pursuant to the Mechanicsville SC9 contract, SC10 sales of natural gas for vehicular use, Page 6 of 21 8

11 Testimony of A. Leo Silvestrini SC12 distributed generation ( DG ) sales using fewer than 250,000 therms annually, and SC13 sales to residential DG customers. Forecasts of deliveries to special contract customers are not modeled, but are determined on a customer-specific basis by assessing the terms of the contracts and the nature of each customer s operations Q. How does the Company derive the delivery forecasts? A. With the exception of the deliveries to special contract customers that are developed on a customer-specific basis, the forecasts are derived using statistical and econometric models. The total energy delivery forecasts are the result of customer count forecasts multiplied by use-per-customer forecasts that are modeled separately Q. Please describe how you derived the customer count forecast. A. The Company developed customer count forecast models as two components. One captures the annual changes in customer counts. The other captures the monthly or seasonal variation of customer counts over the course of a year. The annual changes are modeled using linear regression analysis with customer counts as a function of economic and demographic variables and statistical trend analysis. The monthly variation is modeled by fitting logistic functions that capture the seasonal Page 7 of 21 9

12 Testimony of A. Leo Silvestrini decline in customer counts during the summer months and the subsequent increase during the winter months. The monthly results of these logistic models are then reconciled to the results of the annual regression models to establish a monthly pattern over the course of the five-year forecast period. The Company obtained the historical and projected economic and demographic data used as the independent variables in the regression equations from Moody s economy.com (vintage February 2011). The customer count models for each rate class and the data used to derive them are described in more detail below Q. Please describe the derivation of the use-per-customer forecast. A. The historical monthly use-per-customer values are obtained by dividing the total billed therms for each month by the number of billed customers for the month. This data series is then modeled as a function of independent variables such as weather, seasonal factors, economic and demographic variables, natural gas prices, oil prices and time trends. The specific independent variables used in the models vary by rate class depending on the statistical results of the analysis and the goodness-of-fit of the equations to the data. The use-per-customer dependent variable is modeled as two components. The first component captures the annual trend in the baseload, or non-heating load, of the use-per-customer for Page 8 of 21 10

13 Testimony of A. Leo Silvestrini each rate class. The second component captures the trend in the heating load of use-per-customer as it relates to heating degree days. The monthly fluctuations in use-per-customer are captured by determining monthly coefficients on degree days and are further adjusted by monthly alpha factors, which capture the non-linear relationship between consumption and degree days. The monthly alpha factors are modeled as the ratio of the fitted values of the regression equations to the actual values to correct for the linear nature of regressions. The Company obtained the economic and demographic data used as the independent variables in these equations from Moody s economy.com, energy price data from the U.S. Department of Energy, Energy Information Administration ( DOE/EIA ), and the weather data from the National Oceanic and Atmospheric Administration ( NOAA ), National Weather Service ( NWS ). The use-per-customer models for each rate class and the data used to derive them are described in more detail below Q. How is the weather variable in the models determined? A. The weather variable in the models is determined by consideration of heating degree days. A heating degree day is defined as the positive difference between 65 degrees Fahrenheit and the daily average of the maximum and minimum temperatures for that day. The daily averages of Page 9 of 21 11

14 Testimony of A. Leo Silvestrini the high and low temperatures are obtained from the Syracuse and Albany National Weather Service stations. The system heating degree days are the arithmetic average of the Syracuse and Albany heating degree days. The heating degree day forecasts are based on the 30 year averages for the period January 1982 through December For example, the forecast heating degree days for January 5 are the average of the thirty January 5 degree day observations over that period. It should be noted that the forecast that the Company is presenting here was generated in the spring of 2011 using its demand models, and was based on the 30 year average for the period January 1, 1977 through December 31, 2006, which was the period used to calculate normal weather in Case No. 08-G-0609, Proceeding on Motion of the Commission as to the Rates, Charges, Rules and Regulations of Niagara Mohawk Power Corporation for Gas Service (the 2008 Gas Rate Case ). For purposes of this filing, the Company adjusted that forecast by applying the coefficients on the weather variables from the model equations to the difference between the updated 30 year average ending December 2011 and the one ending December Page 10 of 21 12

15 Testimony of A. Leo Silvestrini Q. Please explain how the initial forecast was adjusted for additional efficiency gains resulting from the energy efficiency programs sponsored by the Company and NYSERDA. A. The Company reduced the results of its econometric forecast models by energy efficiency adjustment factors to account for the incremental impact of the energy efficiency programs sponsored by the Company and NYSERDA. These adjustment factors account for the incremental savings that are not contained in the historical data used to derive the econometric results. They are, therefore, exogenous to the modeling effort. The Company derived the energy efficiency adjustment factors by deducting the historical savings attributable to these programs from the future goals of these programs for the residential and commercial sectors. The incremental percentage reductions are the projected delivery reductions for each year of the forecast period. The cumulative percentage reductions are the cumulative sums of these annual reductions from the start of the forecast period. The adjustment factor is equal to one minus the cumulative percentage factor divided by 100. Exhibit (ALS-6) shows the annual and cumulative percentage reductions and the adjustment factors used. For example, the annual forecast deliveries of all residential service classes from April 2011 to March 2012 were multiplied by the efficiency adjustment factor of The difference between the initial Page 11 of 21 13

16 Testimony of A. Leo Silvestrini forecast and the efficiency adjusted forecast by service class are also shown in Exhibit (ALS-6). It shows that cumulative energy efficiency reductions are projected to be 251 MDTH or 0.27% in Fiscal Year 2012, increasing to 959 MDTH or 0.8% in Data Year Q. Please explain how the initial forecast was adjusted for environmental and economic development initiatives in the Company s service territory that will impact the amount of natural gas consumed over the next five years. A. The Company is promoting the installation of compressed natural gas ( CNG ) fueling stations to serve the natural gas vehicle market in its service territory. The Company did not adjust its forecast for the impact of the CNG fueling stations because the anticipated volumes are uncertain. The forecast was adjusted, however, to reflect the impact of an additional new large customer in the town of Malta, as discussed later in my testimony. 17 Page 12 of 21 14

17 Testimony of A. Leo Silvestrini Q. Has the forecast methodology that you described been used previously by the Company? A. Yes. The forecast methodology described here has been used by the Company for business, gas resource and infrastructure planning for a number of years Q. Please describe the annual forecast deliveries and the year-end customer count forecast. A. Exhibit (ALS-4) sets forth the annual deliveries by rate class for the fiscal years ending March 31, 2011 through March 31, 2016, including the Rate Year. Exhibit (ALS-5) lists the fiscal year-end customer counts. The annual delivery forecasts also reflect the impact of the Company s energy efficiency programs. Natural gas deliveries are projected to increase by an average of 1,660 MDth, or 1.5%, per year. This compares with the historical average between 2007 and 2011 of approximately 1,760 MDth, or 1.7%, per year, as shown on Exhibit (ALS-1). Between 2011 and 2016, the customer count is projected to increase by 3,910 or 0.7% per year, compared to an average of 3,561, or 0.6%, between 2007 and 2011, as shown on Exhibit (ALS-3). The trend in declining use- perresidential customer, as shown on Exhibit (ALS-2), is projected to stabilize after reversing the historic downward trend. Deliveries to large Page 13 of 21 15

18 Testimony of A. Leo Silvestrini transportation customers are projected to increase as the result of the addition of a new customer in the town of Malta. The volumes for this customer were added to the results of the forecast models because the Company determined that, given the size and scope of this customer s gas demand and operations, its volumes are exogenous to the Company s modeling process. Deliveries to customers served under special contracts are projected to remain constant because the customers are expected to extend their contracts at the time of expiration and maintain their current level of consumption Q. Please summarize Moody s economy.com economic forecast for Upstate New York that drives the delivery forecast. A. As mentioned earlier, the Moody s economy.com economic forecast that the Company used for this forecast was issued in February The data used in the forecast is presented in Exhibit (ALS-7). The Moody s economy.com economic forecast for Upstate New York indicates that the recession ended in This is demonstrated by Moody s projection of the gross metropolitan product ( GMP ), which measures the value of all goods and services produced in the region. This GMP projection shows accelerating annual growth of approximately 5% in 2012 and 2013 before tapering off to 4% by Similarly, the Moody s economy.com Page 14 of 21 16

19 Testimony of A. Leo Silvestrini forecast for employment ( EMP ) indicates annual growth of 2% in 2012, increasing to 4% in 2013, and then tapering off to less than 1%, which is closer to the historical growth rate for region before the onset of the recession in a. Residential Heating Q. How were the Residential Heating customer counts and Dth modeled? A. The specific models for the Residential Heating classes are presented in Exhibit (ALS-11). There are separate models for SC1 Residential Heating Sales, SC1 Residential Heating Monthly Balancing, SC2 Residential Heating Sales, and SC2 Residential Heating Monthly Balancing. Annual customer counts for the Residential Heating classes were modeled as a function of manufacturing employment, population, and time trends. The monthly variation in customer counts was modeled using logistic functions that capture the seasonal decline in customer counts in the summer months and the subsequent increase in the winter months. The annual and monthly customer count models were then reconciled to produce the forecast of monthly customer counts through In 2009, approximately 8,300 customers were transferred from residential heating rate classes to residential non heating rate classes as a result of an audit performed during the 2008 Gas Rate Case. These Page 15 of 21 17

20 Testimony of A. Leo Silvestrini transferred customer counts and their associated gas volumes were reflected in the historical data the Company used to prepare its forecast models Use-per-customer for the Residential Heating classes was modeled as two components. The first component captures base load, or non heating load, per customer and the second component captures the heating load per customer. Base load use-per-customer models for the Residential Heating classes were developed on annual data as a function of gross municipal product, average household income, manufacturing employment, housing starts, gas prices, and oil prices. The heating load component of the model captures the monthly fluctuation of gas demand for this class. The Company modeled monthly heating load use-per-customer as a function of heating degree days. Then, to capture the non-linear nature of the relationship between monthly use-per-customer and heating degree days, the Company calculated alpha factors that are modeled as the ratio of the fitted values of the regression equations to the actual values to correct for the linear nature of regressions. 19 Page 16 of 21 18

21 Testimony of A. Leo Silvestrini The results of the customer count forecasts and the use-per-customer forecasts were then multiplied together to derive the volume delivery forecast presented in Exhibit (ALS-4) b. Residential Non Heating Q. How were the Residential Non Heating customer counts and Dth modeled? A. The specific models for the Residential Non Heating classes are presented in Exhibit (ALS-11). There are separate models for SC1 Residential Non Heating Sales, SC1 Residential Non Heating Monthly Balancing, SC2 Residential Non Heating Sales, and SC2 Residential Non Heating Monthly Balancing. Annual customer counts were modeled as a function of time for each of the rate classes. In 2009, approximately 8,300 customers were transferred from residential heating rate classes to residential non heating rate classes as a result of an audit performed during the 2008 Gas Rate Case. These transferred customer counts and their associated gas volumes were reflected in the historical data the Company used to prepare its forecast models Unlike the Residential Heating classes, use-per-customer for the Residential Non Heating classes was modeled as only one component, the Page 17 of 21 19

22 Testimony of A. Leo Silvestrini base load component. Base load use-per-customer models for the Residential Non Heating classes were developed on annual data as a function of number of households, housing starts, and time trends. Then, the Company developed an algorithm to determine the relationship between monthly consumption and annual consumption for these classes to allocate the forecast annual use-per-customer to monthly use-percustomer The results of the customer count forecasts and the use-per-customer forecasts were then multiplied together to derive the volume delivery forecast presented in Exhibit (ALS-4) c. Commercial/Industrial Heating Q. How were the Commercial/Industrial Heating customer counts and Dth modeled? A. The specific models for the Commercial/Industrial Heating classes are presented in Exhibit (ALS-11). There are separate models for SC2 Commercial Heating Sales, SC2 Commercial Heating Monthly Balancing, SC3 Commercial Heating, and SC4 Commercial Heat. 20 Page 18 of 21 20

23 Testimony of A. Leo Silvestrini The customer counts are modeled as a function of time. Similar to the Residential Heating classes, use-per-customer for the Commercial/Industrial Heating classes was modeled as two components. The first component captures base load, or non heating load per customer and the second component captures the heating load per customer. The base load use-per-customer models for the Commercial/Industrial Heating classes were developed on annual data as a function of disposable personal income, housing starts, gross municipal product, manufacturing employment, retail sales, average household income, gas prices, and oil prices. The heating load component of the model captures the seasonal fluctuation of gas demand for this class. The Company modeled monthly heating load use-per-customer as a function of heating degree days. Then, to capture the non-linear nature of the relationship between monthly useper-customer and heating degree days, the Company calculated alpha factors that are modeled as the ratio of the fitted values of the regression equations to the actual values to correct for the linear nature of regressions. 18 Page 19 of 21 21

24 Testimony of A. Leo Silvestrini d. Commercial/Industrial Non Heating Q. How were the Commercial/Industrial Non Heating customer counts and Dth modeled? A. The specific models for the Commercial/Industrial Non Heating classes are presented in Exhibit (ALS-11). There are separate models for SC2 Commercial Non Heating Sales, SC2 Commercial Non Heating Monthly Balancing, SC2 Industrial, SC2 Industrial Monthly Balancing, SC3 Commercial Non Heating, SC3 Industrial, SC5 Firm, and SC7 Firm Customer counts were modeled as a function of time and manufacturing employment. Use-per-customer for the Commercial/Industrial Non Heating classes was modeled as a single component. Use-per-customer was modeled on annual data as a function of time, disposable income, housing starts, number of households, total unemployed, gross municipal product, gas prices, and oil prices. Then, the Company developed an algorithm to determine the relationship between monthly consumption and annual consumption for this class to allocate the forecast annual use-percustomer to monthly use-per-customer. 19 Page 20 of 21 22

25 Testimony of A. Leo Silvestrini The results of the customer count forecasts and the use-per-customer forecasts were then multiplied together to derive the volume delivery forecast presented in Exhibit (ALS-4). 4 5 IV. Conclusion 6 7 Q. Does this conclude your testimony? A. Yes it does. Page 21 of 21 23

26 Exhibits of A. Leo Silvestrini

27 Testimony of A. Leo Silvestrini Index of Exhibits Exhibit (ALS-1) Exhibit (ALS-2) Exhibit (ALS-3) Exhibit (ALS-4) Exhibit (ALS-5) Exhibit (ALS-6) Exhibit (ALS-7) Exhibit (ALS-8) Exhibit (ALS-9) Calendar Year Deliveries by Service and Revenue Class for the Period Average Annual Calendar Year Use-Per-Customer Based on Total Residential Deliveries for the Historical Period and the Forecast Period End of Year Customer Count by Service and Revenue Class for the Period Forecast Fiscal Year Ending March 31 Deliveries by Service and Revenue Class for the Period 2012 through 2016 in MDth Forecast Fiscal Year Ending March 31 Customer Counts by Service and Revenue Class for the Period 2012 through 2016 Effects of the Energy Efficiency Programs Sponsored by the Company and New York State Energy Research and Development Administration ( NYSERDA ) for the Period 2012 through 2016 Upstate New York Historical and Projected Economic Indicators Used to Develop the Forecast Models Historical Actual Billed Sales Data by Month and by Class for the Period January 2007 through March 2012 Historical Weather Normalized Actual Billed Sales Data by Month and by Class for the Period January 2007 through March 2012 Exhibit (ALS-10) Historical Actual Customer Counts by Month and by Class for the Period January 2007 through March 2012 Exhibit (ALS-11) Delivery Forecast Model Specifications Exhibit (ALS-12) Design Day Forecast Methodology 24

28 Exhibit (ALS- 1)

29 Testimony of A. Leo Silvestrini Exhibit (ALS-1) Calendar Year Deliveries by Service and Revenue Class for the Period

30 Exhibit (ALS-1) Page 1 of 1 Exhibit (ALS-1) Page 1 of 1 NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Calendar Year deliveries by Service and Revenue class in thousands of Dekatherms SC1 Res Non Heat 3,475 2,408 1,645 1, ,147 1,227 1,201 1,217 1,337 1,312 1,340 1,261 1,355 1,308 1,389 1,129 1,189 SC1 Res Heat 51,211 53,862 50,004 55,503 54,078 46,160 50,442 52,932 47,543 44,619 48,700 44,960 44,692 39,568 41,913 39,330 38,487 36,276 37,070 SC2 Res Non Heat SC2 Res Heat SC2 Comm Non Heat 3,512 1, SC2 Comm Heat 17,764 20,732 19,989 21,504 19,521 14,678 14,798 14,627 13,459 13,356 14,374 13,215 13,085 11,477 11,435 10,415 9,733 8,995 9,135 SC2 Industrial SC3 Comm Non Heat SC3 Comm Heat SC3 Industrial SC4 Comm Heat 856 2,385 1,590 1, SC5 Firm 6,622 6,706 6,934 6,945 7,608 7,757 8,641 8,997 7,805 7,157 7,064 7,280 6,861 6,673 7,281 6,978 6,961 6,950 7,088 SC6 Interruptible 17,809 13,988 13,796 10,719 11,738 8,839 10,100 8,585 7,632 10,390 5,543 5,406 6,004 8,377 8,494 9,429 8,299 8,460 8,151 SC7 Firm 4,074 3,807 3,568 3,760 5,392 5,215 6,279 6,287 6,002 5,566 6,265 6,261 5,977 5,115 5,877 5,878 5,936 5,799 5,783 SC8 Trans includes STBY 10,771 11,207 12,637 10,745 11,776 11,298 12,834 13,905 11,783 11,498 10,609 10,804 11,277 11,766 12,132 13,818 12,985 15,381 16,696 SC1 Res Non Heat MB SC1 Res Heat MB ,560 5,460 7,793 8,139 7,396 5,996 7,652 9,072 10,159 10,484 11,616 SC2 Res Non Heat MB SC2 Res Heat MB SC2 Comm Non Heat MB SC2 Comm Heat MB ,149 1,697 3,139 5,129 5,125 5,915 7,357 6,928 6,976 6,425 7,650 8,139 8,424 8,299 8,941 SC2 Industrial MB SC10 Natural Gas Vehicles SC12 DG < 250 K SC12 DG < 250 K MB SC12 DG 250 K K MB SC13 DG Res SC9 NYSEG Mechanicsville SC9 Special Contracts 31,661 51, , , ,080 92,893 95,233 95,761 84,221 66,203 41,568 34,007 43,702 27,606 33,062 21,725 30,620 36,890 36,760 Total 149, , , , , , , , , , , , , , , , , , ,128 Total less Special Contracts 118, , , , ,367 99, , , , , , , ,719 99, , , , , ,367 Annual Growth 206 (5,505) 820 1,664 (15,368) 10,719 4,645 (9,720) 2,283 4,316 (4,958) (565) (7,154) 7, (1,989) (804) 3,873 Average Growth ,760 CAGR % 26

31 Exhibit (ALS-2)

32 Testimony of A. Leo Silvestrini Exhibit (ALS-2) Average Annual Calendar Year Use Per Customer Based on Total Residential Deliveries for the Historical Period , and the Forecast Period

33 Exhibit (ALS-2) Page 1 of 1 Exhibit (ALS-2) Page 1 of 1 NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Annual (calendar year) Use per Customer total Residential deliveries in therms Actual 1,204 1,217 1,097 1,184 1, ,056 1,102 1,020 1,013 1,133 1,059 1, Actual Weather Normalized 1,184 1,146 1,121 1,121 1,131 1,099 1,111 1,108 1,064 1,089 1,083 1,065 1,023 1, ,025 Forecast ,400 1,200 1, Actual Actual Weather Normalized Forecast 28

34 Exhibit (ALS-3)

35 Testimony of A. Leo Silvestrini Exhibit (ALS-3) End of Year Customer Count by Service and Revenue Class for the Period

36 Exhibit (ALS-3) Page 1 of 1 Exhibit (ALS-3) Page 1 of 1 NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID End of Year (December) customer count by Service and Revenue class SC1 Res Non Heat 76,691 53,362 42,885 39,652 41,071 40,857 40,875 40,492 39,294 38,381 37,057 36,716 36,538 35,397 33,828 32,148 38,622 37,372 36,122 SC1 Res Heat 383, , , , , , , , , , , , , , , , , , ,450 SC2 Res Non Heat SC2 Res Heat SC2 Comm Non Heat 7,644 2,801 2,571 2,482 2,427 2,333 2,162 2,080 2,007 1,983 2,015 1,993 1,968 1,826 1,687 1,585 1,518 1,458 1,399 SC2 Comm Heat 32,122 37,912 38,628 39,060 38,433 36,947 34,683 34,878 33,659 32,896 32,651 32,966 32,853 30,583 29,089 28,025 27,354 27,075 25,971 SC2 Industrial SC3 Comm Non Heat SC3 Comm Heat SC3 Industrial SC4 Comm Heat SC5 Firm SC6 Interruptible SC7 Firm SC8 Trans includes STBY SC1 Res Non Heat MB ,414 1,875 2,761 2,685 2,367 3,097 4,384 5,763 6,702 7,371 8,081 SC1 Res Heat MB ,407 14,014 41,630 54,544 68,151 65,945 59,651 65,135 78,798 93, , , ,596 SC2 Res Non Heat MB SC2 Res Heat MB SC2 Comm Non Heat MB SC2 Comm Heat MB ,995 4,972 5,322 6,652 7,747 8,273 8,431 8,854 10,990 12,546 13,606 14,370 14,778 15,931 SC2 Industrial MB SC10 Natural Gas Vehicles SC12 DG < 250 K SC12 DG < 250 K MB SC12 DG 250 K K MB SC13 DG Res SC9 NYSEG Mechanicsville SC9 Special Contracts Total 501, , , , , , , , , , , , , , , , , , ,452 Annual Growth - 9,844 7,335 8,422 6,150 4,046 5,082 6,654 2,670 5,803 3,543 3,815 4,200 2,007 3,780 4,785 3,944 3,213 2,082 Average Growth ,561 CAGR % 30

37 Exhibit (ALS-4)

38 Testimony of A. Leo Silvestrini Exhibit (ALS-4) Forecasted Fiscal Year Ending March 31 Deliveries by Service and Revenue Class for the Period

39 Exhibit (ALS-4) Page 1 of 1 NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Forecasted Year ending March 31st deliveries by Service and Revenue class in thousands of Dekatherms SC1 Res Non Heat 1,172 1,149 1,064 1,045 1,029 1,019 SC1 Res Heat 38,052 36,451 37,743 37,557 37,394 37,440 SC2 Res Non Heat SC2 Res Heat SC2 Comm Non Heat SC2 Comm Heat 9,424 8,281 7,822 7,147 6,567 6,141 SC2 Industrial SC3 Comm Non Heat SC3 Comm Heat SC3 Industrial SC4 Comm Heat SC5 Firm 7,228 6,948 6,990 7,031 7,072 7,139 SC6 Interruptible 8,604 8,139 10,387 11,578 12,787 14,146 SC7 Firm 5,962 5,645 5,929 5,986 6,039 6,121 SC8 Trans includes STBY 16,380 17,043 18,400 19,292 20,239 21,180 SC1 Res Non Heat MB SC1 Res Heat MB 11,450 11,664 12,558 13,150 13,726 14,437 SC2 Res Non Heat MB SC2 Res Heat MB SC2 Comm Non Heat MB SC2 Comm Heat MB 8,859 8,575 9,404 9,413 9,128 8,588 SC2 Industrial MB SC10 Natural Gas Vehicles SC12 DG < 250 K SC12 DG < 250 K MB SC12 DG 250 K K MB SC13 DG Res SC9 NYSEG Mechanicsville SC9 Special Contracts 41,282 35,804 35,647 35,647 35,647 35,647 Total 151, , , , , ,011 Total less Special Contracts 110, , , , , ,364 Annual Growth (3,736) 6,196 1,857 1,753 2,229 Average Growth ,660 Annual Percentage Change -3.4% 5.8% 1.7% 1.5% 1.9% CAGR % 32

40 Exhibit (ALS-5)

41 Testimony of A. Leo Silvestrini Exhibit (ALS-5) Forecasted Fiscal Year Ending March 31 Customer Counts by Service and Revenue class for the Period

42 Exhibit (ALS-5) Page 1 of 1 NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Forecasted End of Fiscal Year (March) customer count by Service and Revenue class SC1 Res Non Heat 37,362 36,452 35,833 35,284 34,774 34,283 SC1 Res Heat 386, , , , , ,354 SC2 Res Non Heat SC2 Res Heat SC2 Comm Non Heat 1,461 1,400 1,361 1,327 1,297 1,270 SC2 Comm Heat 26,868 26,123 25,485 24,819 24,167 23,554 SC2 Industrial SC3 Comm Non Heat SC3 Comm Heat SC3 Industrial SC4 Comm Heat SC5 Firm SC6 Interruptible SC7 Firm SC8 Trans includes STBY SC1 Res Non Heat MB 7,438 7,818 7,959 8,034 8,080 8,111 SC1 Res Heat MB 110, , , , , ,135 SC2 Res Non Heat MB SC2 Res Heat MB SC2 Comm Non Heat MB SC2 Comm Heat MB 15,081 15,642 16,237 16,848 17,442 18,001 SC2 Industrial MB SC10 Natural Gas Vehicles SC12 DG < 250 K SC12 DG < 250 K MB SC12 DG 250 K K MB SC13 DG Res SC9 NYSEG Mechanicsville SC9 Special Contracts Total 588, , , , , ,667 Annual Growth 3,878 3,925 3,929 3,920 3,898 Average Growth ,910 Annual Percentage Change 0.7% 0.7% 0.7% 0.7% 0.6% CAGR % 34

43 Exhibit (ALS-6)

44 Testimony of A. Leo Silvestrini Exhibit (ALS-6) Effects of the Energy Efficiency Programs Sponsored by the Company and New York State Energy Research and Development Administration for the Period

45 Exhibit (ALS-6) Page 1 of 1 NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Energy Efficiency Program Effects Year ending Year ending Year ending Year ending Year ending March 31st March 31st March 31st March 31st March 31st Residential (SC1& SC2): Incremental Percent Reductions 0.27% 0.20% 0.13% 0.11% 0.10% Cumulative Percent Reductions 0.27% 0.47% 0.60% 0.71% 0.81% Monthly Adjustment Factor Commercial and Industrial SC2, SC3, SC5, SC7, SC8: Incremental Percent Reductions 0.24% 0.24% 0.19% 0.18% 0.18% Cumulative Percent Reductions 0.24% 0.48% 0.67% 0.85% 1.03% Monthly Adjustment Factor Year ending Year ending Year ending Year ending Year ending Efficiency Reductions in therms March 31st March 31st March 31st March 31st March 31st by Service and Revenue class: SC1 Res Non Heat (30,796) (49,783) (63,017) (73,894) (83,252) SC1 Res Heat (977,219) (1,766,453) (2,263,793) (2,685,690) (3,058,383) SC2 Res Non Heat (201) (534) (796) (1,009) (1,204) SC2 Res Heat (3,820) (6,806) (8,662) (10,178) (11,579) SC2 Comm Non Heat (7,350) (13,205) (17,335) (20,610) (23,100) SC2 Comm Heat (203,231) (379,804) (483,145) (564,376) (637,434) SC2 Industrial (3,601) (8,117) (11,332) (14,476) (17,686) SC3 Comm Non Heat (1,496) (3,216) (4,724) (6,337) (8,050) SC3 Comm Heat (7,992) (11,555) (16,392) (21,084) (25,770) SC3 Industrial (2,750) (6,620) (8,280) (9,486) (11,289) SC4 Comm Heat SC5 Firm (170,521) (339,428) (475,265) (607,788) (741,027) SC6 Interruptible SC7 Firm (138,543) (287,881) (404,620) (519,003) (635,353) SC8 Trans includes STBY (418,272) (893,430) (1,304,103) (1,739,273) (2,198,535) SC1 Res Non Heat MB (7,978) (11,017) (12,555) (12,813) (12,470) SC1 Res Heat MB (312,695) (587,755) (792,656) (985,833) (1,179,361) SC2 Res Non Heat MB (97) (125) (163) (195) (225) SC2 Res Heat MB (2,796) (5,721) (7,554) (8,565) (9,345) SC2 Comm Non Heat MB (8,182) (16,262) (22,751) (29,020) (35,285) SC2 Comm Heat MB (210,450) (456,620) (636,308) (784,428) (891,419) SC2 Industrial MB (2,085) (4,249) (6,108) (8,015) (10,043) SC10 Natural Gas Vehicles SC12 DG < 250 K NYSEG Transp Special Contracts TOTAL THERMS (2,510,075) (4,848,582) (6,539,560) (8,102,073) (9,590,809) TOTAL MDTH (251.01) (484.86) (653.96) (810.21) (959.08) 36

46 Exhibit (ALS-7)

47 Testimony of A. Leo Silvestrini Exhibit (ALS-7) Upstate New York Historical and Projected Economic Indicators Used to Develop the Forecast Models 37

48 Exhibit (ALS-7) Page 1 of 2 Niagara Mohawk Power Corporation d/b/a National Grid Upstate New York Economic Indicators Exhibit (ALS-7) Page 1 of 2 Year FEMF FET FGDPQ FHHOLDCA FHST1Q FHSTMFQ FHSTQ FLBR FLBU FO EMPM EMP GMP HH HSF HMF HTT UEMR UEM , , % , , % , , % , , % , , % , , % , , % , , % , , % , , % , , % , , % , , % , , % , , % , , % , , % Annual Growth Rates % 0.9% 4.0% 0.3% 5.5% 24.9% 8.4% 1.7% 2.6% -19.1% % -0.4% 3.3% 0.5% 11.3% 8.6% 10.9% 18.9% 20.4% 20.5% % -0.2% 4.3% 0.7% -1.5% 7.2% 0.0% 5.3% 5.6% 1.1% % 1.0% 6.8% 0.5% 4.0% -14.2% 0.8% -2.3% -1.2% 37.3% % 0.5% 6.5% 0.3% -0.7% 83.6% 12.0% -5.9% -4.9% 22.3% % 0.3% 5.5% 0.5% -14.1% -34.0% -19.1% -0.9% -0.4% 3.5% % 0.5% 5.3% 0.1% -17.9% 48.1% -4.5% 0.9% 0.7% 32.7% % 0.7% 5.1% 0.3% -26.0% -25.2% -25.7% 21.5% 23.0% -19.2% % -2.1% -1.4% 0.5% -18.9% -64.3% -33.3% 40.7% 40.0% 2.3% % -1.0% 1.1% 0.6% 9.2% -40.3% 0.8% 1.3% 0.5% 9.4% % 0.1% 3.5% 0.5% 27.0% 237.6% 48.1% -0.1% 0.5% 13.6% % 2.0% 5.1% 0.4% 58.1% 13.8% 48.0% 0.3% 1.5% -6.3% % 4.1% 5.2% 0.4% 16.0% 15.3% 15.9% -9.8% -8.6% 5.0% % 3.2% 4.6% 0.5% 2.7% 14.2% 4.7% -17.5% -16.9% 4.4% % 2.1% 4.2% 0.5% -5.1% -9.6% -6.0% -6.4% -5.8% 4.3% % 0.8% 4.0% 0.3% -0.5% -4.7% -1.3% 1.0% 1.4% 7.1% Compound Annual Growth Rates AVERAGE % 0.2% 5.3% 0.5% -0.6% 3.9% 0.3% 4.05% 3.5% 16.2% % -0.3% 2.7% 0.4% -7.3% -4.5% -6.7% 5.61% 11.8% 6.4% % 2.4% 4.6% 0.4% 12.2% 5.2% 10.8% 5.86% -5.9% 2.8% 38

49 Exhibit (ALS-7) Page 2 of 2 Year Annual Growth Rates Compound Annual Growth Ra Niagara Mohawk Power Corporation d/b/a National Grid Upstate New York Economic Indicators Exhibit (ALS-7) Page 2 of 2 FPOP2544Q FPOPCA FRTFSQ FYHHAVGQ FYPCPIQ FYPDPI$Q Lagged_FO Lagged_NG NG NGdivFO Pop* POP25-44 POP RSL INC PIP PIDR DisPersInc , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , % 0.3% 3.0% 4.9% 4.9% 1.4% 20.5% 39.1% -31.1% 15.4% 1.7% -1.4% 0.5% 4.3% 0.1% 0.1% 4.4% 1.1% 4.7% 39.1% 3.6% 5.0% -1.4% 0.7% 5.9% 3.5% 3.5% 2.9% 37.3% 22.1% 4.7% -11.1% 3.6% -1.5% 0.5% 8.0% 5.6% 5.6% 3.6% 22.3% 36.0% 22.1% 11.2% 4.1% -1.6% 0.3% 5.2% 3.9% 3.9% 0.5% 3.5% -16.2% 36.0% -19.0% 0.8% -1.5% 0.5% 3.6% 5.7% 5.6% 1.6% 32.7% -0.4% -16.2% -24.9% 2.1% -1.5% 0.2% 1.7% 6.0% 6.0% 3.2% -19.2% 2.8% -0.4% 27.2% 3.4% -1.2% 0.3% -0.9% 3.3% 3.3% 1.0% 2.3% -31.6% 2.8% -33.1% 1.3% -0.9% 0.4% -5.5% -1.8% -1.7% 2.8% 9.4% 1.4% -31.6% -7.3% 3.2% -0.8% 0.4% 0.8% 1.8% 2.0% 1.1% 13.6% 25.3% 1.4% 10.3% 1.5% -0.4% 0.3% 4.6% 4.6% 4.8% 3.4% -6.3% 0.2% 25.3% 6.9% 3.7% -0.1% 0.3% 5.2% 6.2% 6.2% 3.0% 5.0% 3.9% 0.2% -1.0% 3.4% 0.1% 0.3% 6.6% 7.9% 8.0% 4.2% 4.4% 3.4% 3.9% -0.9% 4.6% 0.1% 0.3% 4.6% 6.3% 6.5% 3.2% 4.3% 0.8% 3.4% -3.3% 3.6% 0.1% 0.3% 3.7% 5.1% 5.3% 2.8% 7.1% 0.5% 0.8% -6.1% 3.1% 0.3% 0.2% 3.5% 4.3% 4.4% 1.8% 6.0% 2.6% 0.5% -3.3% 2.0% -1.5% 0.5% 5.4% 3.7% 3.7% 2.6% 18.4% 7.7% 15.2% -9.0% 3.1% -0.9% 0.3% 0.1% 2.7% 2.8% 2.3% -0.8% -2.2% -2.3% -1.4% 2.6% 0.1% 0.3% 4.7% 6.0% 6.1% 3.0% 5.3% 2.2% 1.8% -2.9% 3.3% 39

50 Exhibit (ALS-8)

51 Testimony of A. Leo Silvestrini Exhibit (ALS-8) Historical Actual Billed Sales Data by Month and by Class for the Period January 2007 March

52 Exhibit (ALS-8) Page 1 of 6 Exhibit (ALS-8) Page 1 of 6 NIAGARA MOHAWK POWER CORPORATION d/b/a NATIONAL GRID Historical Actual Volumes by Month Jan-07 Feb-07 Mar-07 Apr-07 May-07 Jun-07 Jul-07 Aug-07 Sep-07 Oct-07 Nov-07 Dec-07 Total 2007 Actual DTh 1 SC1 Res Non Heat 170, , , ,516 95,490 53,334 40,297 34,994 35,461 39,949 82, ,042 1,355,492 2 SC1 Res Heat 5,645,973 7,912,166 7,874,888 5,253,345 2,732,912 1,182, , , , ,874 2,414,516 5,791,589 41,912,655 3 SC2 Res Non Heat 1,118 1,672 1,710 1, ,038 4 SC2 Res Heat 19,943 29,738 30,361 20,225 9,465 4,639 3,240 2,938 2,804 3,618 9,184 21, ,769 5 SC2 Comm Non Heat 41,814 51,464 53,928 40,930 25,896 22,305 18,423 18,026 20,188 15,706 27,736 48, ,393 6 SC2 Comm Heat 1,487,302 2,242,748 2,286,805 1,473, , , , , , , ,350 1,506,378 11,430,921 7 SC2 Industrial 26,619 44,660 42,648 29,812 12,013 3,569 4,470 3,787 5,593 (1,146) 11,914 32, ,580 8 SC3 Comm Non Heat 6,933 6,643 10,939 5,916 4,844 3,344 3,288 3,843 3,972 3,045 4,674 5,945 63,384 9 SC3 Comm Heat 32,784 46,061 45,437 44,088 25,500 17,398 11,111 7,698 11,424 8,740 15,177 22, , SC3 Industrial 18,485 21,003 19,711 16,700 10,258 (3,137) 7,077 4,857 5,327 4,728 5,467 9, , SC4 Comm Heat 87, ,595 97,000 35,907 35,156 25,787 29,446 32,501 36,941 49,436 77,714 99, , SC5 Firm 806, , , , , , , , , , , ,147 7,280, SC6 Interruptible 554, , , , , , , , , , ,295 1,191,440 8,494, SC7 Firm 938, , , , , , , , , , , ,542 5,876, SC8 Trans includes STBY 1,425,475 1,275,937 1,313,589 1,069, , , , , , ,020 1,145,522 1,318,542 12,132, SC1 Res Non Heat MB 20,340 28,221 29,500 21,220 13,054 6,994 5,422 4,777 5,096 6,234 13,123 28, , SC1 Res Heat MB 958,491 1,358,327 1,398, , , , , , , , ,043 1,167,422 7,651, SC2 Res Non Heat MB , SC2 Res Heat MB 8,555 10,108 15,201 9,461 5,862 2,852 2,314 1,402 1,272 1,500 3,175 6,544 68, SC2 Comm Non Heat MB 30,883 36,704 38,456 30,066 24,392 19,000 17,062 16,139 16,254 16,676 22,395 34, , SC2 Comm Heat MB 926,171 1,341,527 1,388, , , , , , , , ,663 1,087,021 7,646, SC2 Industrial MB 14,030 17,593 (668) 9,532 6,549 1, ,173 1,302 3,536 10,284 66, SC10 Natural Gas Vehicles (397) SC12 DG < 250 K 1,810 2,271 2,060 2,179 1,987 2,013 2,034 2,086 2,213 1,920 1,891 2,060 24, SC12 DG < 250 K MB ,875 2,972 2,717 2,549 1,952 2,281 1,966 16, SC12 DG 250 K K MB SC13 DG Res NYSEG Transp 46,231 50,682 39,809 23,610 8,489 5,182 4,826 4,551 5,338 9,731 29,504 45, , Special Contracts 1,942,852 3,614,849 3,443,053 1,374, ,497 1,605,069 2,930,310 4,554,173 3,578,047 1,126,779 3,110,612 4,811,481 33,061,560 Total 15,212,937 20,540,984 20,604,097 13,454,426 7,575,557 5,605,425 6,431,943 8,086,317 7,065,811 5,255,704 10,744,295 19,152, ,730,439 41