Ground-truth Analysis of New York s Residential Sector aeci Trend

Transcription

1 Ground-truth Analysis of New York s Residential Sector aeci Trend Authors: Margaret Harper, Colin Sheppard, Charles Chamberlin, and Arne Jacobson Schatz Energy Research Center, Humboldt State University Project Managers: Yerina Mugica and Dale Bryk Center for Market Innovation, Natural Resources Defense Council August 2010

2 This report is one in a series of short ground-truth efforts that seek to understand historical residential sector energy consumption trends observed in state specific simulations using the proposed Performance based State Efficiency Program (PSEP) metric. 1,2 Initial simulations of the PSEP metric used historical data to estimate the number of years that the state would have made progress with respect to weather adjusted energy consumption intensity (aeci), where progress is defined as a downward slope over the five year period that ends in the evaluation year. Over the period from , New York would have performed moderately well, with six progress years detected according to the PSEP methodology (Figure 1). New York s energy efficiency efforts started in the late 1970s. The state has a stringent building energy code and both state- and federally-funded weatherization programs to encourage building efficiency in existing structures. In addition to utility demand-side management programs starting in the 1980s, the New York Energy $mart SM program was instituted in 1998 to manage energy efficiency, low-income services, R&D and environmental protection programs during the state s transition to a competitive electricity market. Additionally, the Long Island Power Authority (LIPA) has administered further market-focused efforts since the 1990s. In 2008, New York furthered its commitment to energy efficiency by creating an Energy Efficiency Portfolio Standard (EEPS) and providing additional funding to expand programs in an effort to meet this goal. New York s performance in the PSEP metric does not seem to clearly reflect the intensity of these energy efficiency efforts. Over the period from , the residential aeci has fluctuated around 50 MBtu/cap/year, as electricity consumption has increased by an average of 0.11 MBtu/cap/year per year, fuel oil consumption has decreased by an average of 0.26 MBtu/cap/year per year and natural gas consumption has fluctuated with a slightly increasing trend of 0.05 MBtu/cap/year per year. 3 The increasing electricity consumption may be explained in part by a demographic shift in New York s population as well as by increasing appliance use and decreasing electricity prices potentially offsetting the state s aggressive electricity efficiency efforts. The decreasing trend in fuel oil consumption may be due to switching of home heating fuels, increasing petroleum prices and the efforts of weatherization programs. Fluctuations in the use of natural gas are highly correlated with weather, and increased demand due to fuel switching may be currently offset by the state s energy efficiency efforts. 1 Exploring Strategies for Implementing a Performance Based State Efficiency Program: State Energy Consumption Metrics Residential Sector Analyses, Colin Sheppard, Charles Chamberlin and Arne Jacobson, Schatz Energy Research Center, Humboldt State University in collaboration with Yerina Mugica and Rick Duke, Center for Market Innovation, Natural Resources Defense Council. Released: May 15, For additional information on the PSEP metric: SERC webpage: NRDC webpage: 2 Unless otherwise stated, the energy data used in this report are from the Energy Information Agency of the U.S. Department of Energy s State Energy Data System (SEDS). 3 Throughout the report, MBtu represents one million Btu. 2

3 Figure 1. Map displaying the number of years from that each state made progress in reducing aeci.

4 Analysis of New York s Weather Adjusted Energy Consumption Intensity (aeci) New York s aeci has remained relatively constant over the period of , fluctuating around 50 MBtu/cap/year (Figure 2). 4 Five of the six progress years occurred in the early 1990s and were followed by a period of increasing energy consumption that continued until In 2003, 2005 and 2007, the fiveyear slope of adjusted ECI was slightly negative, but it did not pass the 80% significance test. Figure 2. Adjusted ECI for New York from (above) and Slope of aeci vs. Year with single tailed 80% confidence intervals shown (below). In the upper graph, years without progress are indicated with gray diamonds, years with progress that is not statistically significant are indicated with blue squares, and years with statistically significant progress are indicated with green circles. In the lower graph, a progress year is indicated when the upper bar of the 80% confidence interval falls below zero. 4 The analysis of aeci trends presented in the figure uses state-specific moving average heat rates as described in the PSEP revised methods. HDD and CDD calculations use data from the National Climatic Data Center (NCDC) and assume a base temperature of 65 F; while more accurate base temperatures would be preferable for the analysis, these data are not readily available. 4

5 ENERGY EFFICIENCY INITIATIVES New York s energy efficiency initiatives started with the creation of the New York State Energy Research and Development Authority (NYSERDA) in 1975 and the institution of a building energy code in ,6,7 In the mid to late 1980s, a number of utilities started demand-side management (DSM) programs focused on reducing electricity consumption. In 1996, a Systems Benefit Charge (SBC) was established by the Public Service Commission to fund energy efficiency, low-income services, R&D and environmental protection programs during the state s transition to a competitive electricity market. 8 The SBC, collected from all ratepayers, was used in part to fund the NYSERDA-administered New York Energy $mart SM program. The New York Energy $mart SM program oversees a number of programs focused specifically on encouraging energy efficiency in residential markets including the Single Family and Multifamily Home Performance Programs, the Market Support Program and the Communities and Education Program. Additionally, the New York Energy $mart SM program funds a low-income weatherization program as well as education and outreach programs targeted toward hard-to-reach customers. 9 These programs supplement the federallyfunded Weatherization Assistance Programs administered through the Division of Housing and Community Renewal (DHCR) starting in the 1980s. Additionally, since the 1990s, the New York Energy $mart SM programs have been augmented by efficiency programs targeting the public housing sector run by the New York Power Authority (NYPA) and further market-focused efforts implemented by the Long Island Power Authority (LIPA). 7,10 From its inception in 1998, the New York Energy $mart SM program has gone through three funding cycles: the first from June 1998 through June 2001 at $58 million per year, the second from July 2001 through June 2006 at $147 million per year and the third from July 2006 to June 2011 at approximately $175 million per year. 7 In 2008, the PSC adopted an energy efficiency portfolio standard (EEPS) which called for a reduction in electricity consumption of 15% from projected levels in In an effort to meet this goal, the SBC rate was increased and an additional $80 million per year was allocated to NYSERDA and the state s six investor-owned utilities to expand their efficiency programs. In 2009, an additional natural gas SBC was instituted and allocated $40 million in funding for NYSERDA and the utilities to offer natural gas efficiency measures. 11 This funding represents the only efficiency program focused on residential consumption of natural gas apart from two single-year programs run by Con Edison and administered by NYSERDA in , 13 and Overall, since 1984, funding for energy efficiency programs administered by New York s utilities and energy authorities has increased from $25 million to over $700 million in For more information on NYSERDA, a public benefit corporation focused on helping New York meet its energy goals visit 6 Department of Energy, Status of State Energy Codes: New York, April 6, Much of the information about New York s history of energy efficiency measures was found in Section 4 of the the 2009 State Energy Plan: State Energy Planning Board, Energy Efficiency Assessment New York State Energy Plan 2009, December Downloaded June NYSERDA, New York Energy $mart SM Program Evaluation and Status Report: Interim Report, September Downloaded June NYSERDA. New York Energy $mart SM Program Evaluation and Status Report: Year Ending December 31, March Downloaded June NYPA, Energy Efficiency Services, August 10, 2010, 11 NYSERDA. New York System Benefits Charge Programs Evaluation and Status Report: Year Ending December 31, March Downloaded June Department of Public Service, Commission Ensures Gas Efficiency Program for Con Edison, Press Release, May 16, Downloaded August 10, Personal communication with Phil Mosenthal of Optimal Energy, July 6,

6 The New York Energy $mart SM program has been effective in saving hundreds of GWh of electricity and thousands of MBtu of energy from other fuels each year; total annualized savings have nearly doubled between 2001 and Figures 3 and 4 display the annualized residential electricity and fuel savings reported by the New York Energy $mart SM program in their yearly reports. 7,14 Figure 5 displays the total 14, 15 reported energy savings in the residential sector per capita. The electricity efficiency programs implemented by the LIPA also report substantial savings for the residential sector, estimating to have achieved net annual savings of 76 GWh in 2009, while NYPA reports to have saved over 50 GWh annually since the start of its programs in ,16,17 Figure 3. Annualized Cumulative and Yearly Incremental Electricity Savings reported for New York Energy $mart SM Programs in the Residential Sector Note savings are not reported for 2006, as the largest of the efficiency programs, the Market Support Program, was not evaluated in that year. 14 NYSERDA. New York Energy $martsm Program Evaluation and Status Report: Year Ending December 31, 200X. Downloaded June When calculating total per capita energy savings as reported in Figure 5, annualized electricity savings have been multiplied by a state-specific heat rate to account for primary energy associated with electricity production, allowing the reported savings to be compared to the aeci produced in the PSEP metric (Figure 2). Figure 10 displays the annual state-specific heat rates calculated for New York. Electricity consumption in Figure 3 has not been adjusted to reflect the primary energy, and instead shows reported savings of electricity sales. 16 LIPA, LIPA Efficiency Long Island PY 2009 Assessment Volume 1 May 2010, p Downloaded August 10, This value and the values in Figure 3 have not been adjusted to reflect primary energy. 6

7 Figure 4. Annualized Cumulative and Yearly Incremental Fuel Savings reported for New York Energy $mart SM Programs in the Residential Sector Figure 5. Annualized Cumulative and Yearly Incremental Per Capita Energy Savings reported for New York Energy $mart SM Programs in the Residential Sector

8 Despite these substantial savings, New York falls short of its potential for energy efficiency savings in the residential sector; for comparison, Vermont boasts per capita savings approximately 30% higher than those of New York. 18 Additionally, though New York started addressing energy efficiency in the mid-1970s, during a period of restructuring of New York s electric power industry between 1994 and the start of the New York Energy $mart SM program in 1998, funding for both the state s and utilities energy efficiency efforts was dramatically reduced. 13 This reduction in funding and energy efficiency programs coincides with a period of increase in New York s per capita energy consumption as shown in Figure 6. Figure 6. Timeline of many of New York s energy efficiency efforts 18 This statement is based on savings estimates reported by Efficiency Vermont each year from , and corresponding population estimates reported by the US Census Bureau. Efficiency Vermont, Annual Report 200X, Downloaded March 2010: 8

9 ANALYSIS BY FUEL TYPE New York s residential energy use separated by fuel type suggests that natural gas, electricity and petroleum products meet most of the state s residential energy needs (Figure 7). 19 Since 1985, electricity consumption has experienced some minor fluctuations, but has generally increased at an average rate of approximately 0.11 MBtu/cap/year per year. Natural gas consumption has fluctuated between approximately 18 MBtu/cap/year and 22 MBtu/cap/year with a slightly increasing trend of approximately 0.05 MBtu/cap/year per year. The consumption of petroleum products similarly fluctuates; however per capita consumption has generally decreased since 1985 at an average rate of approximately 0.26 MBtu/cap/year per year. Figure 7. New York s per capita residential energy use distributed by fuel type ELECTRICITY Residential electricity consumption in New York is clearly increasing despite the state s and the utilities targeted efficiency efforts. This paper investigates three possible explanations for this observation, including a demographic shift, increasing penetration of air conditioners and other electric appliances, and a changing grid mix used to produce electricity. This report additionally examines correlations between electricity consumption and both annual degree-days and price. The following analysis suggests that a demographic shift towards older residents, as well as an increase in electric appliances such as air conditioners and personal computers may be causing a substantial increase in the residential energy consumption in the state. Age Distribution As reflected by national data collected through the Residential Energy Consumption Survey (RECS), a demographic shift, particularly an increase in the population s average age, can increase per capita residential energy use. 20 This effect is outside the influence of energy policy makers, and it may therefore be reasonable to correct the ECI trend to account for demographic changes in age distribution within a state. An initial analysis indicated that the effect was small in most states and that the demographic age shifts were similar from state to state following a trend that is consistent with an aging baby boom generation. These shifts in the age distribution of New York s population could account for a 3%, or 0.09 MBtu/cap/year per year, increase in the total aeci from (Figure 8). Assuming the electricity load grows at the same rate 19 The petroleum products, natural gas and electricity data used in this section of the report are not weather-adjusted. 20 The Residential Energy Consumption Survey (RECS) database can be found at 9

10 as the total aeci (3%), this underlying load growth would result in an increase in residential electricity consumption of approximately 0.03 MBtu/cap/year per year. This demographic driven growth alone could offset approximately one fourth of the estimated 0.11 MBtu/cap/year per year reductions in electricity consumption and over one half of the 0.15 MBtu/cap/year per year reductions in total energy consumption resulting from the efforts of the Energy $mart SM programs. 21 A correction for the age distribution effect has not yet been incorporated into the PSEP method, but it may be included in a future version of the metric. Figure 8. Distribution of New York citizens by age (bottom); relationship between age and dimensionless ECI based on analysis of RECS 2005 data set (top right); impact of changes in the age distribution on ECI (top left) demonstrating that from ECI would have increased by ~3% entirely due to shifts in the age of the state s population. 21 Average annual per capita savings were determined by dividing each year s reported savings from the New York Energy $mart SM program by the population and then averaging these savings over the time period. 10

11 AC Penetration A potential driver of electricity consumption is the adoption of air conditioning. Based on data from the RECS surveys, in New York, there has been an increase in air conditioner penetration from approximately 54% to 73% from 1993 to 2005 (Figure 9). Using a rough estimate, the increase in air conditioners alone would increase the rate of growth in demand by 0.06 MBtu/cap/year per year. 22,23,24 This estimate suggests that the growth in the installation of air conditioners accounts for over half of the estimated 0.11 MBtu/cap/year annual estimated savings from the New York Energy $mart SM program. 21 Figure 9. Penetration of air conditioners in residential housing by region (Source: RECS) In addition to the load growth due to air conditioners, the increased use of other electric appliances also contributes to the increased residential energy consumption According to the RECS surveys, in the Mid-Atlantic region, between 1980 and 2001, ownership of microwave ovens and personal computers 22 With approximately 7.06 million households in NY, an estimate of the number of AC units added to the NY housing stock would be 1.3 million, or ~106,000 per year over twelve years. According to the EnergyStar AC Savings calculator, an AC unit with a Seasonal Energy Efficiency Ratio (SEER) of 10 (the low end of efficiency ratings for that period) would consume about 1638 kwh/year. The product of these figures divided by the average population of NY results in about 0.03 MBtu/cap increase in electricity consumption per year. Adjusting this estimate to account for the primary energy associated with electricity consumption results in an average increase of 0.06 MBtu/cap per year. 23 US Census Bureau. State and County Quickfacts. Downloaded June 2010: 24 EnergyStar.gov. Air Conditioning, Central Resources, Savings Calculator. Downloaded March 2010: 11

12 increased more rapidly than that of any other appliances. Households with microwave ovens increased from 7% to 76%, while households with personal computers rose from 17% to 52%. 25 According to another rough calculation, the increased use of these two appliances alone may have contributed 0.03 MBtu/cap/year per year of increased electricity consumption in the region. 23,26,27 This increase, in combination with the increased use of many other appliances, accounts for a substantial portion of the savings from the state s energy efficiency efforts. Grid Mix If New York s average heat rate for electricity generation had increased over time, it could help explain the lack of reduction in the primary energy associated with per capita electricity consumption despite the state s conservation efforts. However, the average heat rate for New York instead has gradually decreased over time, resulting in slightly less primary energy consumed for each unit of electricity consumed in the residential sector (Figure 10). In the current PSEP metric, a heat rate of 1.0 is applied to electricity generated from renewable sources and nuclear power. Since 1975, New York has diversified its production grid mix, lessening its dependence on petroleum products and increasing the use of natural gas, waste and wood to produce electricity. With nearly half of the state s electricity produced by hydropower, nuclear and renewables, the state s heat rate is now slightly less than ,29 25 These figures are reported in the eia s Regional Energy Profile Middle Atlantic Appliance Report, 2001 and based on the RECS data: The Mid-Atlantic region consists of New York, New Jersey and Pennsylvania. 26 Again, with approximately 7.06 million households in NY, an estimate of the number of personal computers and microwaves added to the NY housing stock would be would be 2.5 million and 4.9 million respectively, or ~112,000 and ~221,000 per year over twenty-two years. Assuming a personal computer runs for 4 hours a day at about 270 W (120 W for the CPU and 150 W for the monitor), each computer would consume 394 kwh/year. Assuming a microwave runs for a cumulative 0.5 hours per day at about 1000 W, each microwave would consume kwh/year. The product of these figures divided by the average population of NY results in about MBtu/cap increase in electricity consumption per year attributed to the two appliances. Adjusting this estimate to account for the primary energy associated with electricity consumption results in an average increase of 0.03 MBtu/cap per year. 27 Approximate appliance power consumption was found at: 28 An analysis and calculation of this heat rate can be found in the ground-truth report on Washington State on the PSEP website: 29 Note that Figure 10 displays New York s grid mix for electricity production, which may differ from the grid mix associated with the electricity consumed in New York. Unfortunately data to determine New York s consumption grid mix is not yet available in the SEDS database. 12

13 NY Grid Mix Fraction of Grid by Energy Source Wind Elec. Waste to Elec. Wood to Elec. PV/Solar Thermal Elec. Petroleum to Elec. Nuclear Natural Gas to Elec. Hydro Elec. Geothermal Elec. Coal to Elec Dimensionless Heat Rate !!!!!!!!!!!!! NY Heat Rate!!!!!!!!!!!!!!!!!! Figure 10. New York s generation grid mix by fraction of total electricity production and the associated dimensionless heat rate!! Correlation with Electricity Price and Weather Because energy consumption is often responsive to changes in energy price, decreasing prices could stimulate rising consumption. Residential electricity is characteristically inelastic in that there is not a strong relationship between demand and price. According to an NREL study, which estimated price-elasticities using a complex regression model, New York s residential electricity consumption is not an exception, with a short-term elasticity of and long-term elasticity of Similar, though slightly stronger relationships were suggested from a simple a linear regression analysis; per capita consumption is weakly negatively correlated with the average electricity price (R 2 =0.34). At times when the annual average electricity rate was high, consumption was lower and vice versa (Figures 11 and 12). 31 Electricity rates have declined slightly since the 1980s; these lower rates could be encouraging a slight increase in consumption. 30 Bernstein, Mark and James Griffon, Regional Differences in the Price-Elasticity of Demand for Energy, RAND Corporation technical report prepared for NREL and US DOE, Price elasticity in its simplest form is the percentage change in demand for a good divided by the percentage change in price of the good. A good is said to be inelastic (not particularly responsive to changes in price) when its elasticity is between zero and negative one. Goods with elasticities less than -1 are said to be elastic, or responsive to changes in price. 31 Prices are inflation adjusted to be equivalent to year 2000 USD. 13

14 Figure 11. Per Capita Residential Electricity Consumption and Price of Electricity from Figure 12. Correlation of per Capita Residential Electricity Consumption and Price Residential electricity consumption does not show a strong relationship with annual heating or cooling degree-days (Figures 13 and 14). 32 The R-squared values for the correlations were 0.12 for heating degreedays and 0.22 for cooling degree-days, suggesting that electricity consumption is slightly more responsive to hot weather, likely due to the use of air conditioners. That the response to cooling degree-days is not stronger may be due to the relatively small percentage of the residential electricity consumption that can be 32 Though the total aeci used in the PSEP metric is adjusted for weather, the data presented in these and similar figures showing energy consumption disaggregated by individual fuel type (electricity, natural gas, fuel oil) has not been weather-adjusted and instead has been used to determine how much of an effect heating and cooling needs have on the use of individual fuel types. 14

15 attributed to air conditioning. 33 The weak but statistically significant correlation between electricity use and heating degree days can be explained by the minimal use of electricity for home heating as reported by the RECS surveys (Figure 15). Figure 13. Per Capita Residential Electricity Consumption and Heating Degree Days from (Data Source SEDS and NCDC) Figure 14. Per Capita Residential Electricity Consumption and Cooling Degree Days from (Data Source: SEDS and NCDC) 33 According to RECS data from New York in 1997, 2001 and 2005, air conditioning accounts for between 9% and 17% of the state s total residential electricity consumption. 15

16 Figure 15. Trends in types of residential heating in New York as reported by the RECS surveys NATURAL GAS AND FUEL OIL The use of both natural gas and fuel oil has fluctuated substantially since 1985; however per capita fuel oil consumption has clearly declined over time, while the consumption of natural gas does not seem to display a particular trend (Figure 7). One potential explanation for the decrease in fuel oil consumption is the reduction in households using fuel oil as their primary heating fuel as shown in Figure 15. This fuel switching may also be increasing the underlying demand for natural gas, which is perhaps being offset by both the likely efficiency upgrades occurring by switching heating equipment and the state s energy efficiency efforts. Additionally, the efficiency efforts and weatherization programs targeted at fuel use may have substantially reduced fuel oil consumption. On average, the total per capita fuel savings (natural gas, fuel oil and kerosene) as reported by the New York Energy $mart SM program averaged approximately MBtu/cap/year per year, which could account for approximately one fourth of the 0.26 MBtu/cap/year per year average decline in the consumption of petroleum products. 21 The remaining balance could be explained in part by additional state weatherization programs and the state s building energy code. Additionally, correlations between fuel consumption and both price and heating degree-days are investigated. Building Energy Code New York's Energy Conservation Construction Code (ECCCNYS) is mandatory statewide for both residential and commercial buildings. The residential code became effective in 1989 and has since been updated to be as stringent as the 2004 IECC with amendments. 34,35 In 2009, thanks to stimulus funding from the DOE, $123 million will be provided to aid local jurisdictions, architects, engineers and homebuilders to comply with the increasingly stringent energy efficiency measures mandated by the code. 34 American Council for an Energy Efficient Economy, Building Codes: New York, March 31, Department of Energy, Status of State Energy Codes: New York, April 6,

17 While building codes can be very effective at achieving reductions in heating fuel use, New York has an extremely low rate of new housing starts, which reduces the ability of a building code to induce near term reductions in energy consumption. 36,37 Heating Degree Days Visually, the trends in the use of natural gas and petroleum products and annual heating degree-days seem to fluctuate in tandem (Figures 16 and 17). When a linear regression analysis is run to determine the dependency of fuel oil use on heating degree-days and natural gas consumption on heating degree-days, the correlation explains approximately 17% of the fluctuation in the fuel oil use and 12% of the fluctuation in natural gas consumption between 1985 and Interestingly, when this same analysis is performed starting in 1990, the correlation explains approximately 75% of the natural gas consumption (Figure 17). Perhaps this stronger correlation is due to the increased use of natural gas for space heating due to fuel switching from as indicated by the RECS surveys (Figure 15). Figure 16. Per Capita Residential Natural Gas Consumption and Heating Degree Days from (Data source: SEDS and NCDC) 36 According to data from the National Association of Homebuilders, from New York saw approximately 2.1 new housing starts for every 1000 people, ranking 50 th in the nation. 37 Aroonruengsawat et al. suggest that in 2006, New York s statewide building code may have reduced per capita residential energy consumption by approximately 5%. Aroonruengsawat, Anin, Maximilian Auffhammer and Alan Sanstad, The Impact of State Level Building Codes on Residential Electricity Consumption, University of California, Berkeley, November 25, 2009, 38 In reality, the fuel oil data may be more strongly correlated. The data presented represent annual sales of fuel oil, and fuel oil, unlike electricity or natural gas, can be stored from year to year and is not monitored at the time of use. Therefore, correlations of annual data may be inaccurate. 17

18 Figure 17. Per Capita Residential Fuel Oil Consumption and Heating Degree Days from (Data source: SEDS and NCDC) Figure 18. Regression Analysis of Natural Gas Consumption and Heating Degree Days, (Data source: SEDS and NCDC) Price Fuel oil consumption is weakly correlated to the average annual price of fuel oil, while a linear regression analysis shows no clear relationship between natural gas and price between the years (Figures 19 and 20). 31 A regression analysis suggests that a slightly negative linear relationship exists between fuel oil and price (fuel oil use decreases as price increases), though price fluctuations only explain approximately 15% of the fluctuations in fuel oil sales (Figure 21). 38 The lack of correlation between natural gas and price suggests that price has not been a driver in the fluctuating consumption of natural gas. These findings are supported by previous studies which suggest that fuel oil consumption in New England is moderately 18

19 inelastic with a price-elasticity of -0.55, while natural gas consumption in New York is inelastic and even displays positive price-elasticities (an increase in demand with an increase in price). 39,30 Figure 19. Correlation of per Capita Residential Natural Gas Consumption and Price Figure 20. Correlation of per Capita Fuel Oil Consumption and Price 39 EIA. Regional Residential Heating Oil Model, from American Statistical Society s spring meeting: April 2005, Downloaded August

20 Figure 21. Regression analysis of fuel oil use versus fuel oil price,

21 CONCLUSION New York s record of energy efficiency policies is not reflected by commensurate progress under the PSEP metric. Residential consumption of electricity, natural gas and fuel oil were all analyzed to determine potential effects of efficiency efforts and factors that may influence residential consumption. Some fluctuations in New York s per capita residential energy consumption coincide with shifts in intensity of DSM and energy efficiency efforts. The increasing residential electricity consumption may be explained in part by a demographic shift in New York s population, as well as increasing appliance and air conditioner use, which could offset a significant portion of the savings from the state s electricity efficiency efforts. A decreasing trend in the price of electricity may also be encouraging some growth in consumption. The state s slightly decreasing heat rate has not contributed to the increase in primary electricity consumption and electricity consumption does not seem to be strongly correlated with weather. The decreasing trend in fuel oil consumption may be due to switching of home heating fuels, increasing petroleum prices and the efforts of weatherization programs. Fluctuations in the use of natural gas seem to be highly correlated with weather, and increased demand due to fuel switching may be currently offset by the state s weatherization efforts. All of the prior analysis is based on historical energy data and savings estimates from 1985 until In 2008, New York adopted an energy efficiency portfolio standard, significantly expanding their energy efficiency programs and providing funding for the investor-owned utilities to manage additional programs. Further funding was allocated in 2009 to create programs specifically targeting natural gas use. Perhaps this increased funding for targeted programs will enable New York to reduce its future per capita energy consumption. 21