Kyoto - End-Use Energy Demand (Residential & Commercial)

Report#:SR/OIAF/98-03

Background

This chapter provides in-depth analyses of the carbon emissions reduction cases for the four end-use demand sectors—residential, commercial, industrial, and transportation. Additional analyses are included for a number of alternative cases, including low and high technology sensitivity cases, which have the most direct impacts on energy end use.

Primary and Delivered Energy Consumption

In each of the reduction cases, carbon emissions are reduced through a combination of switching to carbon-free or lower-carbon fuels, reductions in energy services, and increased energy efficiency. The latter two options lower total energy consumption (Figure 25).

Electricity generation typically consumes about three times as much energy, on the basis of British thermal units (Btu), as is contained in the electricity delivered to final consumers. In AEO98, total delivered energy consumption in 1996 is estimated at 70.4 quadrillion Btu, compared with total primary energy consumption of 94.0 quadrillion Btu (Table 3). The difference comes from electricity-related generation and transmission losses and, consequently, is relatively small for the transportation sector, where little electricity is consumed. Although the delivered price of electricity per Btu generally is more than three times the delivered price of other energy sources, the convenience and efficiency of electricity use outweigh the price difference for many applications.

Because consumers base their fuel and equipment choices on performance at the point of use, the analysis of end-use energy consumption presented in this chapter focuses on energy delivered to final consumers. When consumers choose to purchase a particular type of energy-consuming equipment or to use a particular fuel, their decisions are based on the cost and performance characteristics of the technology, mandated efficiency standards, and energy prices. End-use energy prices include all the direct costs of providing energy to the point of use.

The distinction between end-use and primary energy consumption is an important one for the evaluation of efficiency standards and other energy policies. Reducing electricity demand through the use of more efficient technologies reduces primary energy consumption by a factor of three. In addition, although electricity at its point of use produces no carbon emissions, reductions in electricity use produce savings in emissions from the fuels used for its generation.

Integrated Energy Market Analysis

The analysis in this report is a fully integrated analysis of U.S. energy markets, representing the interactions of energy supply, demand, and prices across all fuels and sectors. For example, initiatives to lower energy consumption may lower the prices of the energy supplied, causing some offsetting increase in energy consumption. An integrated market analysis can capture such feedback effects, which may be missed in an analysis that focuses on end-use demand for energy without accounting for impacts on energy prices.

The Energy Information Administration’s Annual Energy Outlook 1998 (AEO98), includes results from a number of alternative sensitivity cases in addition to its reference case projections. Sensitivity cases generally are designed by varying key assumptions in one of the demand, conversion, or supply modules of the National Energy Modeling System (NEMS), in order to isolate the impacts of the revised assumptions. For example, the high technology sensitivity cases for the end-use demand sectors in AEO98 do not include any feedback effects from energy prices, and energy consumption in each sector is lower than in the reference case solely due to the revised assumptions about technology costs and efficiencies. The sensitivity cases described in this report, in contrast, were combined into an integrated analysis. As a result, lower energy consumption in the high technology case leads to lower energy prices, which in turn produce some offsetting increases in consumption.

Carbon emission reduction targets and carbon prices further complicate the integrated market analysis. In the high technology sensitivity cases presented in this chapter, the carbon reduction targets are the same as those in the comparable cases that use the AEO98 reference case technology assumptions. For example, the 9-percent-above-1990 (1990+9%) case and the 1990+9% high technology sensitivity case have the same carbon emissions target. The effect of the high technology assumptions is to lower the projected carbon price that would be required to achieve the same level of carbon emissions, which also reduces the delivered price of fuel. With lower carbon prices, adverse impacts on the macroeconomy and on energy markets are moderated. Assuming that the technological advances posited in the high technology cases for the various end-use sectors could in fact be achieved, energy consumption levels would not necessarily be lower in each sector. Rather, the carbon price would be lower, and it would be less costly to achieve a given emissions reduction target.

Residential Demand

Background

As the largest electricity-consuming sector in the United States, households were responsible for 20 percent of all carbon emissions produced in 1996, of which 63 percent was directly attributable to the fuels used to generate electricity for the sector. Electricity is a necessity for all households, and with electricity use per household growing at 1.5 percent per year since 1990, the projected increase in residential sector electricity consumption has become a central issue in the debate over carbon stabilization and meeting the goals of the Kyoto Protocol.

The number of occupied households is the most important factor in determining the amount of energy consumed in the residential sector. All else being equal, more households mean more total use of energy-related services. From 1980 to 1996, the number of U.S. households grew at a rate of 1.4 percent per year, and residential electricity consumption grew by 2.6 percent per year. In the reference case, the number of households is projected to grow by 1.1 percent per year through 2010, and residential electricity consumption is projected to grow by 1.6 percent per year. Strong growth in the South, which features all-electric homes more prominently than do other areas of the country, and the advent of many new electrical devices for the home have significantly contributed to high electricity growth since 1980. Although these trends are projected to continue through 2010, efficiency improvements—due in part to recent Federal appliance standards, utility demand-side management programs, building codes, and nonregulatory programs (e.g., Energy Star)—should dampen electricity growth somewhat as residential appliances are replaced with newer, more efficient models.

Within the residential sector, all of the major end-uses (heating, cooling, lighting, etc.) are represented by a variety of technologies that provide necessary services. Technologies are characterized by their cost, efficiency, dates of availability, minimum and maximum life expectancies, and the relative weights of the choice criteria—installed cost and operating cost. The ratio of the weight of installed cost to that of operation cost gives an estimate of the “hurdle rate” used to evaluate the energy efficiency choice.²⁴ When more emphasis is placed on installed cost, the hurdle rate is higher. The hurdle rates for residential equipment range from 15 percent for space heating technologies to more than 100 percent for some water heating applications. The range in part reflects differences in the way consumers purchase the two technologies. In the case of water heaters, for example, purchases tend to occur at the time of equipment failure, which tends to restrict the choice to equipment readily available from the plumber. Space conditioning equipment, on the other hand, is not used all year round, allowing some latitude in terms of timing the replacement of an older unit. It is assumed that residential consumers expect future energy prices to remain at the current level at the time of purchase when calculating the future operating cost of a particular technology.

Technological advances and availability play a large role in determining future energy savings and carbon emission reductions. Even in today’s marketplace, there exist many efficient technologies that could substantially reduce energy consumption and carbon emissions, however the relatively high initial cost of these technologies restricts their widespread penetration. Over time, the costs of more advanced technologies are assumed to fall as the technology matures, one example being natural gas condensing water heaters. In addition, technologies that are not available today but are nearing commercialization are assumed to become available in the future. Three technology menus are used in the analysis below: a reference technology menu, a high technology menu (reflecting more aggressive research and development), and a “frozen” menu limited to equipment available today. In all cases, the menu options and characteristics are fixed. In the high technology sensitivity case, for example, the cost of a condensing natural gas water heater is assumed to fall by almost 75 percent by 2005, relative to the reference case, and a natural gas heat pump water heater becomes available for purchase, by 2005.

In response to energy price changes, residential elasticities, defined as the percent change in energy consumed with a 1-percent change in price, range from -0.24 to -0.28 in the short run, depending on the fuel type, to -0.33 to -0.51 in the longer term. The elasticities reported here are derived from NEMS by a series of simulations with only one energy price varying at a time, beginning in 2000.²⁵ These price elasticities reflect changes in both the demand for energy services and the penetration rate of more efficient technologies. In the absence of energy price changes, energy intensity, as defined as delivered energy consumption per household, declines at an average rate of 0.5 percent per year through 2010. This non-price-induced intensity improvement reflects the efficiency gain brought about by ongoing stock turnover, equipment standards, new housing stock, and the future availability of new technologies.

Energy consumption, including the combustion of various fossil fuels, is the major source of U.S. carbon emissions. Energy use in the residential sector is greatly affected by year-to-year variations in seasonal temperatures, particularly in the winter, as illustrated by the decline in delivered energy use in 1990 (Figure 26), which was one of the warmest winters on record. The projections in this analysis assume normal seasonal temperatures over the 1996-2020 forecast period.

In the 3-percent-below-1990 (1990-3%) carbon reduction case, which assumes an emissions target of 3 percent below 1990 levels for the United States, a sharp drop in residential energy use is projected between 2005, when the target is implemented, and 2010 (Figure 26). However, the projected decline is nearly identical to that seen historically from 1978 to 1983, in terms of both consumption and intensity (Figure 27). Housing starts, a major predictor of residential energy use, fell from 2.02 million units in 1978 to 1.062 million in 1982.²⁶ The drop in housing starts was tied directly to mortgage rates, which increased from 9.6 percent in 1978 to over 16 percent in 1981-1982. In addition, real energy prices to the residential sector increased by 87 percent from 1978 to 1982, similar to the 82-percent real price increase projected in the 1990-3% case. In the carbon reduction cases, delivered energy consumption in the residential sector never reaches its 1990 level, which has been used as a benchmark in setting carbon reduction targets. Given the uncertainty regarding technology and consumer behavior in a high-price energy world, additional sensitivities are examined here to analyze the effects of variations in the level of optimism associated with assumptions about both technology advances and consumer responsiveness.

Carbon Reduction Cases

Carbon emissions associated with electricity generation are the largest component of emissions from the residential sector, in terms of both the levels and projected growth in the reference case, and in terms of the projected declines in the carbon reduction cases. In the reference case, which does not include the Kyoto Protocol, 98 percent of the projected increase in residential sector carbon emissions by 2010 results from increasing electricity use and the fuels used for electricity generation. In the 1990+9% case, 87 percent of the sector’s decline in carbon emissions is related to reduced electricity demand and changes in electricity generation (Figure 28). The following discussion focuses on the results of three carbon reduction cases—1990-3%, 1990+9%, and 24-percent-above-1990 (1990+24%)—in which carbon emissions, averaged across all energy sectors, reach targeted levels relative to 1990 in the 2008-2012 period.

Although the use of electricity contributes most to the projected growth in emissions in the residential sector, natural gas consumption, which emits relatively low levels of carbon per Btu burned compared with coal (the major fuel used to generate electricity), is projected to remain the most important fuel in the sector as measured by delivered energy. Figure 29 shows delivered energy consumption by major fuel as well as the losses associated with electricity generation. On a delivered basis, natural gas use is projected to decrease the most in the three carbon reduction cases by 2010. Relative to the projected level of consumption in the reference case in 2010, delivered energy consumption is projected to be 10 percent lower in the 1990+9% case and electricity-related losses 22 percent lower. Of the 2.0 quadrillion Btu savings in electricity-related losses in 2010 in the 1990+9% case, 43 percent (0.9 quadrillion Btu) can be attributed to reduced electricity demand in the residential sector. The remaining 1.1 quadrillion Btu (57 percent) of the savings in electricity-related losses comes from efficiency gains and/or fuel switching for electricity generation. Thus, changes in electricity supply, absent any major technological or behavioral changes in residential end use over the next 12 years, are the key to controlling carbon emissions for the residential sector.

Energy is used in the residential sector to provide a number of different services, which vary in end-use intensity (energy consumption per household) (Figure 30). Space conditioning (which includes heating, cooling, and ventilation) is clearly the most energy-intensive end use in the sector, and it accounts for most of the direct use of fossil fuels. “White goods” (which include refrigerators, freezers, dishwashers, clothes washers and dryers, and stoves), lighting, and other uses are almost entirely powered by electricity and, therefore, are responsible for most of the electricity-related losses.

In the reference case, most of the projected growth in residential energy consumption between 1996 and 2010 comes from increasing use of miscellaneous electric devices, such as personal computers and home security systems (Figure 31). The rate at which energy consumption changes over time depends on factors such as equipment turnover rates, ability to control unit operation (thermostatic controls), energy prices, household size (people per house), housing unit size (square feet), and the efficiency of newly purchased appliances. Stock turnover can provide drastic reductions in energy intensity, even without future gains in appliance efficiency. On average, a new refrigerator purchased in 1995 used 62 percent less electricity than one purchased 20 years earlier.²⁷ Conversely, slow stock turnover can limit the role of energy efficiency gains in the future. Equipment purchased in the 1990s that lasts 20 years or more will not be eligible for replacement until after 2010.

With the exception of white goods, increases in total energy consumption for all the major residential energy services are projected from 1996 to 2010 in the reference case. The negative growth in total energy consumption for white goods results from a decline in energy use for refrigeration, as aggressive Federal efficiency standards²⁸ taking effect in 1993 and 2001 reduce the amount of energy needed to provide the same level of service. In the carbon reduction cases, increasing energy prices act to reduce the growth in energy consumption for all major services relative to their growth in the reference case. In the absence of mandatory standards, residential consumers traditionally have been reluctant to purchase highly efficient appliances. However, faced with the higher energy prices projected in the carbon reduction cases, it is expected that consumers will respond by purchasing more efficient appliances (Table 4). The extent of consumer response and its impact on average equipment efficiencies would also depend on the purchase price of the new equipment (the initial investment required).

In the reference case, the real (inflation-adjusted) prices of electricity and natural gas to residential consumers are projected to decline between 1996 and 2010 (Figure 32), by 8 and 10 percent, respectively. The outlook for prices in the carbon reduction cases, however, is much different. Without major changes in energy policy, technology, or consumer response, prices to the residential sector are expected to be as much as 94 percent higher in 2010 in the 1990-3% case. In response to the higher prices, total residential energy consumption is projected to decline by more than 20 percent by 2010 in the 1990-3% case.

The factors that contribute to lower consumption include behavioral responses, such as adjusting the thermostat or turning off the lights when leaving the room, and, to a lesser extent, the acquisition of more efficient appliances. The rate of improvement in average appliance efficiency is constrained by the rate of stock turnover. For example, it is not uncommon for major energy-using appliances, such as furnaces, to last for 30 years or more. More immediate responses to higher energy prices can be achieved through retrofits to improve the thermal efficiency of building shells. During the energy price shocks of the 1970s, for example, homeowners increased insulation levels substantially,²⁹ with the immediate effect of conserving energy and lowering energy bills. The potential for similar improvement between 1996 and 2010 is reduced, given the improvements already made.

Sensitivity Cases

High and Low Technology. Technology improvements over time can take the form of increased efficiency, decreased cost, or both. To examine the effects of assumptions about the rate at which technologies will improve in the future, two sets of sensitivity cases were analyzed. The low technology sensitivity cases assume that none of the improvements assumed in the reference case will occur. In other words, future technologies are assumed to be “frozen” at their 1998 cost and efficiency levels. Technological improvement occurs in this case as older units are retired and are replaced with 1998 technologies. Engineering technology experts were consulted to develop the high technology case, which assumes more rapid advances than those in the reference case, due to research and development (Table 5).³⁰ In the high technology case, for example, the efficiency of the best available natural gas water heater is assumed to improve by 63 percent over the 1998 level by 2015, and the cost is assumed to decline by 15 percent, while ground-source heat pumps, which do not realize much gain in efficiency, are assumed to decline in cost by 44 percent in the high technology case by 2015. while ground-source heat pumps, which do not realize much gain in efficiency, are assumed to decline in cost by 44 percent in the high technology case by 2015.

Ground-source heat pumps, which draw stored heat from the ground beneath the frost line, provide an efficient and comfortable (in terms of delivered heat) alternative to the more common air-source heat pumps. The cost of the unit and the placement of the ground loop have been major barriers to wide market acceptance, however. Different levels of stocks of ground-source heat pumps are projected in the reference case, the 1990+9% carbon reduction case, and the 1990+9% case low and high technology cases (Figure 33). Given that significant market acceptance is seen only in the high technology case, it can be concluded that the costs associated with the technology restrict its acceptance. Space heating technologies, in general, have the lowest hurdle rates (15 percent) of all residential appliances, primarily because of the large energy costs of home heating, relative to other energy-using services.

Figure 34 shows that improvements in technology can indeed dampen the impact carbon restrictions have on residential energy prices. Given the amount of time needed for technology to penetrate the market, one would expect that over a longer period of time, the prices in the high technology sensitivity would fall relative to the other cases. After 2008, prices in the high technology sensitivity begin to fall, as reduced energy demand caused by more efficient technology penetrating the market begin to make an impact. Relative to the price in the 1990+9% case, the composite real residential energy price in 2010 is 11 percent less in the high technology case. Conversely, if technology were frozen at the level available in 1998, 2010 prices are expected to be 17 percent higher than the 1990+9% case, indicating that energy efficiency plays a significant role in the cases with reference technology assumptions.

Energy fuel expenditures are a good indication of the success that technological advancement achieves in lessening the impact on the consumer in a carbon-restricted environment. Figure 35 details residential sector energy expenditures for the 1990+9% case and technology sensitivities. For the high technology sensitivity, energy expenditures in 2020 are 23 percent less than those realized in the 1990+9% case, saving consumers over $440 billion from 2008 to 2020.

Renewables and Dispersed Electricity Generation

Dispersed renewable energy use in the residential sector includes wood, solar thermal, geothermal energy, photovoltaic cells, and fuel cells.^a Wood is used as a main or secondary heating source in some households. Geothermal energy is used to power ground-source heat pumps, which exchange energy with below-ground earth or water, extracting heat in the winter and delivering heat to the earth (and cooling the building) in the summer. Solar thermal energy is used mainly to heat water for swimming pools and household use. Photovoltaics provide small-scale electricity generation, often in remote locations, using semiconductors to transform sunlight directly into electricity, which may be used for a variety of functions, such as water pumps or remote lighting systems. Fuel cells convert liquid fossil fuels into electricity through electrochemical processes.

The share and quantity of wood as a primary heating fuel in the residential sector has been falling for nearly two decades. In 1982, 6.7 percent of all U.S. households heated with wood, but its share fell to 3.2 percent in 1993. The aggregate quantity of wood consumed as primary heating in households has fallen as well, from 28.7 million cords in 1982 to 12.6 million cords in 1993.^b The decline has resulted in part from local laws restricting wood burning. In addition, the convenience of natural gas heating and the decline in real oil and gas prices over the past decade have led many households to choose gas or oil over wood.

While wood has declined as a primary residential heat source, its use as a backup or secondary heat source has not. Wood use as a secondary heat source increased from 16 percent of households in 1980 to 20 percent in 1993, suggesting that wood stoves are being kept as backup heating systems. If the prices of other fuels rise significantly, however, the use of wood as a primary household heating fuel may well increase. In the reference case for this analysis, wood energy use is projected to be 0.61 quadrillion Btu in 2010. In the most stringent carbon reduction case (7 percent below 1990 levels), higher energy prices lead to wood use of 0.63 quadrillion Btu in 2010, increasing to 0.67 quadrillion Btu in 2020.

The market for solar energy systems has undergone substantial changes over the past three decades, largely as a result of the introduction, removal, and subsequent reintroduction of Federal energy tax credits for photovoltaic cells and solar thermal collection systems. With the introduction of a Federal tax credit in 1978, shipments of solar thermal collectors to the residential and commercial sectors nearly doubled to 10 million square feet from 5.8 million square feet in 1976. The annual growth inshipments averaged 8 percent per year until 1985, when the tax credits were repealed. Subsequently, shipments fell sharply from 19.1 million square feet in 1985 to 9.1 million in 1986. The energy tax credit was reintroduced for the commercial sector in 1986, followed by a small increase in shipments, but since 1991 there has been little growth in the industry. Residential sales of solar thermal systems are not expected to increase substantially in the reference case, given current tax policy and projected declines in real energy prices.

Domestic shipments in the photovoltaic market (including both dispersed and grid-connected system) have grown significantly since the 1980s, but they also were affected by the repeal of the tax credit. From 10,717 peak kilowatts shipped in 1983, shipments were down to 3,224 peak kilowatts in 1986 after the tax credit repeal, a 32-percent average annual decline.^c The market recovered somewhat in the next decade, with 1992 shipments reaching 5,760 peak kilowatts. Since then, the industry has been developing steadily, particularly after 1992, with 23-percent average annual growth to 13,016 peak kilowatts shipped in 1996.

Fuel cells have the potential for future integration into both grid-connected and off-grid applications in every sector. When their cogenerative capabilities are used, capturing excess heat from the chemical reaction for space and water heating, fuel cell efficiencies can rise to two or three times those of typical energy combustion plants, emitting only half the amount of carbon dioxide per unit of useful energy obtained.^d

To date, fuel cells have not been used extensively. With their relatively recent development and only one major manufacturer worldwide, there are only 160 medium-sized (200-kilowatt) units in use.^e Smaller units have been tested in the space program and in the automobile industry, but the first unit designed for the residential market was not built until 1998.^f Fuel cells are a promising technology for the residential sector, but their current high costs do not favor extensive market penetration. Costs can be expected to fall as production volumes increase, and depending on the timing and extent of the cost reductions, fuel cells could become an important source of dispersed electricity generation.

^aDispersed renewable energy is the direct use of power from a renewable energy system such as a photovoltaic array, disconnected from the electric power grid. The production and sale of electricity from utilities using renewable energy fuels are not included.

^bEnergy Information Administration, Housing Characteristics 1980, DOE/EIA-0312 (Washington, DC, June 1982), p. 101; Housing Characteristics 1982, DOE/EIA-0314(82) (Washington, DC, August 1984), pp. 47-98; and Household Energy Consumption and Expenditures 1993, EIA/DOE-0321(93) (Washington, DC, October 1995), pp. 37-62.

^cEnergy Information Administration, Renewable Energy Annual 1997, Vol. 1, DOE/EIA-0603(97/1) (Washington, DC, February 1998), p. 19.

^dWhen byproduct heat is used, average total efficiency of the system increases to approximately 80 percent, significantly more than a standard coal-fired utility plant, which operates at around 30 percent efficiency. Source: U.S. Department of Energy, Office of Fossil Energy, Technology Center, Climate Change Fuel Cell Program, NG001.1197M.

^eFred Kemp, Manager of Government Programs, International Fuel Cells (South Windsor, CT), personal communication, August 1998.

^fNew York Times (June 17, 1998).

Increased Consumer Response. Residential energy consumers have traditionally been reluctant to invest in energy efficiency, even with ample financial benefits. Many market barriers tend to create what are known as high hurdle rates for consumer investments in energy efficiency. As of 1993, 35 percent of all homes were occupied by renters,³¹ most of whom were responsible for paying energy bills but not for purchasing major energy-consuming appliances. Such households tend to buy the least expensive equipment on the market, which also tends to be the least energy-efficient. The same reasoning can be applied to many newly constructed homes as well, because the builders, not the occupants, are tasked with equipping them with most of the major energy-using appliances. Other barriers include equipment availability (e.g., whether plumbing contractors have high-efficiency water heaters available when they make service calls) and lack of information.

To examine the effects that lower hurdle rates could have on both energy prices and expenditures in the carbon reduction cases, and at the same time differentiate those effects from the effects of technological advances, an increased consumer response sensitivity case was analyzed. This sensitivity case includes assumptions of lower discount rates, higher short-run elasticities of demand, greater inclination to change fuels when purchasing equipment, and lower growth in miscellaneous electricity use.³²

Impacts of Increased Consumer Response and Advanced Technology. In order to gauge the impact of assumptions regarding technological advancement and consumer behavior with respect to delivered energy consumption, sensitivity cases were analyzed relative to the 1990+9% case where delivered energy prices were the same across all cases. These cases serve to isolate the impact of each of the key variables separately, and to understand the impact of implementing the sensitivities simultaneously. This section evaluates the relative impact that each of these concepts could have on future energy intensity at a price level realized in the 1990+9% case.

Changes in technological development and the value residential consumers place on energy related issues can significantly affect the pattern of energy consumption—and carbon emissions—in the future. The availability of high-efficiency technologies in itself does not guarantee increased energy efficiency. Without the willingness of consumers to purchase the more efficient products, which usually cost significantly more, technology may not have much of an impact on future energy consumption patterns. Conversely, in a world where energy conservation was of paramount concern to energy consumers, yet at the same time high-efficiency products were unavailable, future energy consumption patterns would probably not be greatly affected either.

Given the detailed nature regarding technological development and consumer choice with regards to different technologies, it is important to analyze the results at the technology level, as well as the overall level. With nearly 40 million households (38 percent) using electric water heaters in 1995, and given the relatively high intensity associated with using electric water heaters, the projected impact of increased energy efficiency can have a large impact on future electricity use for this service. Electric resistance water heaters have traditionally exhibited slow growth in energy efficiency. In fact, the highest efficiency unit available today is not likely to see any efficiency improvement due to thermal limits and diminishing returns on controlling heat loss.³³ This implies that future gains in efficiency for electric water heating must be achieved through the increased penetration of electric air-source heat pump water heaters, which achieve higher efficiency levels by extracting heat from the air surrounding the unit. The current cost of this technology, however, is several times that of a traditional resistance unit, and coupled with observed implicit discount rates of over 100 percent, has led to very limited market penetration.

Assumptions regarding technological advances through improved performance and reduced cost, as well as changes in consumer behavior, can significantly affect the market penetration of emerging technologies. Figure 36 details the relative importance of varying assumptions regarding technological advances and consumer behavior with respect to the intensity of the electric water heating end use.³⁴ Relative to the 1990+9% case, intensity drops faster when assumptions regarding consumer behavior are changed, as compared to changes in technology characteristics. Over time, however, the intensity decline in the technology case outpaces that projected for the behavior case as more and more equipment is purchased at higher efficiency levels. Combining both sets of assumptions, that is, changing both technology characteristics and consumer behavior together, results in over a 25 percent decline in energy intensity for electric water heating over time. This indicates that a combination of both technology and consumer behavior changes can bring about large declines in energy intensity for this service, all else being equal.

Overall annual energy consumption per household, or energy intensity, for these sensitivity cases follows the general pattern described for electric water heating. Again, technology advances exhibit a greater potential for energy intensity decline in the long run (Figure 37), but the combination of the two cases yields roughly half of the intensity decline projected for electric water heating. This is due to the fact that all other major technologies exhibit much lower observed hurdle rates and less range in terms of high-efficiency products. For example, natural gas furnaces, the largest energy consuming product class in terms of delivered energy in the U.S., has already matured in terms of product efficiency, and at the same time hurdle rates are at 15 percent.

Commercial Demand

Background

The commercial sector consists of businesses and other organizations that provide services. Stores, restaurants, hospitals, and hotels are included, as well as a wide range of facilities that would not be considered “commercial” in a traditional economic sense, such as public schools, correctional institutions, and fraternal organizations. In the commercial sector, energy is consumed mainly in buildings, and relatively small amounts are used for services, including street lights and water supply.

The commercial sector is currently the smallest of the four demand sectors in terms of energy use, accounting for 11 percent of delivered energy demand in 1996. The commercial sector is also responsible for fewer carbon emissions than the other sectors, emitting 230 million metric tons, or 16 percent of total U.S. carbon emissions, in 1996. The sector has a larger share of emissions than its share of energy use because of the importance of commercial electricity use. The emissions associated with electricity-related losses are included in the calculation of emissions from electricity use.

Several factors determine energy use and, consequently, carbon emissions in the commercial sector. One of the most important is floorspace. Building location, age, and type of activity also affect commercial energy use. Currently, total commercial floorspace in the United States exceeds the area of the State of Delaware and amounts to about 200 square feet for every U.S. resident. Mercantile (retail and wholesale stores) and service businesses are the most common type of commercial buildings, and offices and warehouses are also common.³⁵

Because of the relatively long lives of buildings, the characteristics of the stock of commercial floorspace change slowly. Over half of the commercial buildings in the United States were built before 1970, and the reference case used for this analysis projects that total commercial floorspace will grow at about the same rate as population, 0.8 percent annually, through 2020. This limits the effects that new, more efficient building practices can achieve in the near term, but as time passes and building stock “turnover” occurs, current and future building practices will have a greater effect on commercial energy use.

The composition of end-use services is another determinant of the amount of energy consumed and the type of fuel used. The majority of energy use in the commercial sector is for lighting, space heating, cooling, and water heating. In addition, the proliferation of new electrical devices, including telecommunications equipment, personal computers, and other office equipment, is spurring growth in electricity use. Electricity use currently accounts for 45 percent of delivered energy consumption in the sector, and that share is projected to grow to about 48 percent by 2010 in the reference case.

Consideration of end-use services leads to another determining factor in commercial energy consumption—the effects of turnover and change in end-use technologies. The stock of installed equipment changes with normal turnover as old, worn-out equipment is replaced and new buildings are outfitted with newer versions of equipment that tend to be more energy-efficient. Equipment with even greater energy efficiency is expected to be available to commercial consumers in the future. Energy prices have both short-term and long-term effects on commercial energy use. Fuel prices influence energy demand in the short run by affecting the use of installed equipment and in the long run by affecting the stock of installed equipment.

Legislated efficiency standards also affect energy use, by imposing a minimum level of efficiency for purchases of several types of equipment used in the commercial sector. Two mandates currently affect commercial appliances: the National Energy Policy Act of 1992 (P.L. 102-486, Title II, Subtitle C, Section 342), which specifically targets larger-scale commercial equipment and fluorescent lighting, and the National Appliance Energy Conservation Amendments (NAECA), which affect commercial buildings that install smaller residential-style equipment. Examples include standards for heat pumps, air conditioning units, boilers, furnaces, water heating equipment, and fluorescent lighting.

Effects of Technology Availability and Choice

The degree to which energy-efficient equipment can affect energy consumption, and in turn carbon emissions, in the commercial sector is limited by the level of efficiency available to commercial consumers and the rate at which more efficient equipment is purchased. Technologies for all the major end uses (lighting, heating, cooling, water heating, etc.) are defined by their installed cost, operating cost, efficiency, average useful life, and first and last dates of availability. These parameters are considered, along with fuel prices at the time of purchase, in the selection of technologies that provide end-use services. Commercial consumers are not assumed to anticipate any future changes in fuel prices when choosing equipment. The commercial sector encompasses a wide variety of buildings, and not all consumers will have the same requirements and priorities when purchasing equipment. Major assumptions that take these differences in behavior into account and affect commercial technology choices are described below.

In making the tradeoffs between equipment cost and equipment efficiency, the purchase behavior of the commercial sector is represented by distributing floorspace over a variety of hurdle rates. Rates of return on investments in energy efficiency (referred to in financial parlance as “internal rates of return”) are required to meet or exceed the hurdle rate. Floorspace is distributed over hurdle rates that range from a low of about 18 percent to rates high enough to cause choices to be made solely by minimizing the costs of installed equipment (i.e., future potential energy cost savings are ignored at the highest hurdle rate).³⁶ The distribution of hurdle rates used in all the cases for this analysis is not static: as fuel prices increase, the nonfinancial portion of each hurdle rate in the distribution decreases.³⁷

For a proportion of commercial consumers, it is assumed that newly purchased equipment will use the same fuel as the equipment it replaces. This proportion varies by building type and by type of purchase—whether it is for new construction, to replace worn-out equipment, or to replace equipment that is economically obsolete. Purchases for new construction are assumed to show the greatest flexibility of fuel choice, while purchases for replacement equipment have the least flexibility. For example, when space heating equipment in large office buildings is replaced, 8 percent of the purchasers are assumed to consider all available equipment using any fuel or technology, while 92 percent select only from technologies that use the same fuel as the equipment being replaced. The proportions used are consistent with data from EIA’s Commercial Buildings Energy Consumption Survey and from published literature.³⁸ Considerations such as owner versus developer financing, past experience, ease of installation, and fuel availability all play a role in fuel choice. This assumption also accounts for some of the factors that influence technology choices but cannot be measured. For example, a hospital adding a new wing has an economic incentive to use the same fuel that is used in the existing building.

The availability and costs of advanced technologies affect the degree to which they can contribute to future energy savings and carbon emission reductions. Many efficient technologies currently available to commercial consumers could significantly reduce energy consumption; however, their high purchase costs and the current low level of fuel prices have limited their penetration to date. As more advanced technologies mature over time, their costs are expected to decline (compact fluorescent lighting is an example). New technologies, beyond those available today, may also enter the market in the future. For example, the high technology sensitivity case, described below, assumes that by 2005 a triple-effect absorption natural-gas-fired commercial chiller will be widely available, and that “typical” heat pump water heaters will cost 18 percent less than assumed in the reference case.

The combination of technology and behavior assumptions determines the commercial-sector price elasticity for each of the major fuels—that is, how commercial-sector demand projections are affected by changes in energy prices. Specifically, the commercial-sector price elasticity for a particular fuel is the percent change in demand for that fuel in response to a 1-percent change in its delivered price. In the reference case, short-run price elasticities for fuel use in the commercial sector are -0.34 for electricity, -0.39 for natural gas, and -0.39 for distillate fuel oil. Long-term price elasticities in the reference case are higher, reflecting changes in both the use of existing equipment and the adoption rates for more efficient equipment: -0.36 for electricity, -0.44 for natural gas, and -0.45 for distillate fuel oil.³⁹ The similarity of the short-run and long-run elasticities for electricity has two main causes. First, electric equipment becomes more efficient even with the reference case assumptions, thus reducing opportunities for further reductions when prices are higher. For example, electric lighting efficiency in the reference case increases on average by 0.6 percent per year from 1996 through 2020. Electric space cooling and ventilation improve on average by 1.1 and 0.7 percent per year, respectively, over the same period. Second, miscellaneous electric end uses capture a growing share of commercial electricity consumption and exhibit the same response in the long run as in the short run. Building codes, equipment standards, and improvements in technology costs and performance contribute to reduced energy intensity in the commercial sector (i.e., annual energy consumption per square foot of floorspace) even in the absence of price changes. With constant real energy prices, energy intensity declines on average by 0.1 percent per year through 2010.

Carbon Reduction Cases

In the 1990-3% case, commercial sector energy use in 2010 is projected to be below the 1996 level (Figure 38), and carbon emissions attributable to the commercial sector are projected to be 29 percent below their 1990 levels (Figure 39), despite 1-percent annual growth in commercial floorspace from 1996 to 2010. Projected fuel prices in 2010 in the 1990-3% case are more than twice as high as the reference case projection, and they are higher in real terms than they have been in any year since 1980 (Figure 40). As a result, energy consumption in 2010 is 22 percent lower in the 1990-3% case than in the reference case, and expenditures for energy purchases are 52 percent higher. Energy consumption starts to increase again later in the 1990-3% case, as demand reductions lead to a decline in fuel prices. Energy consumption in the 1990+24% and 1990+9% cases does not rebound as much, because prices do not fall at the rate seen in the 1990-3% case.

Floorspace expansion in the commercial sector will lead to growth in energy consumption if other factors remain the same. Figure 41 removes the effects of floorspace growth by presenting commercial energy intensity in terms of delivered energy consumption per square foot of commercial floorspace. Although total energy consumption continued to increase when energy prices were rising from 1970 through 1982, commercial energy intensity declined by about 12 percent. Delivered energy intensity in the reference case is projected to remain essentially flat throughout the forecast. Projected commercial sector growth is offset by the availability and continued development of energy-efficient technologies, existing equipment efficiency standards, and voluntary programs such as those for the Climate Change Action Plan. In the carbon reduction cases, with higher energy prices, the energy intensities projected for 2010 are below the 1996 level. The projections for commercial delivered energy intensity in 2010 in the 1990+24%, 1990+9%, and 1990-3% cases are 5 percent, 13 percent, and 21 percent below the reference case projection, respectively.

When energy prices rise, consumers are expected to reduce energy use by purchasing more efficient equipment and by altering the way they use energy-consuming equipment. In addition to buying more efficient boilers and chillers, commercial customers in the 1990-3% case are expected to choose more heat pumps, heat pump water heaters, and efficient lighting technologies than they would in the reference case (Table 6). The same trends toward purchasing efficient technologies and monitoring energy use are projected in the 1990+9% case and in the 1990+24% case, but to a lesser degree than projected for the 1990-3% case.

The adoption of more efficient technologies reflects the reaction to rising fuel prices and a change in the way commercial consumers are expected to look at purchase decisions involving energy efficiency if carbon emissions are severely limited. Most commercial consumers give some consideration to fuel costs when buying equipment. A significant increase in fuel prices is expected to cause consumers to give energy costs greater weight in the purchase decision, by seeking out more information about energy efficiency options and by accepting a longer time period to recoup the additional initial investment typically required to obtain greater energy efficiency. While taking client comfort and employees’ working conditions into consideration, commercial energy consumers would also be expected to turn thermostats down (up) a few degrees during cooler (warmer) weather and to be more conscientious about turning off lights and office equipment not in use.

The vast majority of the projected commercial sector reductions in carbon emissions in the carbon reduction cases are related to electricity use (see Figure 39). Two factors contribute to electricity-related carbon savings: reductions in the level of carbon emitted during the generation of a given amount of electricity (as discussed in Chapter 4), and reductions in electricity consumption. The projections for delivered electricity consumption in the commercial sector in 2010 for the 1990-3% and 1990+9% cases are 19 percent and 12 percent lower, respectively, than the reference case projection (Figure 42), and the 1990+24% case is 5 percent lower.

Historically, steady growth in electricity consumption has been seen in the commercial sector during times of both rising and falling prices. The growth has resulted in part from expansion in the sector and, more importantly, from an increasing number of end uses for electricity (i.e., increasing electricity intensity). The reference case projects further growth in electricity use between 1996 and 2010. In the 1990-3% case, however, the electricity consumption projected for 2010 falls to 1996 levels. The growth in commercial sector electricity intensity is projected to slow in the reference case for the same reasons that apply to energy intensity, and further reductions are expected in the carbon reduction cases.

The projected share of total end-use energy services that each major fuel provides to the commercial sector in 2010 is fairly stable across the different carbon reduction cases, and each fuel’s share of energy consumption within specific end uses (space heating, cooling, water heating, etc.) shows little change. Electricity does increase slightly in share, however—up to 2 percentage points in 2010 in the 1990-3% and 7-percent-below-1990 (1990-7%) cases relative to the reference case.

Because the carbon prices required to meet emissions reduction targets cause a greater percentage increase in natural gas prices than electricity prices relative to those in the reference case, commercial consumers are expected to curtail their use of equipment powered by natural gas more than their use of electrical equipment. In addition, because of its critical nature, the usage pattern of existing commercial refrigeration equipment is not assumed to change in response to price changes, limiting projected reductions in electricity use for refrigeration to those caused by potential earlier retirements and purchases of more efficient equipment when prices are higher.

Finally, the fastest-growing commercial end uses, under reference case assumptions, include office equipment and miscellaneous devices powered by electricity (e.g., telecommunications equipment, medical imaging equipment, ATM machines), which are continuing to penetrate the commercial sector. Although electricity consumption for these end uses would be responsive to the price signals resulting from emissions reduction efforts, their growth still is expected to be faster than growth in the end uses that consume fossil fuels (primarily space heating and water heating).

The expected effects of carbon emission reduction efforts on the average efficiencies of equipment stocks in the commercial sector are exemplified by the projections for natural-gas-fired space heating equipment. In the reference case, the average efficiency of natural gas space heating systems in the commercial sector is projected to increase by 0.6 percent per year through 2010, and gas heating equipment purchased in 2005 is projected to be about 6.4 percent more efficient than the average system in use at that time. The 1990+24% case projects the same level of efficiency improvement and purchased efficiency. With 2010 natural gas prices expected to be near 1996 levels in this case (see Figure 40), there is little incentive for purchasers to invest additional capital in more efficient gas heating systems. In the 1990+9% case, however, the projected higher gas prices yield a projected 0.7-percent annual increase in average stock efficiency and an average efficiency for new equipment purchases in 2005 that is 7.2 percent higher than the stock average. Similarly, in the 1990-3% case, the average stock efficiency for gas heaters in the commercial sector increases by 0.8 percent per year, and new gas heating systems are 7.5 percent more efficient, on average, than the stock average in 2005. Heating systems typically are purchased only for new construction, for major renovations, or when an existing system needs to be replaced. Once in place, they typically last over 20 years. Therefore, the energy savings realized from purchases of more efficient equipment take time to accumulate.

Sensitivity Cases

Sensitivity case assumptions were developed for the 1990+9% case, to examine uncertainties about technology development in the commercial sector. Similar assumptions were developed for each of the demand sectors, and results were derived from integrated model runs requiring the entire U.S. energy system, not the commercial demand sector individually, to meet the specified emission reduction goals. Much different results might be expected if only commercial sector assumptions were modified and/or only the commercial sector was required to meet a specific emissions target, independent from other demand sectors and utilities.

The low technology sensitivity case assumes that all future equipment purchases will be made only from the equipment available to commercial consumers in 1998, and that commercial building shell efficiencies will remain at 1998 levels. Alternatively, the high technology sensitivity assumptions were developed by engineering technology experts, considering the potential impact on technology given increased research and development into more advanced technologies ⁴⁰. The high technology sensitivity case includes technologies with higher efficiencies and/or lower costs than those assumed to be available in the reference case.

The projected carbon prices and fuel prices in the different sensitivity cases (Table 7) reflect the possible impacts that changes in the level of technological progress, across all sectors, may have on the fuel costs required for the United States to meet a specific emissions level. Different actions expected in the residential, commercial, industrial, transportation, and electricity generation sectors all contribute to meeting the emissions target. The combination of these actions results in the projected carbon prices, as each sector is expected to reduce demand in a way suitable to that particular sector. expected to reduce demand in a way suitable to that particular sector.

Photovoltaics and Fuel Cells

In every carbon reduction case considered in this report, neither photovoltaics nor fuel cells are projected to gain significant market penetration, because of their high costs. With payback periods of more than 20 years, the success of these technologies seems largely dependent on reducing production costs and increasing efficiency (which would result in further cost reductions for the consumer). Federal financial assistance would also play a role in their success.

Currently, electricity from photovoltaics and fuel cells is approximately 1.4 to 5.8 times the price to consumers of electricity from utility grids. Average prices in 1998 were 79 mills per kilowatt for utility power, 112 mills for phosphoric acid fuel cells (with no cogeneration), and 461 mills for photovoltaic systems. To increase the market penetration rates of the alternative technologies, their costs would have to be more competitive.

Photovoltaic and fuel cell technologies are examined here on the basis of their potential for further market penetration in 2010 for the 1990-3% case and in sensitivity cases assuming cost reductions (30 to 50 percent), performance improvements (50 percent for fuel cells, 70 percent for photovoltaics), and Federal subsidies and credits. Payback periods are calculated for the regions where these technologies are most likely to penetrate.

The effects of various private and government-assisted financing plans, such as rolling the cost of the alternative technology into a mortgage plan, tax credits, and depreciation, are summarized in the chart below. The first pair of bars shows the projected payback periods in 2010 for the 1990-3% case with current technology performance and costs. The other projections incorporate performance improvements of 50 percent for fuel cells and 70 percent for photovoltaics, as well as the cumulative effects of various methods for reducing the payback periods. The second set of bars shows the effects of the assumed performance improvement. The third includes a 30-percent production cost reduction, the fourth includes a 50-percent cost reduction, the fifth includes the incorporation of capital costs into a mortgage plan, and the sixth includes a tax credit for photovoltaics and depreciation adjustments for businesses. It is important to note that the substantial cost reductions and improvements in efficiency (50 percent for fuel cells, 70 percent for photovoltaics) are merely arbitrary assumptions and are not calculated projections for future costs and efficiencies. These assumptions are not included in the carbon reduction cases or sensitivity cases presented in this report.

Under the most favorable assumptions shown in the graph, payback periods could be reduced to less than 1 year for fuel cells and 2 years for photovoltaics. Although penetration levels are hard to predict from payback periods, it can generally be assumed for the commercial and residential sectors that paybacks within 3 to 4 years would be needed for significant penetration. In the National Appliance Energy Conservation Act, the Federal efficiency payback standard for appliances is 3 years or less for investments to be non-burdensome to the consumer. Although some utilities may have payback periods on their plants of 20 years, building consumers are more likely to spend their money for efficient technologies elsewhere if payback periods are over 4 years. To achieve 3- to 4-year paybacks, both the current performance and the costs of these alternatives would have to be improved by the levels shown here; however, the likelihood of such substantial improvements in the next two decades is small.

Production costs for photovoltaic modules have fallen from $100 per watt to $4 per watt over the past three decades, an 11-percent annual decline, but since 1990 they have declined by an annual average of only 3.9 percent.^a To meet the cost reduction assumptions in these scenarios, the production costs for photovoltaic cells and modules would have to decline at an average annual rate of 5.6 percent through 2010.

The energy production efficiency of photovoltaic modules has also improved, to approximately 12 percent today from 9 percent in 1980.^b Reaching the goal of 70 percent improvement in performance, as assumed for this sensitivity analysis, would require an efficiency level of 20 percent in 2010. Since 1980, the rate of improvement in performance for photovoltaics has been less than 2 percent annually, whereas a 4.3-percent annual rate would be needed to achieve a 70-percent improvement by 2010, and that improvement would also have to be accompanied by cost improvements to achieve a 3- to 4-year payback period. Fuel cells have been on the market for only a short time, and historical information is not available. Neither technology appears to be on course to accomplish such a goal during the period of this analysis, however, and thus extensive market penetration is not probable for either photovoltaics or fuel cells.

^aEnergy Information Administration, Solar Collector Manufacturing Activity 1991, DOE/EIA-0174(91), p. 18; and P. Maycock, “Photovoltaic Energy Conversion: PV Technology, Cost, Products, Markets, and Systems—Forecast 2010,” ASES Conference (Albuquerque, NM, June 1998).

^bPaul Maycock, PV Energy, personal communication, August 1998.

Among the technology cases the highest carbon prices, and thus the highest fuel prices, in 2010 are projected in the 1990+9% low technology sensitivity case. Due to the lack of technological progress in all sectors, higher fuel prices are required to achieve the demand reductions needed to reach the emissions target. The projected price of fuel to the commercial sector is 20 percent higher in the low technology case than in the 1990+9% case, resulting in 7 percent less commercial energy use. Commercial expenditures for fuel are also expected to be highest under these conditions (Figure 43). Fewer options for increased efficiency limit the potential for energy savings in the low technology case. The average efficiency of the equipment stock in this case continues to improve as normal turnover takes place and older equipment is replaced, but the most energy-efficient equipment available for purchase in 2010 or 2020 is what is available today (Table 8).

In the 1990+9% high technology sensitivity case, advanced technologies are expected to penetrate the market in all sectors over time as normal stock turnover results in the replacement of older, less efficient equipment. Projected technological advances throughout the energy market result in a carbon price in 2010 that is 25 percent lower than that projected in the 1990+9% case (see Table 7). In turn, the expected commercial fuel price in 2010 is 12 percent lower than in the 1990+9% case, resulting in 4 percent more energy consumption. Even though more advanced technologies are available in the high technology case, with less price incentive, commercial consumers are not as likely to purchase more costly equipment. For technologies such as commercial natural gas water heaters, where high technology assumptions specify lower costs in 2015 for the most efficient equipment, as compared with the reference case technology assumptions, more consumers are expected to adopt the efficient technology (see Table 8). The projected reduction in energy demand in other sectors causes commercial fuel prices to decline in the later years of the forecast, lowering commercial expenditures for fuel (Figure 43).