TODAY’S STUDY: THE FUTURE OF RENEWABLE ELECTRICITY, PT. 3 (END USE ELECTRICITY)

Volume 3: End-Use Electricity Demand

June 2012 (National Renewable Energy Laboratory)

Introduction

The Renewable Electricity Futures Study (RE Futures) is an initial investigation of the extent to which renewable energy supply can meet the electricity demands of the contiguous United States1 over the next several decades. This study includes geographic and electric system operation resolution that is unprecedented for long-term studies of the U.S. electric sector.

The RE Futures study is documented in four volumes: Volume 1 describes the analysis approach and models along with the key results and insights from the analysis; Volume 2 documents in detail the renewable generation and storage technologies included in the study; Volume 4 documents the operational and institutional challenges of integrating high levels of renewable energy into the electric grid; this Volume—Volume 3—details the end-use electricity demand and efficiency assumptions.

The projection of electricity demand is an important consideration in determining the extent to which a predominantly renewable electricity future is feasible. Any scenario regarding future electricity use must consider many factors, including technological, sociological, demographic, political, and economic changes (e.g., the introduction of new energy-using devices; gains in energy efficiency and process improvements; changes in energy prices, income, and user behavior; population growth; and the potential for carbon mitigation).

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In projecting electricity use, the primary historical drivers for electricity demand (population growth and economic growth) are taken into account along with other emerging trends, including the green building and supply chain1 movements, carbon mitigation, policies and legislation dealing with codes and standards, research and development in energy efficiency, and foreign competition for manufacturing. For the RE Futures, two demand projections were developed to represent probable higher and lower electricity trajectories—hereafter referred to as the High-Demand Baseline and the Low-Demand Baseline. The two electricity demand trajectories used in RE Futures rely on the same assumptions for population and economic growth, so the differences stem from the assumptions regarding other trends.

The emerging trends noted above that lead to increased efficiency motivate the Low-Demand Baseline. Based on these, a scenario was developed in which there is an approximately 30% reduction in overall electricity intensity2 within the buildings sector, a 50% reduction in industrial electricity intensity, and electrification of approximately 40% of the light-duty vehicle stock by 2050.

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5

General Assumptions

Although there is a growing body of literature dedicated to factors affecting energy demand, including behavioral influences, climate change, and new technologies and materials, the explicit inclusion of the potential impacts arising from these influences is beyond the scope of RE Futures. RE Futures relied on readily available data and projections to the extent possible, and attempted to stay within reasonable bounds established by recent literature. RE Futures was further constrained by the modeling requirement for hourly load projections through the study period. This required the conversion of the estimated projections of electricity consumption into regional hourly load profiles. Although studies projecting potential energy consumption futures are plentiful, studies that tie those consumption futures to hourly loads are not readily available.

The basis for the scenarios presented was predominantly drawn from EIA’s AEO for 2009 (industrial sector) and 2010 (buildings sector), which assumed that the major long-term drivers of energy demand—Gross Domestic Product and population—grow at 2.4%/yr and 0.9%/yr, respectively, over the period 2008–2035.3

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The High-Demand Baseline is a business-as-usual scenario that assumes trends for the residential, commercial, and industrial sectors as forecast to 2030 by the Energy Information Administration (EIA) in its Annual Energy Outlook (AEO) (EIA 2009d). Because AEO 2009 contained only a forecast through 2030, RE Futures extended the AEO trends out to 2050. Under this scenario, the overall electricity intensity within the buildings sector remains relatively unchanged from 2010 to 2050, and the industrial sector electricity intensity declines by approximately 35% during the RE Futures period (2010–2050).

The fuel prices assumed by the AEO were also taken into consideration in developing the scenarios because increasing natural gas prices might lead consumers to change out their natural gas heating equipment to equipment fueled by electricity, for example; however, given recent prospects to exploit shale gas deposits, the AEO forecast for natural gas prices was believed to be too high. As such, RE Futures did not assume more fuel switching from natural gas to electric devices for space and water heating than was already assumed in the AEO 2010 Reference Case (EIA 2010). Given the extreme difficulty of capturing carbon emissions arising from distributed use of fossil energy in the buildings sector, however, use of decarbonized electricity to provide space and water heating may be an important means for reducing carbon emissions in the future. Recent work for the European Union (European Climate Foundation 2010) projected greater electrification within the buildings sector; as a consequence, forecasted efficiency gains were offset by new electrical demands from transportation and space and water heating. While the total electrical demand for RE Futures would be represented by the High-Demand Baseline in such a case, the underlying load shapes would not capture the resulting hourly and seasonal changes.

Electricity prices also have an impact on the demand for electricity. However, because the demand profiles are provided as exogenous inputs to the models used in RE Futures, the potential impacts on demand due to changes in electricity prices caused by the various scenarios were not considered in developing the demand projections. The interactions that impact electricity prices between electricity supply and demand are complex and beyond the scope of RE Futures. The efficiency gains are assumed to be cost-effective using today’s electricity prices and the current AEO forecasts for electricity prices.

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Within the commercial sector, two additional trends underlie the AEO projections. First, the growth in disposable income increases the demand for services that depend on computers and other electronic equipment. Also, the growing share of the population over age 65 increases the demand for health care and assisted-living facilities and the demand for electricity to power medical and monitoring equipment at those facilities. Trends in the residential sector include population migration into the South and the West;4 the conversion of older homes from room air conditioning to central air conditioning; and the growth in the use of “other” appliances, including large-screen televisions and computers. Within the industrial sector, the AEO projects that energy-intensive manufacturing industries will show slow growth due to increased foreign competition. Additionally, an increase in the use of biofuels in the transportation sector is expected to lead to an increase in the conversion of biomass to fuels such as ethanol, diesel, and jet fuel. This process creates heat, which can be used for industrial on-site generation…

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Potential Impact of Carbon Mitigation Measures and Climate Change on Electricity Demand

There is currently much discussion about climate change, emissions, and carbon mitigation measures. Potential policies, legislation, and regulation can logically be expected to have an impact on the way in which energy is generated, delivered, and used, whether by specific controls or through pricing incentives or disincentives. The same drivers that might push the United States toward more renewable generation of electricity would also be expected to lead to increased energy efficiency—that is, a drive to use less energy to yield the same level of service. These drivers act in opposition to other trends, such as population growth and the development of new electricity-using devices. Climate change influences another aspect of the energy use picture because heating and cooling loads are highly dependent upon outside temperature.

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Although a carbon mitigation policy was not explicitly assumed for RE Futures, implementation of a carbon mitigation policy would have an impact on electricity demand. Depending on how such a policy might be implemented, one potential outcome is higher prices for fossil energy, which could lead to fuel switching in end uses such as space and water heating. The Electric Power Research Institute (EPRI) (2009), the National Academy of Sciences (NAS et al. 2009), and the Union of Concerned Scientists (Cleetus et al. 2009) all use reference cases from recent editions of EIA’s AEO. The extent to which fuel switching occurs in these projections is largely due to how EIA models fuel choice in its existing residential and commercial building models. In general, some amount of fuel switching (in the sense of the predicted fuel shares of space and water heating in new buildings) occurs as a function of projected fuel prices and the menu of available energy efficiency technologies for these end uses. With regard to the energy efficiency scenarios undertaken by these studies, none of them makes any explicit assumptions about any fuel switching that would alter the future evolution of electricity growth in buildings.5 One of the results of a greater percentage of renewable generation is that the generation sector would reduce its use of natural gas in the longer term. Currently, electricity generation is responsible for approximately one-third of the U.S. demand for natural gas;6 reduced demand could potentially lower natural gas prices, countering to some extent the price increases brought about by carbon policies.

Just as climate mitigation policies may impact electricity demand, climate change would also be expected to impact both energy supply and energy demand, and numerous studies have been conducted to determine the potential impacts of climate change on the U.S. (and world) energy picture (e.g., Scott and Huang 2007; Huang 2006; Mansur et al. 2005; Scott et al. 2005). Although these studies present varying estimates of the impact on energy demand within the United States,7 they are in general agreement that overall heating consumption is expected to decrease due to climate change (ranging from -3% to -35% by 2050), while overall cooling consumption could increase, ranging from 4% to 90% by 2050 (see Appendix G for comparisons). For RE Futures, climate change was not explicitly addressed because the overall impacts are subject to a number of assumptions, including temperature change and time frame, that are beyond the scope of RE Futures. Generally, if climate change and climate mitigation policies were to be taken into account, the demand profiles presented here would most likely be underestimating cooling and overestimating heating (although the lower heating demand may cause more switching into electricity, e.g. heat pumps that would offset some of the direct effects of higher temperatures).

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Resulting Scenarios

RE Futures selected two energy demand scenarios to represent reasonable bounds for the electricity generation requirements through 2050. These two scenarios represent a “higher” level of demand (the High-Demand Baseline) and a “lower” level of demand (the Low-Demand Baseline). Developing scenarios of energy use 40 years into the future is challenging, and the analysis is further complicated by the requirement for detailed hourly system load shapes by region, which are needed for the modeling effort.

The High-Demand Baseline represents a business-as-usual case that assumed that trends within the residential, commercial, industrial, and transportation sectors recently forecast by the EIA (EIA 2009d and EIA 2010) to 2030 continue through 2050.8 This scenario assumed no radical changes in available technologies or consumer behavior, although current technologies will evolve in terms of cost and efficiency. No new regulations or laws not already enacted are included in an AEO Reference Case, and beyond its 2030 horizon, a simple extrapolation is made to 2050. The AEO Reference Case was chosen to represent a higher demand trajectory because it does not include planned equipment and appliance standards or proposed energy code changes, which are expected to lower demand.

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The Low-Demand Baseline assumed a moderately high level of energy efficiency within the buildings and industrial sectors. The Low-Demand Baseline assumed that approximately 40% of the light-duty vehicle stock becomes electrified by 2050. In the buildings sector, the efficiency improvements necessary to achieve ultra-high-efficiency buildings are estimated,9 while in the industrial sector, estimated responses to carbon restrictions, based on the Waxman-Markey cap and trade provisions, are applied.

The electricity demand forecasts for buildings, industry, and transportation represent sales trajectories. Transmission and distribution losses are not considered as part of these on-site electricity projections. The electricity sector is expected to deliver these energy quantities according to the timing and distribution specified by the corresponding load shapes used in the models.

Figure 15-1 illustrates the resulting demand trajectory for the Low-Demand and High-Demand Baselines through 2050. For comparison, the EIA analysis (EIA 2009b)10 of the American Clean Energy and Security Act of 2009 (the Waxman-Markey Climate Bill from 2009)11 is included, using the 2025–2030 trend to extend the analysis to 2050.

Figure 15-2 illustrates the electricity consumption by sector for the High-Demand Baseline and the Low-Demand Baseline. For context, Figure 15-3 contains the historical energy use by sector.

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Unlike the renewable technologies explored in RE Futures, the reductions in consumption have been generated without explicitly considering the investment needed to realize these gains. Terms such as cost-effective or cost-competitive are often used in discussing energy efficiency measures. These generally mean that the efficiency measures cost less or about the same as their less efficient counterparts once the various costs (e.g., energy, operation and maintenance, capital) over the lifetime of the measure are considered. Although these investment costs are not considered here, findings from other studies are presented to illustrate the approximate cost of efficiency gains to provide some perspective.

The National Academy of Sciences (NAS et al. 2009) reported conservation supply curves for energy efficiency in the buildings sector that were originally developed by Lawrence Berkeley National Laboratory (Brown et al. 2008). These supply curves indicated that energy savings of 30%–35% could be achieved over Brown et al.’s reported reference case at a cost less than the 2007 retail cost of energy. For electricity, the conserved cost of energy was found to range from less than 1 cent per kWh to about 8 cents per kWh, with an average conserved cost of energy of 2.7 cents per kWh. Brown et al. (2008) calculated that the cumulative capital investment13 required between 2010 and 2030 to achieve their level of electricity savings14 was approximately $299 billion.15 Combined with average annual electricity bill savings of $128 billion in 2030, electricity efficiency measures, on average, had a payback of 2.3 years. Additionally, NAS et al. (2009) reported that energy savings of 14%–22% could be cost-effectively achieved by 2020 within the industrial sector. Within the National Academy of Sciences study, cost-effectiveness was defined as an internal rate of return of at least 10% or exceeding a company’s cost of capital by that company’s defined risk premium; however, no conserved cost of energy was specifically reported for the industrial sector.

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In another study, McKinsey and Company (Granade et al. 2009) calculated the cost-effective energy efficiency potential in the residential, commercial, and industrial sectors.16 Granade et al. (2009) calculated the present value of investment costs and annual energy savings for each sector, as well as a set of sub-sectors. Table 15-2 contains the simple paybacks calculated for selected categories.

Another cost estimate can be drawn from Lazard (2009), which reports a levelized cost of energy for energy efficiency measures to range from 0 cents/kWh to 5 cents/kWh, based on utility costs as reported in the joint U.S. Environmental Protection Agency and U.S. Department of Energy (DOE) National Action Plan for Energy Efficiency Report (DOE/ 2006).

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Conclusion

The introduction of PEVs creates opportunities for the reduction of petroleum and the creation of new flexible load that can be integrated in utility operations with a high penetration of renewables to achieve a long-term strategy of creating a more sustainable transportation system. This work developed energy system load characteristic forecasts on a regional basis during the study period for the PEV market penetration scenario to be used in RE Futures. The work builds upon past travel survey data analyses, regional population forecasts, and assumptions regarding incentivization of charge management scenarios. A single scenario was developed, assuming a high penetration of PEVs. This scenario mirrors trends in the historical hybrid electric vehicle market stock to date. Three PEV charge scenarios were considered, including No Utility Control, Opportunity, and Valley Fill/Managed. The energy needed in the Valley Fill/Managed scenario was assumed to be flexible in terms of when it needs to be delivered throughout the day and thus provides the utility with a flexible load that can be managed to improve renewable generation asset utilization. According to the scenario, by 2050, 45% of the total vehicle energy demand of 350 TWh is under managed control while the remaining 55% is a fixed load to be planned for and met by utility assets. The hourly load profile of the fixed transportation energy demand also shifted over the time period from mainly No Utility Control toward Opportunity charging. RE Futures is the first study to assume that a variety of vehicle load shapes will exist and may transition over time, resulting in a unique fixed load and functional flexible load for integration into utility operational planning tools.

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