Effect of Energy Efficiency Standards on Natural Gas Prices

A primary justification for the establishment of energy efficiency standards for home appliances is the existence of information deficiencies and externalities in the market for appliances. For example, when a long-term homeowner purchases a new gas-fired water heater, she will maximize the value of her purchase by comparing the life-cycle cost of ownership of available units, including both total installed cost - purchase price plus installation costs - and operating cost in the calculus. Choice of the appliance with the lowest life-cycle costs leads to the most economically efficient balance between capital cost and fuel cost. However, if the purchaser's expected period of ownership is shorter than the useful life of the appliance, or the purchaser does not pay for the fuel used by the appliance, as is often the case with rental property, fuel cost will be external to her costs, biasing her decision toward spending less on fuel efficiency and resulting in the purchase of an appliance with greater than optimal fuel usage. By imposing an efficiency standard on appliances, less efficient appliances are made unavailable, precluding less efficient purchases and reducing fuel usage. The reduction in fuel demanded by residential users affects the total demand for such fuels as natural gas, for example. Reduced demand implies that residential customers are willing to purchase less gas at each price level. That is, the demand curve, labeled D{sub 0} in Figure 1, shifts to the left to D{sub 1}. If there is no change in the supply function, the supply curve will intersect the demand curve at a lower price. Residential demand is only one component of the total demand for natural gas. It is possible that total demand will decline very little if demand in other sectors increases substantially in response to a decline in the price. If demand does decrease, modeling studies generally confirm the intuition that reductions in demand for natural gas will result in reductions in its price as seen at the wellhead (Wiser 2007). The magnitude of the effect on price relative to the demand reduction, and the mechanism through which it occurs, is less well established. This report attempts to quantify the potential effects of reduced demand for natural gas in the residential sector, in response to the implementation of an energy efficiency standard for water heaters

A Framework for Comparative Assessments of Energy Efficiency Policy Measures

When policy makers propose new policies, there is a need to assess the costs and benefits of the proposed policy measures, to compare them to existing and alternative policies, and to rank them according to their effectiveness. In the case of equipment energy efficiency regulations, comparing the effects of a range of alternative policy measures requires evaluating their effects on consumers’ budgets, on national energy consumption and economics, and on the environment. Such an approach should be able to represent in a single framework the particularities of each policy measure and provide comparable results. This report presents an integrated methodological framework to assess prospectively the energy, economic, and environmental impacts of energy efficiency policy measures. The framework builds on the premise that the comparative assessment of energy efficiency policy measures should (a) rely on a common set of primary data and parameters, (b) follow a single functional approach to estimate the energy, economic, and emissions savings resulting from each assessed measure, and (c) present results through a set of comparable indicators. This framework elaborates on models that the U.S. Department of Energy (DOE) has used in support of its rulemakings on mandatory energy efficiency standards. In addition to a rigorous analysis of the impacts of mandatory standards, DOE compares the projected results of alternative policy measures to those projected to be achieved by the standards. The framework extends such an approach to provide a broad, generic methodology, with no geographic or sectoral limitations, that is useful for evaluating any type of equipment energy efficiency market intervention. The report concludes with a demonstration of how to use the framework to compare the impacts estimated for twelve policy measures focusing on increasing the energy efficiency of gas furnaces in the United States

Simulating a Nationally Representative Housing Sample Using EnergyPlus

This report presents a new simulation tool under development at Lawrence Berkeley National Laboratory (LBNL). This tool uses EnergyPlus to simulate each single-family home in the Residential Energy Consumption Survey (RECS), and generates a calibrated, nationally representative set of simulated homes whose energy use is statistically indistinguishable from the energy use of the single-family homes in the RECS sample. This research builds upon earlier work by Ritchard et al. for the Gas Research Institute and Huang et al. for LBNL. A representative national sample allows us to evaluate the variance in energy use between individual homes, regions, or other subsamples; using this tool, we can also evaluate how that variance affects the impacts of potential policies. The RECS contains information regarding the construction and location of each sampled home, as well as its appliances and other energy-using equipment. We combined this data with the home simulation prototypes developed by Huang et al. to simulate homes that match the RECS sample wherever possible. Where data was not available, we used distributions, calibrated using the RECS energy use data. Each home was assigned a best-fit location for the purposes of weather and some construction characteristics. RECS provides some detail on the type and age of heating, ventilation, and air-conditioning (HVAC) equipment in each home; we developed EnergyPlus models capable of reproducing the variety of technologies and efficiencies represented in the national sample. This includes electric, gas, and oil furnaces, central and window air conditioners, central heat pumps, and baseboard heaters. We also developed a model of duct system performance, based on in-home measurements, and integrated this with fan performance to capture the energy use of single- and variable-speed furnace fans, as well as the interaction of duct and fan performance with the efficiency of heating and cooling equipment. Comparison with RECS revealed that EnergyPlus did not capture the heating-side behavior of heat pumps particularly accurately, and that our simple oil furnace and boiler models needed significant recalibration to fit with RECS. Simulating the full RECS sample on a single computer would take many hours, so we used the 'cloud computing' services provided by Amazon.com to simulate dozens of homes at once. This enabled us to simulate the full RECS sample, including multiple versions of each home to evaluate the impact of marginal changes, in less than 3 hours. Once the tool was calibrated, we were able to address several policy questions. We made a simple measurement of the heat replacement effect and showed that the net effect of heat replacement on primary energy use is likely to be less than 5%, relative to appliance-only measures of energy savings. Fuel switching could be significant, however. We also evaluated the national and regional impacts of a variety of 'overnight' changes in building characteristics or occupant behavior, including lighting, home insulation and sealing, HVAC system efficiency, and thermostat settings. For example, our model shows that the combination of increased home insulation and better sealed building shells could reduce residential natural gas use by 34.5% and electricity use by 6.5%, and a 1 degree rise in summer thermostat settings could save 2.1% of home electricity use. These results vary by region, and we present results for each U.S. Census division. We conclude by offering proposals for future work to improve the tool. Some proposed future work includes: comparing the simulated energy use data with the monthly RECS bill data; better capturing the variation in behavior between households, especially as it relates to occupancy and schedules; improving the characterization of recent construction and its regional variation; and extending the general framework of this simulation tool to capture multifamily housing units, such as apartment buildings

Variability in Energy Factor Test Results for Residential Electric Water Heaters

Recent modifications to the minimum energy efficiency requirements for residential water heaters have spurred an investigation into the variability in testing high-efficiency electric water heaters. While initial inter-laboratory comparisons showed excellent agreement between test results from different labs, subsequent inter-laboratory comparisons show differences between measured energy factors of up to 0.040. To determine the source of these differences, analyses of various parts of the test procedure are performed. For one case studied, the uncertainty in test results can be as high as +-0.028 if instrument accuracies reach the minimum level allowed in the test procedure. Other areas of the test procedure where variability is introduced are the optional use of pre-draws, the location of the lower tank temperature-measuring device, the use of insulation on tank fittings, and the use of a warm-up period before the simulated-use test commences. The implications of these issues on test results are provided

Automated Demand Response Opportunities in Wastewater Treatment Facilities

Wastewater treatment is an energy intensive process which, together with water treatment, comprises about three percent of U.S. annual energy use. Yet, since wastewater treatment facilities are often peripheral to major electricity-using industries, they are frequently an overlooked area for automated demand response opportunities. Demand response is a set of actions taken to reduce electric loads when contingencies, such as emergencies or congestion, occur that threaten supply-demand balance, and/or market conditions occur that raise electric supply costs. Demand response programs are designed to improve the reliability of the electric grid and to lower the use of electricity during peak times to reduce the total system costs. Open automated demand response is a set of continuous, open communication signals and systems provided over the Internet to allow facilities to automate their demand response activities without the need for manual actions. Automated demand response strategies can be implemented as an enhanced use of upgraded equipment and facility control strategies installed as energy efficiency measures. Conversely, installation of controls to support automated demand response may result in improved energy efficiency through real-time access to operational data. This paper argues that the implementation of energy efficiency opportunities in wastewater treatment facilities creates a base for achieving successful demand reductions. This paper characterizes energy use and the state of demand response readiness in wastewater treatment facilities and outlines automated demand response opportunities

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California

This report summarizes the Lawrence Berkeley National Laboratory's research to date in characterizing energy efficiency and open automated demand response opportunities for industrial refrigerated warehouses in California. The report describes refrigerated warehouses characteristics, energy use and demand, and control systems. It also discusses energy efficiency and open automated demand response opportunities and provides analysis results from three demand response studies. In addition, several energy efficiency, load management, and demand response case studies are provided for refrigerated warehouses. This study shows that refrigerated warehouses can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for open automated demand response (OpenADR) at little additional cost. These improved controls may prepare facilities to be more receptive to OpenADR due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data

Opportunities for Open Automated Demand Response in Wastewater Treatment Facilities in California - Phase II Report. San Luis Rey Wastewater Treatment Plant Case Study

This case study enhances the understanding of open automated demand response opportunities in municipal wastewater treatment facilities. The report summarizes the findings of a 100 day submetering project at the San Luis Rey Wastewater Treatment Plant, a municipal wastewater treatment facility in Oceanside, California. The report reveals that key energy-intensive equipment such as pumps and centrifuges can be targeted for large load reductions. Demand response tests on the effluent pumps resulted a 300 kW load reduction and tests on centrifuges resulted in a 40 kW load reduction. Although tests on the facility?s blowers resulted in peak period load reductions of 78 kW sharp, short-lived increases in the turbidity of the wastewater effluent were experienced within 24 hours of the test. The results of these tests, which were conducted on blowers without variable speed drive capability, would not be acceptable and warrant further study. This study finds that wastewater treatment facilities have significant open automated demand response potential. However, limiting factors to implementing demand response are the reaction of effluent turbidity to reduced aeration load, along with the cogeneration capabilities of municipal facilities, including existing power purchase agreements and utility receptiveness to purchasing electricity from cogeneration facilities

Furnace Blower Electricity: National and Regional Savings Potential

Currently, total electricity consumption of furnaces is unregulated, tested at laboratory conditions using the DOE test procedure, and is reported in the GAMA directory as varying from 76 kWh/year to 1,953 kWh/year. Furnace blowers account for about 80percent of the total furnace electricity consumption and are primarily used to distribute warm air throughout the home during furnace operation as well as distribute cold air during air conditioning operation. Yet the furnace test procedure does not provide a means to calculate the electricity consumption during cooling operation or standby, which account for a large fraction of the total electricity consumption. Furthermore, blower electricity consumption is strongly affected by static pressure. Field data shows that static pressure in the house distribution ducts varies widely and that the static pressure used in the test procedure as well as the calculated fan power is not representative of actual field installations. Therefore, accurate determination of the blower electricity consumption is important to address electricity consumption of furnaces and air conditioners. This paper compares the potential regional and national energy savings of two-stage brushless permanent magnet (BPM) blower motors (the blower design option with the most potential savings that is currently available in the market) to single-stage permanent split capacitor (PSC) blower motors (the most common blower design option). Computer models were used to generate the heating and cooling loads for typical homes in 16 different climates which represent houses throughout the United States. The results show that the potential savings of using BPM motors vary by region and house characteristics, and are very strongly tied to improving house distribution ducts. Savings decrease dramatically with increased duct pressure. Cold climate locations will see savings even in the high static pressure duct situations, while warm climate locations will see less savings overall and negative savings in the high static pressure duct situations. Moderate climate locations will see little or no savings

Economics of residential gas furnaces and water heaters in United States new construction market

New single-family home construction represents a significant and important market for the introduction of energy-efficient gas-fired space heating and water-heating equipment. In the new construction market, the choice of furnace and water-heater type is primarily driven by first cost considerations and the availability of power vent and condensing water heaters. Few analysis have been performed to assess the economic impacts of the different combinations of space and water-heating equipment. Thus, equipment is often installed without taking into consideration the potential economic and energy savings of installing space and water-heating equipment combinations. In this study, we use a life-cycle cost analysis that accounts for uncertainty and variability of the analysis inputs to assess the economic benefits of gas furnace and water-heater design combinations. This study accounts not only for the equipment cost but also for the cost of installing, maintaining, repairing, and operating the equipment over its lifetime. Overall, this study, which is focused on US single-family new construction households that install gas furnaces and storage water heaters, finds that installing a condensing or power-vent water heater together with condensing furnace is the most cost-effective option for the majority of these houses. Furthermore, the findings suggest that the new construction residential market could be a target market for the large-scale introduction of a combination of condensing or power-vent water heaters with condensing furnaces