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DOE OSTI2017

The International Database of Efficient Appliances (IDEA): A new tool to support appliance energy-efficiency deployment

Appliance energy-efficiency programs are a central component of many countries’ energy-policy portfolios. A major barrier to optimal implementation of these programs is lack of data to determine market baselines, assess the potential for cost-effective energy savings, and track markets over time to evaluate and verify program impacts. To address this gap, we have developed the International Database of Efficient Appliances (IDEA), a suite of software tools that automatically gathers data that is currently dispersed across various online sources and compiles it into a unified repository of information on efficiency, price, and features for a diversity of appliances and devices in markets around the world. In this article we describe the framework and functionality of IDEA, and we demonstrate its power as a resource for research and policy development related to appliance energy efficiency. Using IDEA data for refrigerators in China and India, we assess the potential for cost-effective energy savings within each market by computing robust indicators that can also be easily compared across different appliances and markets. We find that significant cost-effective savings are available on both markets. We discuss implications for the development of future energy-efficiency deployment programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Non-Intrusive Appliance Identification with Appliance-Specific Networks

The problem of noninstrusive load monitoring (NILM) is usually formulated as a single-channel blind source separation task, whose successful solution enable fast and convenient load identification and energy disaggregation. When applied at test time, NILM algorithms aim to identify the operating characteristics of individual appliances from an aggregate power measurement of the entire house. Recent advances in deep learning gave rise to many methods that mostly focus on learning a direct mapping from aggregate measurement to individual appliance power. However, these methods are not only computationally expensive, but they often suffer from overfitting and do not generalize very well. In this article, we propose a novel NILM method that leverages advances in statistical learning that have not been properly applied in this domain before. The proposed method consists of three stages: first, a Bayesian nonparametric learning-based approach for appliance state extraction; second, synthetic minority oversampling technique for data augmentation and mitigating the heavy imbalance in switching events; and third, appliance-specific lightweight long short-term memory networks for status classification for each appliance. Here, we adopt a “differential” input (the difference before and after the switching event) to reduce the complexity of network training and make the proposed method robust to multiappliance switching events. Experiments are conducted to demonstrate the effectiveness of the proposed method, achieving superior performance when compared to recent methods. An ablation study is conducted to demonstrate the effectiveness of each module of our method. Finally, we investigate the quality of generated synthetic samples.

42 ENGINEERING↗

DOE OSTI2012

Modeling of GE Appliances: Cost Benefit Study of Smart Appliances in Wholesale Energy, Frequency Regulation, and Spinning Reserve Markets

This report is the second in a series of three reports describing the potential of GE’s DR-enabled appliances to provide benefits to the utility grid. The first report described the modeling methodology used to represent the GE appliances in the GridLAB-D simulation environment and the estimated potential for peak demand reduction at various deployment levels. The third report will explore the technical capability of aggregated group actions to positively impact grid stability, including frequency and voltage regulation and spinning reserves, and the impacts on distribution feeder voltage regulation, including mitigation of fluctuations caused by high penetration of photovoltaic distributed generation. In this report, a series of analytical methods were presented to estimate the potential cost benefit of smart appliances while utilizing demand response. Previous work estimated the potential technical benefit (i.e., peak reduction) of smart appliances, while this report focuses on the monetary value of that participation. The effects on wholesale energy cost and possible additional revenue available by participating in frequency regulation and spinning reserve markets were explored.

appliances↗

DOE OSTI2020

Impacts of Experimentally Obtained Harmonic Spectrums of Residential Appliances on Distribution Feeder

Owing to the increased use of power electronic based appliances and energy-efficient home equipment such as modern lighting loads, the percentage of nonlinear loads has increased in the distribution system, which can impact system performance, loss, and stability. Thus a comprehensive knowledge of their power quality and harmonic analysis is essential to improve the load models, voltage stability assessment, determination of possible interactions at harmonic frequencies, protection planning, and the effect of system impedance. This paper focuses on harmonic load flow analysis for multiple residential load types to determine the expected impacts on an modeled distribution secondary. For this study, the household appliances include lighting, power electronic, resistive, and motor loads with a nominal supply voltage of 120 V single-phase or 240 V split phase at a nominal frequency of 60 Hz. The harmonic spectrums, as obtained from the experimental evaluation of real loads, are used to inform the harmonic load flow for a detailed secondary network, including the distribution service transformer extracted from a real distribution feeder's model. Additionally, the impact of voltage harmonics on a three-phase test load is presented with experimental results. The harmonic data of the transformer terminal voltage, as obtained from the former load flow study, are scaled to generate the source voltage for the three-phase configuration of the grid simulator to make the test setup very similar to a typical secondary design in the U.S.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

DOE OSTI2014

Measure Guideline: Combustion Safety for Natural Draft Appliances Through Appliance Zone Isolation

This measure guideline covers how to assess and carry out the isolation of natural draft combustion appliances from the conditioned space of low-rise residential buildings. It deals with combustion appliances located either within the living space in enclosed closets or side rooms or outside the living space in an adjacent area like an attic or garage. This subset of houses does not require comprehensive combustion safety tests and simplified prescriptive procedures can be used to address safety concerns. This allows residential energy retrofit contractors inexperienced in advanced combustion safety testing to effectively address combustion safety issues and allow energy retrofits including tightening and changes to distribution and ventilation systems to proceed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Measure Guideline: Combustion Safety for Natural Draft Appliances Through Appliance Zone Isolation

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2013

The Demand Reduction Potential of Smart Appliances in U.S. Homes

The widespread deployment of demand respond (DR) enabled home appliances is expected to have significant reduction in the demand of electricity during peak hours. The work documented in this paper focuses on estimating the energy shift resulting from the installation of DR enabled smart appliances in the U.S. This estimation is based on analyzing the market for smart appliances and calculating the total energy demand that can potentially be shifted by DR control in appliances. Appliance operation is examined by considering their sub components individually to identify their energy consumptions and savings resulting from interrupting and shifting their load, e.g., by delaying the refrigerator defrost cycle. In addition to major residential appliances, residential pool pumps are also included in this study given their energy consumption profiles that make them favorable for DR applications. In the market analysis study documented in this paper, the U.S. Energy Information Administration's (EIA) Residential Energy Consumption Survey (RECS) and National Association of Home Builders (NAHB) databases are used to examine the expected life of an appliance, the number of appliances installed in homes constructed in 10 year intervals after 1940 and home owner income. Conclusions about the effectiveness of the smart appliances in reducing electrical demand have been drawn and a ranking of appliances in terms of their contribution to load shift is presented. E.g., it was concluded that DR enabled water heaters result in the maximum load shift; whereas, dishwashers have the highest user elasticity and hence the highest potential for load shifting through DR. This work is part of a larger effort to bring novel home energy management concepts and technologies to reduce energy consumption, reduce peak electricity demand, integrate renewables and storage technology, and change homeowner behavior to manage and consume less energy and potentially save consumer energy costs.

Demand Reduction↗

DOE OSTI2013

Modeling of GE Appliances: Final Presentation

The Energy Information Administration (EIA) estimates that electricity use will increase by more than 30 percent by 2035, and that residential electricity usage will increase by 23 percent. During this time, peak electricity demand is expected grow at an even greater rate, requiring significant investment in system capacity. In addition, increased penetration of intermittent renewable resources will increase system variability, requiring additional resources to mitigate the variability associated with generator output. Widespread adoption of demand response (DR) enabled appliances, thermostats, and other demand-side resources can result in significant reduction to peak electrical demand and provide potential grid stabilization benefits. The key to adoption is to provide this resource at a cost commensurate with traditional grid capabilities, and to appropriately share both the costs and the benefits between the consumer and the service provider (i.e., the utility). However, the business model for investing in demand-side resources cannot be determined without an estimation of the possible technical benefits and how those benefits translate to monetary value in current electrical market structures. GE Appliances has developed a line of appliances that will have the capability of offering several levels of demand reduction actions based on information received from the utility grid, often in the form of price or grid status. However due to a number of factors, including the number of DR-enabled appliances available at any given time, the reduction of diversity factor due to the synchronizing control signal, and the percentage of consumers who may override the utility signal, it can be difficult to predict the aggregate response of a large number of residences. The effects of these behaviors have been modeled and simulated in the Pacific Northwest National Laboratory (PNNL) developed open-source software, GridLAB-D™, including evaluation of appliance controls, improvement to current algorithms, and development of aggregate control methodologies. The results of these simulations provide an estimation of the possible technical benefits (e.g., peak load reduction) attributable to smart appliances, but do not describe the monetary value of these services. This report is the final in a series of three reports funded by U.S. Department of Energy Office of Electricity Delivery and Energy Reliability (DOE-OE) in collaboration with GE Appliances’ through a Cooperative Research and Development Agreement (CRADA) to describe the potential of GE Appliances’ DR-enabled appliances to provide benefits to the utility grid.

Demand Response↗

DOE OSTI2015

Estimating Price Elasticity using Market-Level Appliance Data

This report provides and update to and expansion upon our 2008 LBNL report “An Analysis of the Price Elasticity of Demand for Appliances,” in which we estimated an average relative price elasticity of -0.34 for major household appliances (Dale and Fujita 2008). Consumer responsiveness to price change is a key component of energy efficiency policy analysis; these policies influence consumer purchases through price both explicitly and implicitly. However, few studies address appliance demand elasticity in the U.S. market and public data sources are generally insufficient for rigorous estimation. Therefore, analysts have relied on a small set of outdated papers focused on limited appliance types, assuming long-term elasticities estimated for other durables (e.g., vehicles) decades ago are applicable to current and future appliance purchasing behavior. We aim to partially rectify this problem in the context of appliance efficiency standards by revisiting our previous analysis, utilizing data released over the last ten years and identifying additional estimates of durable goods price elasticities in the literature. Reviewing the literature, we find the following ranges of market-level price elasticities: -0.14 to -0.42 for appliances; -0.30 to -1.28 for automobiles; -0.47 to -2.55 for other durable goods. Brand price elasticities are substantially higher for these product groups, with most estimates -2.0 or more elastic. Using market-level shipments, sales value, and efficiency level data for 1989-2009, we run various iterations of a log-log regression model, arriving at a recommended range of short run appliance price elasticity between -0.4 and -0.5, with a default value of -0.45.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Estimating Residential Appliance Lifetime for Energy Efficient Policy Analysis

Accurate knowledge of appliance lifetimes helps policy makers set effective energy efficiency policy. The cost-effectiveness of an appliance efficiency measure depends on the length of time consumers will use an appliance. National shipments projections depend on the rate of replacement in the installed appliance stock. Furthermore, early retirement programs need an accurate understanding of the remaining useful life in order to calculate lifetime savings and cost-effectiveness of a program. This paper uses a method for calculating lifetime of appliances based on the most recent data available on appliance shipments, total appliance stock, and the fraction of surviving appliances by age bins. An example of the calculation methodology is provided for residential gas boilers. This paper concludes by comparing the results to other available data on gas boiler lifetime.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Realistic operation of two residential cordwood-fired outdoor hydronic heater appliances—Part 1: Particulate and gaseous emissions

This study investigated how heat demand and fuel loading affect the emissions from outdoor wood-fired hydronic heaters by testing two such appliances using an integrated-duty cycle test method. This test included transient operating conditions, such as cold and hot-starts and modulation between 15 and 100% of maximum rated output. Emission values indicate transient operating conditions produce higher emissions than steady state operation. Cold starts resulted in elevated particulate matter emission factors for both appliances; in one case the particulate matter emission factor for this period was >3500 mg/MJ, which represented emissions 20 times the average value. Additionally, when heat demand was cycled—elevated CO emission factors were measured, with values >5000 mg/MJ for both appliances and more than 3 times the appliance averages, respectively. It follows that the appliance average particulate matter emission factors and CO emission factors were not representative of the actual EF values during these transient periods. In contrast, methane emission factors were relatively stable throughout all tested combustion conditions; however, they were much higher than oil-fired appliances are therefore should not be ignored. These findings demonstrate that wood-fired hydronic heater emissions during transient operating conditions can be significantly greater than emissions during steady-state test conditions, such as those used in typical certification tests. Consequently, certification test values for particulate matter and CO emission factors may significantly underestimate the actual emissions of these appliances when operated in a home. Use of integrated duty-cycle test protocols that capture cold-starts and reloading are better for representing in-use operations of wood-fired hydronic heaters and provide more realistic emissions and delivered efficiency measurements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2012

Modeling of GE Appliances in GridLAB-D: Peak Demand Reduction

The widespread adoption of demand response enabled appliances and thermostats can result in significant reduction to peak electrical demand and provide potential grid stabilization benefits. GE has developed a line of appliances that will have the capability of offering several levels of demand reduction actions based on information from the utility grid, often in the form of price. However due to a number of factors, including the number of demand response enabled appliances available at any given time, the reduction of diversity factor due to the synchronizing control signal, and the percentage of consumers who may override the utility signal, it can be difficult to predict the aggregate response of a large number of residences. The effects of these behaviors can be modeled and simulated in open-source software, GridLAB-D, including evaluation of appliance controls, improvement to current algorithms, and development of aggregate control methodologies. This report is the first in a series of three reports describing the potential of GE's demand response enabled appliances to provide benefits to the utility grid. The first report will describe the modeling methodology used to represent the GE appliances in the GridLAB-D simulation environment and the estimated potential for peak demand reduction at various deployment levels. The second and third reports will explore the potential of aggregated group actions to positively impact grid stability, including frequency and voltage regulation and spinning reserves, and the impacts on distribution feeder voltage regulation, including mitigation of fluctuations caused by high penetration of photovoltaic distributed generation and the effects on volt-var control schemes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Load Disaggregation (Modeling Individual Appliance Power Generation & Consumption in Real-Time)

We developed a machine learning-based load disaggregation method to estimate the real-time output of individual appliances from the whole-house measurements. We first learn the important features associated with each type of appliances using the ground truth consumption data of individual appliances potentially available for a small set of houses equipped with submeters. The learned features are then be used to estimate the power generation/consumption of the appliances from the whole-house consumption. This developed load disaggregation software includes two steps. The first step is to identify the on/off status of different appliances using a classification method, and the second step is to estimate the appliance output using a regression method.

Hao, Jun↗

DOE OSTI2012

Assessment of Literature Related to Combustion Appliance Venting Systems

In many residential building retrofit programs, air tightening to increase energy efficiency is constrained by concerns about related impacts on the safety of naturally vented combustion appliances. Tighter housing units more readily depressurize when exhaust equipment is operated, making combustion appliances more prone to backdraft or spillage. Several test methods purportedly assess the potential for depressurization-induced backdrafting and spillage, but these tests are not robustly reliable and repeatable predictors of venting performance, in part because they do not fully capture weather effects on venting performance. The purpose of this literature review is to investigate combustion safety diagnostics in existing codes, standards, and guidelines related to combustion appliances. This review summarizes existing combustion safety test methods, evaluations of these test methods, and also discusses research related to wind effects and the simulation of vent system performance. Current codes and standards related to combustion appliance installation provide little information on assessing backdrafting or spillage potential. A substantial amount of research has been conducted to assess combustion appliance backdrafting and spillage test methods, but primarily focuses on comparing short-term (stress) induced tests and monitoring results. Monitoring, typically performed over one week, indicated that combinations of environmental and house operation characteristics most conducive to combustion spillage were rare. Research, to an extent, has assessed existing combustion safety diagnostics for house depressurization, but the objectives of the diagnostics, both stress and monitoring, are not clearly defined. More research is also needed to quantify the frequency of test “failure” occurrence throughout the building stock and assess the statistical effects of weather (especially wind) on house depressurization and in turn on combustion appliance venting. Incorporating weather variations and house ventilation system characteristics in existing simulation software may assist such analyses and with developing a more reliable diagnostic for use on-site.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2015

Powering a Home with Just 25 Watts of Solar PV. Super-Efficient Appliances Can Enable Expanded Off-Grid Energy Service Using Small Solar Power Systems

Highly efficient direct current (DC) appliances have the potential to dramatically increase the affordability of off-grid solar power systems used for rural electrification in developing countries by reducing the size of the systems required. For example, the combined power requirement of a highly efficient color TV, four DC light emitting diode (LED) lamps, a mobile phone charger, and a radio is approximately 18 watts and can be supported by a small solar power system (at 27 watts peak, Wp). Price declines and efficiency advances in LED technology are already enabling rapidly increased use of small off-grid lighting systems in Africa and Asia. Similar progress is also possible for larger household-scale solar home systems that power appliances such as lights, TVs, fans, radios, and mobile phones. When super-efficient appliances are used, the total cost of solar home systems and their associated appliances can be reduced by as much as 50%. The results vary according to the appliances used with the system. These findings have critical relevance for efforts to provide modern energy services to the 1.2 billion people worldwide without access to the electrical grid and one billion more with unreliable access. However, policy and market support are needed to realize rapid adoption of super-efficient appliances.

14 SOLAR ENERGY↗

DOE OSTI2012

Impact of Natural Gas Appliances on Pollutant Levels in California Homes

This report presents results from the first year of a 2-year study, investigating associations of five air pollutants (CO, NO 2 , NO X , formaldehyde and acetaldehyde) with the presence of natural gas appliances in California homes. From November 2011 to March 2012, pollutant concentration and occupant activity data were collected in 155 homes for 6-day periods. The sample population included both single-family (68%) and multi-family (32%) dwellings, with 87% having at least one gas appliance and 77% having an unvented gas cooking appliance. The geometric mean (GM) NO 2 levels measured in the kitchen, bedroom and outside of homes were similar at values of 15, 12 and 11 ppb, respectively. In contrast, the GM NO X levels measured in the kitchen and bedroom of homes were much higher than levels measured outdoors, at levels of 42 and 41 ppb, compared to 19 ppb, respectively. Roughly 10% of sampled homes had 6-day average NO2 levels that exceeded the outdoor annual average limit set by the California Ambient Air Quality Standards (CAAQS) (30 ppb). The GMs of the highest 1-h and 8-h CO level measured in homes were 2.5 and 1.1 ppm, respectively. Four homes had a 1-h or 8-h concentration that exceeded the outdoor limits set by the CAAQS. The GM formaldehyde and acetaldehyde concentrations measured in homes were 15 and 7 ppb, respectively. Roughly 95% of homes had average formaldehyde levels indoors that exceeded the Chronic Reference Exposure Level set by the California EPA (7 ppb). Concentrations of NO 2 and NO X , and to a lesser extent CO were associated with use of gas appliances, particularly unvented gas cooking appliances. Based on first principles, it is expected that effective venting of cooking pollutant emissions at the source will lead to a reduction of pollutant concentrations. However, no statistical association was detected between kitchen exhaust fan use and pollutant concentrations in homes in this study where gas cooking occurred frequently. The lack of statistical

03 NATURAL GAS↗

DOE OSTI2026

Characterizing electrical demand and load diversity of low-power water and space heating appliances in US homes

Home renovation and remodeling projects can involve costly and time consuming electrical infrastructure upgrades at the household level. From the grid perspective they also lead to costly replacement of local infrastructure, such as transformers, and can add stress to the grid at peak times. The emergence of innovative, power-efficient household appliances offers a way to minimize these problems. These appliances are designed for lower power consumption, simplifying installation through standard plug-in connections, reducing the need for new electric circuits/panels/service, and minimizing the peak power demand for the home. Key examples include low-power heat pump water heaters (HPWHs) and cold climate window heat pumps that operate on standard 120V outlets. To assess the real-world impact of these solutions, we compiled and analyzed power metering data from several US field studies. This data provides insights into the effects on peak power demand of selecting lower-power appliances. Our analysis focuses on several key metrics, including the maximum power demand of individual appliances, their operational runtime, continuous operation and load diversity. While individual low-power 120V space and water heating appliances offer significant peak demand reductions compared to 240V heat pump or resistance alternatives, their longer runtimes might increase the likelihood of operation during whole-dwelling peak events, albeit at lower power levels.

Less, Brennan↗

DOE OSTI2013

Avoided electricity subsidy payments can finance substantial appliance efficiency incentive programs: Case study of Mexico

Numerous countries use taxpayer funds to subsidize residential electricity for a variety of socioeconomic objectives. These subsidies lower the value of energy efficiency to the consumer while raising it for the government. Further, while it would be especially helpful to have stringent Minimum Energy Performance Standards (MEPS) for appliances and buildings in this environment, they are hard to strengthen without imposing a cost on ratepayers. In this secondbest world, where the presence of subsidies limits the government’s ability to strengthen standards, we find that avoided subsidies are a readily available source of financing for energy efficiency incentive programs. Here, we introduce the LBNL Energy Efficiency Revenue Analysis (LEERA) model to estimate the appliance efficiency improvements that can be achieved in Mexico by the revenue neutral financing of incentive programs from avoided subsidy payments. LEERA uses the detailed techno-economic analysis developed by LBNL for the Super-efficient Equipment and Appliance Deployment (SEAD) Initiative to calculate the incremental costs of appliance efficiency improvements. We analyze Mexico’s tariff structures and the long-run marginal cost of supply to calculate the marginal savings for the government from appliance efficiency. We find that avoided subsidy payments alone can finance incentive programs that cover the full incremental cost of refrigerators that are 27% more efficient and TVs that are 32% more efficient than baseline models. We find less substantial market transformation potential for room ACs primarily because AC energy savings occur at less subsidized tariffs.

25 ENERGY STORAGE↗