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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Framework for Evaluating Grid Readiness for Integrating Electric Vehicles and Utility Scale Storage in India

Electric vehicles (EVs) and distributed solar are poised to grow substantially in India in the coming years following ambitious Government of India targets. The localized impact of these changes, both in terms of infrastructure investments and demand patterns, are not well understood, nor are tools for this type of analysis readily available. This paper describes the development of a framework that can analyze network readiness in terms of feeder impacts for distributed energy resources (DERs) including growing EV penetration, and the potential solutions introduced by utility-scale battery energy storage systems (BESSs). The building blocks of the feeder analysis require multiple data sets to be compiled into a usable network model. The work is driven by feeder head and distribution transformer (DT) loading data along with all the technical specifications and schematics of distribution feeders. These measured data sets are conditioned to remove any afflictions, and the cleaned load profiles are used to perform multi-year quasi-static time-series power flow analyses on detailed three-phase feeder models. EVs translated to grid-tied loads are represented with aggregated EV demand profile estimates based on possible charging scenarios in residential sector, and in workplace and/or public charging stations. Finally, BESSs are evaluated for their cost-effectiveness in the framework through an initial screening that includes the benefits of grid service applications to mitigate present and future overloading scenarios. The outcomes from this framework are expected to help utilities gauge the readiness of their distribution grid for integrating an increasing number of EVs as well as load growth during a projected multi-year time horizon, where BESSs can contribute in making the grid more reliable.

electric vehicles↗
DOE OSTI2019

A review of the residential efficient lighting programme rollout in South Africa

Efficient lighting for the residential sector in South Africa stemmed out of an electricity supply crisis. The Compact Fluorescent Lamps (CFL) rollout programme was carried out in the absence of a supporting policy. The implementation resulted in both desirable and undesirable outcomes. Of even greater concern is that a section of the market may be regressing to inefficient lighting. An analysis of lighting technologies available in the market shows that a shift to more energy efficient lighting technologies, such as light-emitting diodes (LED), will result in significant energy savings.

Covary, T↗
DOE OSTI2024

Proactive and Reactive Thermal Comfort Behaviors

The expansion of renewable electricity generation, growing demands due to electrification, greater prevalence of working from home, and increasing frequency and severity of extreme weather events, will place new demands on the electric supply and distribution grid. Broader adoption of demand response programs (DRPs) for the residential sector may help meet these challenges; however, experience shows that occupant overrides in DRPs compromises their effectiveness. There is a lack of formal understanding of how discomfort, routines, and other motivations affect DRP overrides and other related human building interactions (HBI). This paper reports preliminary findings from a study of 20 households in Colorado and Massachusetts, US over three months. Participants responded to ecological momentary assessments (EMA) triggered by thermostat interactions and at random times throughout the day. EMAs included Likert-scale questions of thermal preference, preference intensity, and changes to 7 different activity types that could affect thermal comfort, and an opened ended question about motivations of such actions. Twelve tags were developed to categorize motivation responses and analyzed statistically to identify associations between motivations, preferences, and HBI actions. Reactions to changes in the thermal environment were the most frequently observed motivation (118 of 220 responses). On the other hand, almost half (47%) responses were at least partially motivated by non-thermal factors, suggesting limited utility for occupant behavior models founded solely on thermal comfort. Changes in activity level and clothing were less likely to be reported when EMAs were triggered by thermostat interactions, while fan interactions were more likely. Windows, shades, and portable heater interactions had no significant dependence on how the EMA was triggered. These results suggest that better understanding of motivations for HBI may improve effectiveness of demand response programs.

Pathak, Maharshi↗
DOE OSTI2014

Assessing National Employment Impacts of Investment in Residential and Commercial Sector Energy Efficiency: Review and Example Analysis

Energy efficiency is a key solution to concerns regarding future energy supply, energy security, and the harmful long-term effects of climate change. In addition to addressing these issues, actions motivated by governmental policies and programs, along with efforts by utilities and third parties, result in greater energy efficiency and also save consumers money. A continuing question is the degree to which energy efficiency measures spur economic growth and higher levels of employment. Research interest in this topic has recently risen in response to trends reflecting increased market adoption of energy efficiency measures, increased reliance on energy efficiency as a resource to offset new electricity generation, and the utilization of energy efficiency portfolio standards by states to spur wider adoption of energy efficiency and reduce future electricity demand.

Economic Impact Modeling↗
DOE OSTI2012

Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation

Changing the rate of airflow through a home affects the annual thermal conditioning energy. Large-scale changes to airflow rates of the housing stock can significantly alter the energy consumption of the residential energy sector. However, the complexity of existing residential energy models hampers the ability to estimate the impact of policy changes on a state or nationwide level. The Incremental Ventilation Energy (IVE) model developed in this study was designed to combine the output of simple airflow models and a limited set of home characteristics to estimate the associated change in energy demand of homes. The IVE model was designed specifically to enable modelers to use existing databases of home characteristics to determine the impact of policy on ventilation at a population scale. In this report, we describe the IVE model and demonstrate that its estimates of energy change are comparable to the estimates of a wellvalidated, complex residential energy model when applied to homes with limited parameterization. Homes with extensive parameterization would be more accurately characterized by complex residential energy models. The demonstration included a range of home types, climates, and ventilation systems that cover a large fraction of the residential housing sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Forecasting of municipal solid waste quantity in a developing country using multivariate grey models

Highlights: • Grey model can be used to forecast MSW quantity accurately with the limited data. • Prediction interval overcomes the uncertainty of MSW forecast effectively. • A multivariate model gives accuracy associated with factors affecting MSW quantity. • Population, urbanization, employment and household size play role for MSW quantity. - Abstract: In order to plan, manage and use municipal solid waste (MSW) in a sustainable way, accurate forecasting of MSW generation and composition plays a key role. It is difficult to carry out the reliable estimates using the existing models due to the limited data available in the developing countries. This study aims to forecast MSW collected in Thailand with prediction interval in long term period by using the optimized multivariate grey model which is the mathematical approach. For multivariate models, the representative factors of residential and commercial sectors affecting waste collected are identified, classified and quantified based on statistics and mathematics of grey system theory. Results show that GMC (1, 5), the grey model with convolution integral, is the most accurate with the least error of 1.16% MAPE. MSW collected would increase 1.40% per year from 43,435–44,994 tonnes per day in 2013 to 55,177–56,735 tonnes per day in 2030. This model also illustrates that population density is the most important factor affecting MSW collected, followed by urbanization, proportion employment and household size, respectively. These mean that the representative factors of commercial sector may affect more MSW collected than that of residential sector. Results can help decision makers to develop the measures and policies of waste management in long term period.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2011

Target Allocation Methodology for China's Provinces: Energy Intensity in the 12th FIve-Year Plan

Experience with China's 20% energy intensity improvement target during the 11th Five-Year Plan (FYP) (2006-2010) has shown the challenges of rapidly setting targets and implementing measures to meet them. For the 12th FYP (2011-2015), there is an urgent need for a more scientific methodology to allocate targets among the provinces and to track physical and economic indicators of energy and carbon saving progress. This report provides a sectoral methodology for allocating a national energy intensity target - expressed as percent change in energy per unit gross domestic product (GDP) - among China's provinces in the 12th FYP. Drawing on international experience - especially the European Union (EU) Triptych approach for allocating Kyoto carbon targets among EU member states - the methodology here makes important modifications to the EU approach to address an energy intensity rather than a CO{sub 2} emissions target, and for the wider variation in provincial energy and economic structure in China. The methodology combines top-down national target projections and bottom-up provincial and sectoral projections of energy and GDP to determine target allocation of energy intensity targets. Total primary energy consumption is separated into three end-use sectors - industrial, residential, and other energy. Sectoral indicators are used to differentiate the potential for energy saving among the provinces. This sectoral methodology is utilized to allocate provincial-level targets for a national target of 20% energy intensity improvement during the 12th FYP; the official target is determined by the National Development and Reform Commission. Energy and GDP projections used in the allocations were compared with other models, and several allocation scenarios were run to test sensitivity. The resulting allocations for the 12th FYP offer insight on past performance and offer somewhat different distributions of provincial targets compared to the 11th FYP. Recommendations for reporting and monitoring progress on the targets, and methodology improvements, are included.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Coastal Ohio Wind Project for Reduced Barriers to Deployment of Offshore Wind Energy

The Coastal Ohio Wind Project was created to establish the viability of wind turbines on the coastal and offshore regions of Northern Ohio. The project’s main goal was to improve operational unit strategies used for environmental impact assessment of offshore turbines on lake wildlife by optimizing and fusing data from the multi-instrument surveillance system and providing an engineering analysis of potential design/operational alternatives for offshore wind turbines. The project also developed a general economic model for offshore WTG deployment to quantify potential revenue losses due to wind turbine shutdown related to ice and avian issues. In a previous phase of this project (Award Number: DE-FG36-06GO86096), we developed a surveillance system that was used to collect different parameters such as passage rates, flight paths, flight directions, and flight altitudes of nocturnal migrating species, movements of birds and bats, and bird calls for assessing patterns and peak passage rates during migration. To derive such parameters we used thermal IR imaging cameras, acoustic recorders, and marine radar Furuno (XANK250), which was coupled with a XIR3000B digitizing card from Russell Technologies and open source radR processing software. The integration yielded a development of different computational techniques and methods, which we further developed and optimized as a combined surveillance system. To accomplish this task we implemented marine radar calibration, optimization of processing parameters, and fusion of the multi-sensor data in order to make inferences about the potential avian targets. The main goal of the data fusion from the multi-sensor environment was aimed at reduction of uncertainties while providing acceptable confidence levels with detailed information about the migration patterns. Another component comprised of an assessment of wind resources in a near lake environment and an investigation of the effectiveness of ice coating materials to mitigate adverse effects of ice formation on wind turbine structures. Firstly, a Zephir LiDAR system was acquired and installed at Woodlands School in Huron, Ohio, which is located near Lake Erie. Wind resource data were obtained at ten measurement heights, 200m, 150m, 100m, 80m, 60m, 40m, 38m, 30m, 20m, and 10m. The Woodlands School’s wind turbine anemometer also measured the wind speed at the hub height. These data were collected for approximately one year. The hub anemometer data correlated well with the LiDAR wind speed measurements at the same height. The data also showed that on several days different power levels were recorded by the turbine at the same wind speed as indicated by the hub anemometer. The corresponding LiDAR data showed that this difference can be attributed to variability in the wind over the turbine rotor swept area, which the hub anemometer could not detect. The observation suggests that single point hub wind velocity measurements are inadequate to accurately estimate the power generated by a turbine at all times since the hub wind speed is not a good indicator of the wind speed over the turbine rotor swept area when winds are changing rapidly. To assess the effectiveness of ice coatings to mitigate the impact of ice on turbine structures, a closed-loop icing research tunnel (IRT) was designed and constructed. By controlling the temperature, air speed, water content and liquid droplet size, the tunnel enabled consistent and repeatable ice accretion under a variety of conditions with temperatures between approximately 0°C and -20°C and wind speeds up to 40 miles per hour in the tunnel’s test section. The tunnel’s cooling unit maintained the tunnel temperature within ±0.2°C. The coatings evaluated in the study were Boyd Coatings Research Company’s CRC6040R3, MicroPhase Coatings Inc.’s PhaseBreak TP, ESL and Flex coatings. Similar overall performance was observed in all coatings tested in that water droplets form on the test articles beginning at the stagnation region and spreading in the downstream direction in time. When comparing ice accumulation characteristics for the four coatings tested, for ice thickness during accumulation the CRC6040R3 had the least, followed by the ESL, Flex, and TP. However, when comparing the coatings’ ability to reduce ice adhesion, the Flex showed the highest adhesion reduction, followed by the ESL, TP and CRC 6040R3 coatings. The ice accumulated on the Flex coated surface shed under gravity when rotated 90 degrees following the tests while the other coatings required application of varying degrees of force to remove the ice. In conclusion, the ice coatings tested were not sufficient in preventing ice accumulation on all surfaces. However, Flex coating shows promise in mitigating ice on the rotor blades under the gravitational and centrifugal forces. Only the effect of gravity in shedding the ice was considered in this study. Further research will be needed to evaluate this coating on rotating blades in the icing tunnel to characterize its effectiveness. Lastly, the development of economic feasibility models used existing approaches adapted for offshore deployment in marine settings to one more suitable for Lake Erie deployment. Two different wind turbine models were tested and dynamic return on investment (ROI) model scenarios were generated. For the purpose of estimating power generation three bladed wind turbines of 3 MW capacity were selected including Model1- Leitwind LTW101-3.000-kW and Model2-Vostro V90-3.0 MW. The analysis were based on the revenue aspect of decision making of deploying wind turbines in the Ohio coastal region. The installation cost, maintenance and operational aspects were disregarded due to unavailability of data. The adjusted varying price (residential and industrial sector) and projected future price of electricity in different years suggested that the Leitwind model could generate $\$ $32.4 million of revenue in 25 years if the supply electricity is in the residential sector, while it would be $\$ $14.7million if the supply is in the industrial sector. For the Vostro model these figures are $\$ $28.6 million for residential sector and $\$ $12.9 million for industrial sector for 25 years.

17 WIND ENERGY↗
DOE OSTI2018

Is Every kWh the Same? How Do Energy Efficiency Measures Stack Up Across Regions?

The U.S. residential building sector is responsible for thirty-eight percent of electricity use, as well as for 49%, 8%, 19% and 2% of U.S. SO2, NOx, CO2 and PM2.5 emissions, respectively. The residential building sector is also a key target of customer funded energy efficiency programs, which have typically been designed to reduce energy consumption (kWh). Today, energy efficiency is also being used to meet air emissions goals. However, not every kWh saved has the same mitigation potential. The goal of this work is to evaluate energy efficiency potential in the U.S. residential building sector and determine how energy conservation measures (ECMs) that reduce electricity consumption correlate to air emissions reductions. To assess energy efficiency potential, this analysis uses Scout, a software program developed by the U.S. Department of Energy that estimates the energy and CO2 impact potential of various ECMs on the U.S. residential and commercial building sectors. Here, Scout is first used to assess the total long term national energy (electricity, gas, and oil), CO2, and cost savings of deploying residential ECM portfolios. Then, electricity savings results from Scout in 2021 are used to assess the regional differences in emissions reductions with the Avoided Emissions and geneRation Tool (AVERT) model from different end uses. Better understanding the relationship between ECMs and cost-effective emission reductions will enable states, municipalities and other interested parties to meet multiple policy objectives through energy efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

A simplified regression building thermal modelling method for detached two-floor house in U.S.

The residential building sector accounts for approximately 37% of total U.S. electricity consumption. Within the residential building sector, heating and cooling is the main target for peak load shifting/reduction since it is the largest contributor to peak demand. In fact, the flexibility of residential HVAC loads can provide continuous variation of demand to provide grid services by varying their demand over a baseline. The performance of HVAC load control to provide grid services relies heavily on the accuracy of indoor air temperature or cooling/heating demand predictions and therefore the quality of building model. Besides forward models, popular building models are data-driven models which can be broken down into two categories: gray-box model, e.g. Resistance-Capacitance (RC) model and black-box model. RC model, also called lumped capacitance or network model, which is constituted with electrical analogue pattern with resistance (R) and capacitance (C). In general, RC models require considerable computation burden and long periods of data to train limited number of model coefficients. Black-box models have gained increasing interest due to their capability in analyzing large-scale data and flexibility in practical applications. But, the data-mining based (machine learning algorithms/techniques based) models tend to have invisible model structures which poses a problem when trying to use the model for optimal control or model predictive control of the HVAC system. Hence, there is a continuing need for efficient online system identification techniques, which can provide explicit parameters for the model. Traditional regression models fit well for this specific purpose. This paper presents an innovative way to predict average indoor temperature in separate floors of typical detached residential house. A rolling horizon linear regression model, which includes online adaptive correction component, is proposed to predict the temperature difference between downstairs and upstairs. A RC model is used to predict the overall mean indoor air temperature. Since the adaptive algorithm needs to be implemented online, a less computation-demanding polynomial fitting algorithm is adopted. This kind of fitting problem can be cast as linear regression problem with multiple variables, parameters of which can be efficiently obtained by well-known gradient descent method.The validation is conducted by comparing the predicted results with the results from data-mining based models as well as measured data from a real typical detached two-floor house. The results show that the developed method has satisfactory performance in predicting the building indoor temperature in 1st and 2nd floors.

Cui, Borui↗
DOE OSTI2024

Geospatial characterization of low-temperature heating and cooling demand in residential, commercial, manufacturing, agricultural, and data center sectors for potential geothermal applications in the United States

Thermal demand for heating and cooling has been predominantly supplied by fossil fuel combustion in the United States, although low-carbon alternatives are extensively available including geothermal, solar thermal, and waste heat. Here, this study analyzed end-use energy consumption, fuel expenditure, and data center commissioned power data to geospatially characterize the U.S. low-temperature heating and cooling demand at the county level in residential, commercial, manufacturing, agricultural, and data center sectors and understand potential opportunities for geothermal applications. In the analysis, the regional-scale energy consumption data was incorporated with system efficiencies to address actual demand and was then disaggregated with weighting factors to the county level. The results indicated that total low-temperature heating and cooling demand is 16.7 EJ, combining heating demand of 10.8 EJ and cooling demand of 5.9 EJ. Overall, 59.9 % (10 EJ) of the low-temperature heating and cooling demand occurred in the residential sector. The heating and cooling demand visualized in maps represented that the geospatial distribution of heating and cooling demand in the residential and commercial sectors is governed by the number of housing units and climate zone designations, while heating and cooling demand in the manufacturing, agricultural, and data center sectors is dependent on the number and location of facilities. The results also demonstrated that geothermal heat pumps are broadly used in the residential and commercial sectors for heating and cooling in the U.S. Midwest, South, and Northeast regions but are limited in the West, implying great decarbonization potential in the future.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Technology inventory: energy efficiency measures for residential, commercial, and industrial sectors in the United States

Energy efficiency is expected to continue to be one of main levers for governments to address the energy and climate crisis. While a diverse mix of energy efficiency programs has been regarded as an important part of governmental actions, an energy efficiency policy or program needs to identify and assess eligible savings measures, i.e., specific technologies or practices, for designing key features, e.g., target type, target stringency, covered load, and cost recovery. This report briefly discusses U.S. energy efficiency policies and programs, explores publicly available resources of energy efficiency measures for residential, commercial, and industrial sectors in the U.S., and describes how to compile key measures and characteristics into an integrated spreadsheet database. The database in the initial version offers, for more than 1,200 measures, efficiency or improvement potential, technical notes, costs at a given year, where applicable. Energy efficiency measures compiled here could play an important role in determining savings targets and target stringency under a potential energy efficiency policy such as an energy efficiency resource standard in Korea, and offer significant opportunities for energy efficiency improvement.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Long-term decarbonization impacts on residential energy security across income groups and US states

Abstract The impact of a transition to a net-zero economy on the residential energy sector across diverse income groups in the US remains uncertain. Here, we employ an integrated human-Earth system model, incorporating an expanded set of ten income groups in the residential energy sector, to examine the distributional impacts of long-term decarbonization scenarios on residential energy security at the state level through 2050. We use multiple metrics of energy security, including energy burden, energy satiation gap, and the distribution of energy service across income groups. Our findings show that the net-zero decarbonization scenarios affect residential energy security differently across income groups, with low-to-mid-income groups experiencing larger negative impacts on the dimensions studied here. Comparatively, climate change impact on residential energy security is minor through 2050 based on our model outcomes. Specifically, the net-zero decarbonization scenarios lead to increased energy burden across all income groups and states in 2050, where the lowest (highest) income group in each state shows an average of 0.6 (0.2) percentage point increase in energy burden, relative to the business-as-usual in 2050. The distribution of energy service consumption across income groups is also slightly more skewed under these scenarios. As incomes grow across all deciles in the future, residential energy security generally improves through 2050. Targeted interventions could mitigate the disproportionate impacts that some groups could incur under a transition to a net-zero economy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1975

Input-output analysis of some sector actions

Selected energy conservation actions previously discussed in depth but separately in the areas of the energy industry, the industry sector, the transportation sector, and the residential and commercial sector, were brought together and assessed as a group. Particular emphasis was devoted to identifying secondary or indirect impacts and multiple interactions. Preliminary results obtained from the ECASTAR energy input-output model suggest that the impacts of energy conservation actions can be grossly misrepresented if secondary impacts are not included in the assessment. A methodology which stresses the importance of secondary and multiple interactions permeates the underlying philosophy of this discussion.

Source record↗
DOE OSTI2024

Cost-Benefit Analysis For Indonesia Building Sector: Whole-Building Cooling Solutions

The Net Zero World (NZW) Initiative Collaborative Work Program with the Government of Indonesia (GoI) includes technical assistance and investment mobilization facilitation to accelerate deployment of energy efficiency technologies and solutions for the building sector. A February 2023 U.S.–Indonesia Joint Workshop on Decarbonizing the Building Sector yielded a NZW Indonesia Building Decarbonization Working Group (NZW IBDWG) with four sub-working groups (SWG): SWG-A National Center, SWG-B Capacity Building, SWG-C Investment and Financing, and SWG-D Pilot Projects. Technical analysis of whole-building cooling solutions for tropical climates of Indonesia was conducted by SWG-A to quantify energy savings, carbon dioxide reductions, and comfort improvements offered by 12 passive or low-energy cooling strategies: ceiling fans with and without thermostat setbacks; cool roofs; cool walls; exterior awnings; exterior shades; interior shades; insulated roofs; insulated walls; low-e windows; solar window films; and natural ventilation. Leveraging the results from SWG-A, cost-benefit analysis (CBA) was conducted by SWG-C to assess the consumer and national costs and impacts associated with these 12 cooling solutions. The evaluation involved estimating life-cycle costs (LCC), payback period (PBP), net present values (NPV), annual electricity burden change for low-income households, and reduced national annual power-sector generation demand by 2030, 2040, 2050, and 2060. This evaluation can help guide Indonesia’s Just Energy Transition Partnership (JETP) investments in policies and programs to advance research, development, deployment, and commercial adoption (RDDCA) of efficient residential building sector cooling technologies and solutions in Indonesia. Four key energy conservation measures (ECM) have been identified to reduce air-conditioning (AC) energy demand in single-family housing in Indonesia: ceiling fan with temperature setback (to 28.1 °Celcius from 25 °C); insulated walls; insulated roof; and cool roof. This study found that low-income households with AC installations in Indonesia currently face a high energy cost burden of approximately 10%. However, by implementing a ceiling fan with temperature setback, this burden could decrease to 2.5% today and further reduce to 1.3% by the year 2060. The PBP for a ceiling fan with temperature setback is one year, indicating one of the lowest LCC and best NPV. In the planned upcoming phase of CBA, a series of building cooling improvement scenarios can be further defined, incorporating more than one ECM in combination with socio-economic factors evaluated in the initial CBA phase. Additionally, the analysis of ECM effects in multifamily housing can be expanded. This broader national analysis aims to encompass a holistic and comprehensive system-level perspective, including factors such as avoided power sector infrastructure investments, domestic job creation, domestic manufacturing job creation, and gross domestic product (GDP) growth.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2010

California Energy Balance Update and Decomposition Analysis for the Industry and Building Sectors (Final Report)

This report on the California Energy Balance version 2 (CALEB v2) database documents the latest update and improvements to CALEB version 1 (CALEB v1) and provides a complete picture of how energy is supplied and consumed in the State of California. The CALEB research team at Lawrence Berkeley National Laboratory (LBNL) performed the research and analysis described in this report. CALEB manages highly disaggregated data on energy supply, transformation, and end-use consumption for about 40 different energy commodities, from 1990 to 2008. This report describes in detail California's energy use from supply through end-use consumption as well as the data sources used. The report also analyzes trends in energy demand for the "Manufacturing" and "Building" sectors. Decomposition analysis of energy consumption combined with measures of the activity driving that consumption quantifies the effects of factors that shape energy consumption trends. The study finds that a decrease in energy intensity has had a very significant impact on reducing energy demand over the past 20 years. The largest impact can be observed in the industry sector where energy demand would have had increased by 358 trillion British thermal units (TBtu) if subsectoral energy intensities had remained at 1997 levels. Instead, energy demand actually decreased by 70 TBtu. In the "Building" sector, combined results from the "Service" and "Residential" subsectors suggest that energy demand would have increased by 264 TBtu (121 TBtu in the "Services" sector and 143 TBtu in the "Residential" sector) during the same period, 1997 to 2008. However, energy demand increased at a lesser rate, by only 162 TBtu (92 TBtu in the "Services" sector and 70 TBtu in the "Residential" sector). These energy intensity reductions can be indicative of energy-efficiency improvements during the past 10 years. The research presented in this report provides a basis for developing an energy-efficiency performance index to measure progress over time in the State of California.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

An Implementation for Transforming a Home Energy Management System to a Multi-agent System

In the United States, 41% of produced energy is consumed by the building sector, i.e. residential and commercial buildings (Building Energy Data Book, Buildings Sector, US Department of Energy, Office of Energy Efficiency and Renewable Energy, Building Technologies Office, 2012. n.d.). The anticipation is that Home Energy Management Systems (HEMS) will support energy efficiency gains through control of the devices in an optimal fashion. New opportunities are offering the ability to integrate grid type controls and the most suitable way to perform these controls is through a multi-agent system (MAS). In this paper, approaches on supporting a HEMS and MAS integration are discussed.

Zandi, Helia↗