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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Device-level plug load disaggregation in a zero energy office building and opportunities for energy savings

Along with heating, cooling, ventilation, and lighting, plug loads are one of the principal consumers of energy in commercial buildings. Managing ever-changing plug loads is a great challenge given the quantity and variety of devices in commercial buildings and the cost of monitoring equipment. To address this issue, we propose a method for developing a disaggregated model of an office building's plug loads that utilizes power data from a small portion of monitored devices and a device inventory. Using data from metering and control devices in the Research Support Facility at the National Renewable Energy Laboratory, we compared our model to the building's plug load submeters. We found that the model was effective in predicting the shape of the building's average plug loads; however, it did not account for the entire magnitude of the load. With the disaggregated breakdown, we identified devices that contributed significantly to the building's unoccupied load, such as the audio visual equipment as well as devices that contributed significantly at specific times of the day, such as the microwaves at noon. This disaggregated information enables building owners to make more informed decisions with respect to plug load controls and energy efficiency upgrades. Furthermore, we highlight how the plug loads in the Research Support Facility have changed over time and offer recommendations for implementing this disaggregation method in other buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

New Whole-House Solutions Case Study: Low-Cost Evaluation of Energy Savings at the Community Scale - Fresno, California

In this project, IBACOS partnered with builder Wathen-Castanos Hybrid Homes to develop a simple and low-cost methodology by which community-scale energy savings can be evaluated based on results at the occupied test house level.Research focused on the builder and trade implementation of a whole-house systems integrated measures package and the actual utility usage in the houses at the community scale of production. Five occupants participated in this community-scale research by providing utility bills and information on occupancy and miscellaneous gas and electric appliance use for their houses. IBACOS used these utility data and background information to analyze the actual energy performance of the houses. Verification with measured data is an important component in predictive energy modeling. The actual utility bill readings were compared to projected energy consumption using BEopt with actual weather and thermostat set points for normalization.

Building America↗
DOE OSTI2013

Boston Architectural College Urban Sustainability Initiative

The Boston Architectural College's Urban Sustainability initiative is a demonstration project as defined by the National Energy Technology Laboratory. BAC's proposed project with the U.S. Department of Energy - NETL, is a large part of that overall initiative. The BAC's Urban Sustainability Initiative is a multi-part project with several important goals and objectives that will have a significant impact on the surrounding neighborhood including: energy conservation, reduction of storm water runoff, generation of power through alternative energy sources, elimination/reduction of BAC carbon footprint, and to create a vehicle for ongoing public outreach and education. Education and outreach opportunities will serve to add to the already comprehensive Sustainability Design courses offered at BAC relative to energy savings, performance and conservation in building design. At the finish of these essential capital projects there will be technical materials created for the education of the design, sustainability, engineering, community development and historic preservation communities, to inform a new generation of environmentally-minded designers and practitioners, the city of Boston and the general public. The purpose of the initiative, through our green renovations program, is to develop our green alley projects and energy saving renovations to the BAC physical plant, to serve as a working model for energy efficient design in enclosed 19th century and 20th century urban sites and as an educational laboratory for teaching ecological and sustainable technologies to students and the public while creating jobs. The scope of our project as it relates to the BAC and the U.S. Department of Energy- NETL combined efforts includes: Task I of the project is Phase II (Green Alley). Task I encompasses various renovation activities that will demonstrate the effectiveness of permeable paving and ground water recharge systems. It will aid in the reduction of storm water runoff into the Charles River Basin in one of its most significantly polluted sections and, will provide a green renovation mechanism for the redirected storm water of a public alley way. This activity is designed to improve the quality of water recharging the ground water and protecting the vulnerable wood pilings under many of the historic masonry buildings in Boston's Back Bay. Sustainable design research and system monitoring opportunities will also be incorporated, providing ongoing tools for public outreach and education through innovative signage and "virtual tour" technology. The monitoring will include a "building performance dash board" that reflects real time operating conditions and improvements in environmental and economic performance to be prominently displayed on the face of our 320 Newbury Street building (approximately 1.5 million people walk by annually). The project site and demonstration area is located at the rear of 951 Boylston Street, Boston, MA 02115 and the parking area adjacent to Public Alley #444 in Boston's historic Back Bay. Task II of the project is Geothermal Solution. This task involves the installation of approximately seven Geothermal wells which will tap into the earth's constant underground temperatures to provide air-conditioning and heating for BAC facilities. The environmentally friendly geothermal system uses no fossil fuel, produces no emissions and runs silently, providing a sustainable model for commercial and residential buildings throughout Boston. Ultimately the combination of this project and other projects will assist in making the BAC "carbon-neutral", and could generate enough additional energy to provide free power to the Engine 33 and Ladder 15 Firehouse located at 941 Boylston Street. The project is located at the rear of 951 Boylston Street, Boston, MA 02115 and the parking area adjacent to Public Alley #444 in Boston's historic Back Bay. Task III of the project is the Sustainability Design Curriculum at the BAC. The BAC is the nation’s largest independent, multi-disciplinary college of spatial design, and a leader in sustainable design education. The Sustainabiltiy Design program, in particular, focuses on energy efficiency,energy performance, energy modeling, energy and air quality principles, green building, renewable energy alternatives and much more. Additionally, the Urban Sustainability Initiative has an objective of providing courses relative to the BAC's demonstration project with DOE, the project’s period of performance activities, subsequent performance data and anticipated sustainability teaching tools. In keeping with BAC's practice based curriculum, students have been involved in the discussion and planning of this project since its inception and sustainability issues have become a part of other programs throughout the college as well. Students will continue to benefit from this hands-on learning opportunity. The project is located at 320 Newbury Street Boston, MA 02115. Task IV of the project is Program Management and Reporting. This task will involve BAC's oversight and general management of the entire project including subcontract administration, contracts administration, technical and financial reporting, design and renovation assistance, other deliverables in accordance with the Federal Assistance reporting Checklist and other contractual obligations and provisions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Building thermal load prediction through shallow machine learning and deep learning

Building thermal load prediction informs the optimization of cooling plant and thermal energy storage. Physics-based prediction models of building thermal load are constrained by the model and input complexity. In this study, we developed 12 data-driven models (7 shallow learning, 2 deep learning, and 3 heuristic methods) to predict building thermal load and compared shallow machine learning and deep learning. The 12 prediction models were compared with the measured cooling demand. It was found XGBoost (Extreme Gradient Boost) and LSTM (Long Short Term Memory) provided the most accurate load prediction in the shallow and deep learning category, and both outperformed the best baseline model, which uses the previous day's data for prediction. Then, we discussed how the prediction horizon and input uncertainty would influence the load prediction accuracy. Major conclusions are twofold: first, LSTM performs well in short-term prediction (1 h ahead) but not in long term prediction (24 h ahead), because the sequential information becomes less relevant and accordingly not so useful when the prediction horizon is long. Second, the presence of weather forecast uncertainty deteriorates XGBoost's accuracy and favors LSTM, because the sequential information makes the model more robust to input uncertainty. Training the model with the uncertain rather than accurate weather data could enhance the model's robustness. Finally, our findings have two implications for practice. First, LSTM is recommended for short-term load prediction given that weather forecast uncertainty is unavoidable. Second, XGBoost is recommended for long term prediction, and the model should be trained with the presence of input uncertainty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Building America Case Study: Low-Cost Evaluation of Energy Savings at the Community Scale, Fresno, California (Fact Sheet)

A new construction pilot community was constructed by builder-partner Wathen-Castanos Hybrid Homes (WCHH) based on a single occupied test house that was designed to achieve greater than 30% energy savings with respect to the House Simulation Protocols (Hendron, Robert; Engebrecht, Cheryn (2010). Building America House Simulation Protocols. Golden, CO: National Renewable Energy Laboratory.). Builders face several key problems when implementing a whole-house systems integrated measures package (SIMP) from a single test house into multiple houses. Although a technical solution already may have been evaluated and validated in an individual test house, the potential exists for constructability failures at the community scale. This report addresses factors of implementation and scalability at the community scale and proposes methodologies by which community-scale energy evaluations can be performed based on results at the occupied test house level. Research focused on the builder and trade implementation of a SIMP and the actual utility usage in the houses at the community scale of production. Five occupants participated in this community-scale research by providing utility bills and information on occupancy and miscellaneous gas and electric appliance use for their houses. IBACOS used these utility data and background information to analyze the actual energy performance of the houses. Verification with measured data is an important component in predictive energy modeling. The actual utility bill readings were compared to projected energy consumption using BEopt with actual weather and thermostat set points for normalization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

NREL's Sustainable Campus Overview

The high-performance buildings across the Energy Department's National Renewable Energy Laboratory's (NREL) South Table Mountain campus incorporate a number of state-of-the art energy efficiency and renewable energy technologies, making them models for sustainability. Each building, designed to meet the Gold or Platinum standards of the U.S. Green Building Council's Leadership in Energy and Environmental Design (LEED®) program, brings NREL closer to developing the campus of the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

An Open, Cloud-Based Platform for Whole-Building Fault Detection and Diagnostics

Small commercial buildings in the U.S. waste an estimated 300 Trillion BTU (approximately $6 billion in energy costs) annually due to faults, but lack cost-effective automated fault detection and diagnosis (AFDD) tools. NREL and GE Global Research are partnering to develop hybrid AFDD algorithms tailored to the unique needs of small commercial buildings (</=10,000 sq. ft.). The approach combines physics-based energy modeling tools with state-of-the-art machine learning algorithms to enable diagnostics using modeled input data. NREL, in partnership with Purdue University, has adapted DOE's physics-based modeling software EnergyPlus and OpenStudio to simulate common building faults. Cloud-based implementations of these physics-based models were used to generate data for multiple climate zones. The data were then used to train machine learning algorithms, such as those available in GE's Predix platform, to detect and diagnose building faults. Key features of the system including the automated, cloud-implementation of EnergyPlus, genetic algorithms for automated model feature selection, multiclass detection and diagnosis models, and anomaly detection algorithms will be presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Anomaly Attribution with Likelihood Compensation

This paper addresses the task of explaining anomalous predictions of a black-box regression model. When using a black-box model, such as one to predict building energy consumption from many sensor measurements, we often have a situation where some observed samples may significantly deviate from their prediction. It may be due to a sub-optimal black-box model, or simply because those samples are outliers. In either case, one would ideally want to compute a responsibility score indicative of the extent to which an input variable is responsible for the anomalous output. In this work, we formalize this task as a statistical inverse problem: Given model deviation from the expected value, infer the responsibility score of each of the input variables. We propose a new method called likelihood compensation (LC), which is founded on the likelihood principle and computes a correction to each input variable. To the best of our knowledge, this is the first principled framework that computes a responsibility score for real valued anomalous model deviations. We apply our approach to a real-world building energy prediction task and confirm its utility based on expert feedback.

Idé, Tsuyoshi↗
DOE OSTI2024

National Cost-Effectiveness of ANSI/ASHRAE/IES Standard 90.1-2022

The purpose of this analysis is to examine the cost-effectiveness of the 2022 edition of ANSI/ASHRAE/IES Standard 90.1, which is developed by the ASHRAE Standard Standing Project Committee (SSPC) 90.1 and is the model energy standard for all commercial buildings and multifamily residential buildings over three floors. PNNL analyzed the cost-effectiveness of changes in Standard 90.1-2022, compared to the previous 90.1-2019 edition, as applied in commercial buildings across the United States. In reviewing proposed changes to Standard 90.1, the SSPC considers the cost-effectiveness of individual changes (addenda). Due to the continuous nature of the development process, however, ASHRAE does not evaluate the entire package of addenda from one edition of the standard to the next, which is of particular interest to adopting state and local governments. Providing states with an analysis of cost-effectiveness facilitates a more comprehensive understanding of the impacts associated with updated model energy codes, informs the state decision-making process and its authorities, and ultimately encourages greater adoption of updated energy codes. This information also informs the development of future editions of Standard 90.1.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Framework for Modeling 3D-Printed Concrete Construction to Assess Energy Efficiency and Backup Power Trade-Offs in a Mixed-Use, New Construction Neighborhood Development

This paper presents a framework that expands the URBANopt(TM) modeling platform to include 3D-printed concrete wall assemblies and assess energy efficiency and backup power trade-offs in new housing developments. Applied to a planned mixed-use neighborhood in Oil City, Pennsylvania, the workflow integrates building energy and distributed energy resource (DER) modeling to evaluate envelope and equipment upgrades alongside DER operations. Results show that advanced 3D-printed envelopes combined with efficient systems and onsite photovoltaics (PV) and storage reduce energy use intensity and sustain critical loads during outages. The framework supports planning for emerging construction technologies by quantifying key trade-offs between energy efficiency and backup power performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

City and County Vehicle Inventories

This light-duty vehicle inventory dataset provides information on vehicle registrations by vehicle type (car vs. truck), fuel type, and model year showing the changes in adoption trends over time and average fuel economies. This data is part of a suite of state and local energy profile data available at the "State and Local Energy Profile Data Suite" link below and builds on Cities-LEAP energy modeling, available at the "EERE Cities-LEAP Page" link below. Examples of how to use the data to inform energy planning can be found at the "Example Uses" link below.

Alternative Fuel↗
DOE OSTI2025

Energy innovation in the US buildings sector: Setting the stage and mapping the future

Jared Langevin is a staff scientist at Lawrence Berkeley National Laboratory, where he leads modeling of US buildings sector innovation and its implications for energy demand, consumer costs, and the power grid. Eric Wilson is a senior research engineer in the Building Technologies and Sciences Center at the National Renewable Energy Laboratory (NREL). Much of his 15-year career at NREL has revolved around modeling and analysis of the US building stock. Jared and Eric co-led the development of a National Blueprint for buildings sector innovation while serving as advisors to the US Department of Energy’s Deputy Assistant Secretary for Buildings and Industry.

Langevin, Jared↗
DOE OSTI2014

Strengthening Retrofit Markets for Comprehensive Savings in Multifamily Buildings (Interim Final Report)

Energy efficiency is vitally important in Maine. Nearly 70% of Maine households rely on fuel oil as their primary energy source for home heating, a higher share than in any other state. Coupled with the state's long, cold winters, Maine's dependence on oil renders homeowners particularly vulnerable to fluctuating fuel costs. With $\$$4.5 million in seed funding from the Energy Department's Better Buildings Neighborhood Program, the Governor's Energy Office (GEO), through Efficiency Maine Trust (the Trust), is spurring Maine landlords to lower their monthly energy bills and improve comfort for their tenants during the state's cold winter months and increasingly warmer summers. Maine's aging multifamily housing stock can be expensive to heat and costly to maintain. It is not unusual to find buildings with little or no insulation, drafty windows, and significant air leaks, making them ideal candidates for energy efficiency upgrades. Maine modeled its Multifamily Efficiency Program (MEP) after the state's highly successful Home Energy Savings Program (HESP) for single-family homes. HESP provided cash incentives and financing opportunities to owners of one-to four-unit structures, which resulted in thousands of energy assessments and whole-house energy upgrades in 225 communities. Maine's new MEP multifamily energy efficiency upgrade and weatherization initiative focuses on small to medium-sized (i.e., five to 20 units) apartment buildings. The program's energy efficiency upgrades will provide at least 20% energy savings for each upgraded multifamily unit. The Trust’s MEP relies on a network of approved program partners who help move projects through the pipeline from assessment to upgrade. MEP has two components: benchmarking and development of an Energy Reduction Plan (ERP). Using the ENERGY STAR® Portfolio Manager benchmarking tool, MEP provides an assessment of current energy usage in the building, establishes a baseline for future energy efficiency improvements, and enables tracking and monitoring of future energy usage at the building— all at no cost to the building owner. The ERP is developed by a program partner using either the Trust’s approved modeling or prescriptive tools; it provides detailed information about the current energy related conditions in the building and recommends energy efficiency, health, and safety improvements. The Trust's delivery contractor provides quality assurance and controls throughout the process. Through this effort, MEP's goal is to establish a self-sustaining, market-driven program, demonstrating the value of energy efficiency to other building owners. The increasing value of properties across the state will help incentivize these owners to continue upgrades after the grant period has ended. Targeting urban areas in Maine with dense clusters of multifamily units—such as Portland, Lewiston- Auburn, Bangor, and Augusta—MEP engaged a variety of stakeholder groups early on to design its multifamily program. Through direct emails and its website, program officials invited lending institutions, building professionals, engineering firms, equipment distributors, and local property owners associations to attend open meetings around the state to learn about the goals of the multifamily program and to help define its parameters. These meetings helped program administrators understand the diversity of the customer base: some owners are individuals with a single building, while other owners are groups of people or management companies with an entire portfolio of multifamily buildings. The diversity of the customer base notwithstanding, owners see MEP as an opportunity to make gains in their respective properties. Consistently high turnouts at stakeholder meetings fueled greater customer interest as awareness of the program spread through word of mouth. The program also gained traction by utilizing the program partner networks and building on the legacy of the Trust’s successful HESP for single-family residences. MEP offers significant incentives for building owners to participate in the upgrade program. Wholebuilding benchmarking services are available to most multifamily housing buildings free of charge. The service provides the building owner with an assessment of the building's current energy efficiency as compared to other multifamily buildings on a national scale, establishes a baseline to measure future improvements, and enables owners to track monthly energy consumption using the ENERGY STAR Portfolio Manager. Once the benchmarking process is complete, the program links building owners with approved program partners (e.g., energy professionals, home performance contractors) to identify and implement specific energy-saving opportunities in the building. Program partners can also provide project quotes with estimated financing incentives and payback period calculations that enable building owners to make informed decisions. What's more, the Trust provides two financial incentives for successful completion of program milestones. The first is a per-unit incentive for completion of an approved ERP (i.e., $\$$100 per unit if a prescriptive path is followed, and $\$$200 per unit for a modeled ERP). Upon final inspection of the installed project scope of work, an incentive of $\$$1,400 per unit or 50% of installed cost—whichever is less—is paid. The Trust originally established a $\$$1 million loan-loss reserve fund (LLRF) to further enhance financing opportunities for qualified multifamily building owners. This funding mechanism was designed to connect building owners with lenders that retain the mortgages for their properties and encourages the lenders to offer financing for energy efficiency improvements. However, there has been no interest in the LLRF and therefore the LLRF has been reduced. Ultimately, MEP plans to build an online tool for building owners to assess opportunities to make upgrades in their multifamily units. The tool will include a performance rating system to provide a way for building owners to more easily understand energy use in their building, and how it could be improved with energy efficiency upgrades. Prospective tenants will also be able to use the rating system to make informed decisions about where to rent. Furthermore, the rating can be incorporated into real estate listings as a way for prospective home buyers and the real estate financial community to evaluate a home's operating costs. The Trust’s MEP has identified the state's most experienced energy professionals, vendors, suppliers, and contractors that install energy efficiency equipment in the multifamily sector to be qualified program partners. To be eligible for partnership, energy assessment professionals and contractors are required to have demonstrated experience in the multifamily sector and hold associated professional certifications, such as Building Operator Certification (BOC), Certified Energy Manager (CEM), Professional Engineer (PE), or Building Performance Institute (BPI) Multifamily Building Analyst. Widespread program interest has enabled the Trust to redirect funds that might otherwise be needed for program promotion to building capacity through contractor training. In addition to boosting professional training and certification opportunities, MEP teaches its partners how to market the multifamily program to prospective multifamily homeowners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Simulation Analyses in Support of DOE’s Fossil Fuel Rule for Single Component Equipment and Lighting Replacements

At the request of the US Department of Energy’s (DOE) Federal Energy Management Program (FEMP), Pacific Northwest National Laboratory (PNNL) conducted a series of building energy simulations using a large office model to investigate the potential savings that could be accrued from a typical chiller, boiler, or lighting replacement in a Federal office building. FEMP’s interest was in knowing whether or not single component replacements like these would have any chance of achieving the fossil- fuel-based energy consumption reduction requirements specified in Section 433 of the Energy Independence and Security Act (EISA) of 20071. Specifically, FEMP was interested in whether an older Federal building, built in the 1980s or 1990s and designed to meet energy standards in place at the time the building was designed, could meet the requirements of Section 433 of EISA for renovations. Many single component renovations like chiller replacements, boiler replacements, and lighting retrofits may meet the minimum cost requirement of Section 433 of EISA but may not offer any opportunity to achieve fossil-fuel-generated energy consumption reductions on the order of 55% or more. If single component renovations such as these would not achieve the necessary reductions, then FEMP would consider modifying rules based on Section 433 of EISA to exempt these types of single component renovations from the overall fossil-fuel-generated energy consumption reduction provisions. FEMP would instead require Federal agencies to ensure that these renovations use FEMP-designated efficiencies for chillers and boilers or the lighting power density requirements found in ASHRAE Standard 90.1-2010. The results of PNNL’s analysis indicated that it is unlikely that a combined boiler and chiller replacement, or an individual boiler or chiller replacement in an older existing Federal building would meet the requirements of Section 433 of EISA. While buildings can achieve up to 34% reduction in cooling and 11% reduction in heating load with this type of retrofit, these savings fall well short of the minimum savings specified in Section 433 of EISA. Similarly, a lighting retrofit in an older existing Federal building would also not likely meet the requirements of Section 433 of EISA. While buildings can save up to 52% on lighting loads, the whole buildings savings would be well short of the minimum savings specified in Section 433 of EISA.

Halverson, Mark A.↗
DOE OSTI2014

Energy Evaluation of a New Construction Pilot Community: Fresno, California

A new construction pilot community was constructed by builder-partner Wathen-Castanos Hybrid Homes (WCHH) based on a single occupied test house that was designed to achieve greater than 30% energy savings with respect to the House Simulation Protocols (Hendron, Robert; Engebrecht, Cheryn (2010). Building America House Simulation Protocols. Golden, CO: National Renewable Energy Laboratory). Builders face several key problems when implementing a whole-house systems integrated measures package (SIMP) from a single test house into multiple houses. Although a technical solution already may have been evaluated and validated in an individual test house, the potential exists for constructability failures at the community scale. This report addresses factors of implementation and scalability at the community scale and proposes methodologies by which community-scale energy evaluations can be performed based on results at the occupied test house level. Research focused on the builder and trade implementation of a SIMP and the actual utility usage in the houses at the community scale of production. Five occupants participated in this community-scale research by providing utility bills and information on occupancy and miscellaneous gas and electric appliance use for their houses. IBACOS used these utility data and background information to analyze the actual energy performance of the houses. Verification with measured data is an important component in predictive energy modeling. The actual utility bill readings were compared to projected energy consumption using BEopt with actual weather and thermostat set points for normalization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Evaluating the Thermal Performance of Mass Walls Compared to Wood-Framed and Steel-Framed Walls in Residential Buildings using EnergyPlus

While homes across the United States are traditionally built using wood-frame construction, mass or concrete walls are popular in certain regions of the country. While, mass walls have certain obvious advantages in terms of energy efficiency compared to the lighter wood-frame or steel-frame walls, conducting hotbox tests and specialized thermal modelling analyses of these walls to evaluate energy performance is often time-consuming and cost-prohibitive. More importantly, heat transfer in real buildings is a dynamic process consisting of the effects of outdoor air temperature and solar gains in conjunction with infiltration and internal gains. These are not captured through isolated hotbox tests or modelling techniques. The latest state-of-art building energy simulation tools can be utilized to overcome these constraints. This paper describes a comprehensive analysis of different wall types using EnergyPlus. The methodology for modelling various wood, steel and mass walls and the development of material properties for use in simulation is described. An overview of the large-scale simulation structure used in the analysis is provided. Resulting energy consumption for various mass walls is included along with a comparison of select mass walls and wood-frame or steel-frame walls.

Mass walls, Large-scale simulation, residential bu↗
DOE OSTI2020

Probabilistic Power Consumption Modeling for Commercial Buildings Using Logistic Regression Markov Chain

The total energy consumed by buildings takes up to 40% of U.S. energy use, in which a large portion is contributed by commercial buildings. Building performance optimization is desirable but requires accurate building models with uncertainties taken into account. This paper proposes a novel probabilistic modeling method using Logistic Regression Markov Chain (LRMC). The LRMC model enhances the performance of traditional Markov Chain (MC) models by adopting time-variant transition matrices calibrated using logistic regression with exogenous inputs. Compared with existing building models, the proposed model produces accurate multi-step modeling results with full probability distribution. The proposed probabilistic building model is tested using actual commercial building measurements and modeling performance is evaluated with two probabilisitc metrics. The results show that the LRMC model has higher accuracy than traditional MC model and Logistic Regression (LR) model in that it yields lower error scores under both evaluation metrics.

Building modeling↗
DOE OSTI2013

Retrofitting Vegas: Implementing Energy Efficiency in Two Las Vegas Test Homes

In 2009, the state of Nevada received nearly forty million dollars in Neighborhood Stabilization Funds from the Department of Housing and Urban Development. The purpose of this funding was to stabilize communities that have suffered from foreclosures and abandonment. In an effort to provide guidance to local officials and maximize how effectively this NSP funding is utilized in retrofitting homes, CARB provided design specifications, energy modeling, and technical support for the Building America Retrofit Alliance (BARA) team and its local partners - Better Building Performance, Nevada Energy Star Partners Green Alliance, and Home Free Nevada - for two retrofit test homes. One home was to demonstrate a modest retrofit and the other a deep energy retrofit. Through this project, CARB has provided two robust solution packages for retrofitting homes built in this region between the 1980s and early 1990s without substantially inconveniencing the occupants. The two test homes, the Carmen and Sierra Hills, demonstrate how cost-effectively energy efficient upgrades can be implemented in the hot, dry climate of the Southwest. In addition, the homes were used as an educational experience for home performance professionals, building trades, remodelers, and the general public. In-field trainings on air-sealing, HVAC upgrades, and insulating were provided to local contractors during the retrofit and BARA documented these retrofits through a series of video presentations, beginning with a site survey and concluding with the finished remodel and test out.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗