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At least 1,333 records · Page 74

All sources NASA NTRS DOE OSTI

DOE OSTI2018

Implementing Nationally Determined Contributions: Building Energy Policies in India’s Mitigation Strategy

The Nationally Determined Contributions (NDCs) are allowing countries to examine options for reducing emissions through a range of domestic policies. Here we use the Global Change Assessment Model to demonstrate the potential impacts of energy policies and discuss strategies to implement India’s NDC with a focus on the buildings sector. Buildings are the largest end-use sector globally, and building energy consumption is expected to increase as income grows in developing countries. We find that implementing a range of energy efficiency policies robustly can reduce total Indian building energy use by 22% and lower total Indian carbon dioxide emissions by 9% in 2050 compared to the business as usual scenario. Among various policies, energy codes for new buildings can result in the most significant savings. For all energy efficiency policies, well-coordinated, consistent implementation is critical, which requires coordination across different departments and agencies, improving capacity of stakeholders, and developing appropriate institutions to facilitate policy implementation. Renewable energy deployment can also reduce carbon emissions from buildings, and incentives in the short term are important to ensuring strong market uptake. Effective development and implementation of building energy policies could help avoid lock-in of carbon-intensive infrastructure, while improving living standards and generating health benefits.

Yu, Sha↗

DOE OSTI2022

Commercial Building Planning and Retrofitting Strategy for Grid Services

The increasing integration of distributed energy resources (DERs) plays an important role in improving energy consumption efficiency. In September 2020, the Federal Energy Regulatory Commission (FERC) approved Order 2222 which opens wholesale electricity markets to small capacity DERs. The benefit of this new FERC Order 2222 is that DERs, such as rooftop solar panels and batteries, will be able to participate in regional electricity markets and provide grid services. Meanwhile, the planning and operation strategies of DERs are facing new challenges to account for the impact of the wholesale market with numerous uncertainty factors. Therefore, in this paper, we propose a new planning and retrofitting model for long-term commercial buildings that considers both DER investment and market participation. Specifically, we explore the capability of implementing DERs for grid services. The effectiveness of the proposed model is validated using real-world data. Simulation results also validate that participating in grid services can significantly increase revenues through appropriate building energy management and shorten the payback period of DER investments.

building energy management↗

DOE OSTI2021

Urban cells: Extending the energy hub concept to facilitate sector and spatial coupling

The rapid growth of urban areas and concerns over climate change make it vital to improve the energy sustainability of cities. Understanding the complex interactions within different sectors (sectoral) and localities (spatial) of cities plays a crucial role in improving efficiency and sustainability, which is extremely challenging due to the complex urban morphology. State-of-the-art energy concepts do not facilitate a detailed consideration of both sectoral and spatial coupling that energy infrastructure maintains at the urban scale. This has become a significant challenge when designing interconnected urban energy infrastructure. The Urban Cell concept is introduced to address this bottleneck. A novel computational model using a modular approach is introduced to create an interconnected urban infrastructure, including the energy, building, and transportation sectors. Optimal sizing of the distributed energy system (including renewables, energy storage, and dispatchable sources) and optimal urban morphology is determined within a modular unit. A game-theoretic approach is used to model the interactions between urban cells (modular units). The study revealed that the urban cell concept can reduce the net present value of the interconnected energy infrastructure by 37% while increasing the installed renewable energy capacity by 25%. This demonstrates the benefit potential of urban cells and the importance of considering interactions between different sectors and different parts within a city. The Urban Cell concept can be used to present the complex interactions maintained within a city.

Perera, ATD↗

NASA NTRS2010

Effects of Solar Photovoltaic Panels on Roof Heat Transfer

Building Heating, Ventilation and Air Conditioning (HVAC) is a major contributor to urban energy use. In single story buildings with large surface area such as warehouses most of the heat enters through the roof. A rooftop modification that has not been examined experimentally is solar photovoltaic (PV) arrays. In California alone, several GW in residential and commercial rooftop PV are approved or in the planning stages. With the PV solar conversion efficiency ranging from 5-20% and a typical installed PV solar reflectance of 16-27%, 53-79% of the solar energy heats the panel. Most of this heat is then either transferred to the atmosphere or the building underneath. Consequently solar PV has indirect effects on roof heat transfer. The effect of rooftop PV systems on the building roof and indoor energy balance as well as their economic impacts on building HVAC costs have not been investigated. Roof calculator models currently do not account for rooftop modifications such as PV arrays. In this study, we report extensive measurements of a building containing a flush mount and a tilted solar PV array as well as exposed reference roof. Exterior air and surface temperature, wind speed, and solar radiation were measured and thermal infrared (TIR) images of the interior ceiling were taken. We found that in daytime the ceiling surface temperature under the PV arrays was significantly cooler than under the exposed roof. The maximum difference of 2.5 C was observed at around 1800h, close to typical time of peak energy demand. Conversely at night, the ceiling temperature under the PV arrays was warmer, especially for the array mounted flat onto the roof. A one dimensional conductive heat flux model was used to calculate the temperature profile through the roof. The heat flux into the bottom layer was used as an estimate of the heat flux into the building. The mean daytime heat flux (1200-2000 PST) under the exposed roof in the model was 14.0 Watts per square meter larger than under the tilted PV array. The maximum downward heat flux was 18.7 Watts per square meters for the exposed roof and 7.0 Watts per square meters under the tilted PV array, a 63% reduction due to the PV array. This study is unique as the impact of tilted and flush PV arrays could be compared against a typical exposed roof at the same roof for a commercial uninhabited building with exposed ceiling and consisting only of the building envelope. Our results indicate a more comfortable indoor environment in PV covered buildings without HVAC both in hotter and cooler seasons.

Dominguez, A.↗

DOE OSTI2022

Automated fault detection and diagnosis deployment Internet of Things solution for building energy system

The building sector is the highest energy consumer and ranks first in terms of carbon emissions among all sectors. To address these issues, decarbonization and electrification in the building energy sector are two critical missions of the new US administration. For decarbonization, the new administration has set a target to reduce greenhouse gas emissions by 50–52% by 2030 and targeting a carbon-neutral economy by 2050. For electrification, the goal is to achieve 100% clean electricity by 2035. Such decarbonization and electrification in the building sector require that energy consumption in buildings be reduced significantly. Therefore, the building sector must continuously adopt new technologies to achieve its energy and carbon emission goals. One of the most fundamental technologies is the Internet of Things (IoT). IoT has proven to be an effective solution for the building domain, including building information/energy modeling, smart buildings, etc. Although much progress has been made in the development of IoT-based building energy systems, there is still a lack of reliable, scalable, and affordable IoT-based automated fault and degradation diagnostic (AFDD) solutions. Such solutions would enable deployment of advanced algorithms into real systems to archive the projected energy benefits. Here, this study reviews existing IoT solutions developed for building energy–related application and developed a simple but effective AFDD IoT deployment solution, including developing a suitable IoT architecture and conducting easy and scalable deployment by leveraging a common cloud-based IoT service.

42 ENGINEERING↗

DOE OSTI2022

Connected Loads – Grid Connected Appliances: Deployment IoT Solution for Fault Detection and Diagnostics

As one of the most energy-intensive end-uses in the commercial buildings sector, supermarkets consume around 50 kWh/ft 2 ( or 537.6 kWh/m 2 ) of electricity annually, or more than 2 million kWh of electricity per year for a typical store. The biggest consumer of energy in a supermarket is its refrigeration system, which accounts for 40–60% of its total electricity usage and is equivalent to about 2–3% of the total energy consumed by commercial buildings in United States, or around 0.5 quadrillion Btu (or 0.53 quadrillion KJ). Also, the supermarket refrigeration system is one of the biggest consumers of refrigerants. Current supermarket refrigeration systems rely on high global warming potential hydrofluorocarbon refrigerants. Reducing refrigerant usage or using environment friendly alternatives can result in significant climate benefits. Transcritical CO2 refrigeration systems have attracted more attention in recent years because of their zero-carbon emission advantages compared with traditional refrigerants. These systems are widely used in commercial buildings such as supermarkets. The refrigeration system can also be adapted to handle flexible building loads and be integrated into grid response transactive control to balance the supply and demand of the electric grid. Even minor improvements in the efficiency and operational reliability of supermarket refrigeration systems can create significant value in terms of saving energy, improving food quality, protecting the environment, reducing carbon footprint, and enhancing electric grid resilience. For decarbonization, the new administration has set a target to reduce greenhouse gas emissions by 50– 52% by 2030 and targeting a carbon-neutral economy by 2050. For electrification, the goal is to achieve 100% clean electricity by 2035. Such decarbonization and electrification in the building sector require that energy consumption in buildings be reduced significantly. Therefore, the building sector must continuously adopt new technologies to achieve its energy and carbon emission goals. One of the most fundamental technologies is the Internet of Things (IoT). IoT has proven to be an effective solution for the building domain, including building information/energy modeling, smart buildings, etc. Although much progress has been made in the development of IoT-based building energy systems, there is still a lack of reliable, scalable, and affordable IoT-based automated fault and degradation diagnostics (AFDDs) solutions. Such solutions would enable deployment of advanced algorithms into real systems to archive the projected energy benefits. This study reviews existing IoT solutions developed for building energy– related application and developed a simple but effective AFDD IoT deployment solution, including developing a suitable IoT architecture and conducting easy and scalable deployment by leveraging a common cloud-based IoT service.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

An Efficient Bayesian Method for Advancing the Application of Deep Learning in Earth Science

Despite their wide and successful applications, deep learning (DL) models are prone to overfitting for small training datasets, produce a poor predictive performance for uncertain data, and provide point estimations without any indication of the accuracy and credibility. These limitations of the deterministic DL models hinder their effective application in Earth system science where the labelled data are sparse, noisy and incomplete with large uncertainty and where the predictive uncertainty quantification is needed for scientific understanding and policy decision making. Integration of Bayesian inference into DL models adds an estimate of uncertainty and regularization in the predictions. However, traditional Bayesian methods are computationally unaffordable and inflexible for high-dimensional problems, which limits their application to DL systems that typically have millions of model parameters. In this effort, we propose an efficient and general-purpose Bayesian inference method to advance DL model optimization and uncertainty quantification, so as to facilitate the adoption of DL in Earth sciences. In a demonstration, we integrate the proposed Bayesian method with a feedforward neural network (NN) to build a fast-to-evaluate surrogate of the complex Energy Exascale Earth System Land Model for efficient modeling. The formulated Bayesian NN, using a small number of training data, produces an accurate prediction with high credibility, whereas with the same small training size, the deterministic NN cannot yield a reasonable estimation and does not provide confidence information. The proposed Bayesian method is computationally efficient and flexible, capable of integration with diverse network variants such as convolutional NNs and recurrent NNs to advance the application of DL in Earth sciences.

Lu, Dan↗

DOE OSTI2019

Annual Energy Savings and Peak Power Reduction Simulated for CCHP Design and Baseline HP in Cold Climate Cities

This report assesses energy savings and peak power reduction of three heat pumps in multiple US cold climate cities and building types. The three heat pumps comprise a baseline heat pump and two high efficiency cold climate heat pumps (CCHP). The DOE/ORNL Heat Pump Design Model was used to simulate the heat pumps and generate performance curves for EnergyPlus building energy simulations. The annual energy simulations were performed over seven cold climates: 1) Minneapolis, MN; 2) Duluth, MN; 3) Fairbanks, AK; 4) Helena, MT; 5) Indianapolis, IN; 6) Peoria, IL and 7) Eagle County, CO. In order to assess impact of residential building types matching different energy codes, we simulated six single-family houses in Indianapolis, IN, including : 1) single-family house having a crawlspace; 2) having a slab foundation; 3) having a heated basement; 4) having an unheated basement; 5) one single-family house having a heated basement matching IECC code of 2009, 6) and one single-family house having a heated basement matching IECC code of 2012. The former 4 houses match the IECC 2006 code.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Discomfort glare with complex fenestration systems and the impact on energy use when using daylighting control

Glare is a frequent issue in highly glazed buildings. A modelling approach is presented that uses discomfort glare probability and discomfort glare index as metrics to determine occupants’ behaviour. A glare control algorithm that actuated an interior shade for glare protection based on the predicted perception was implemented in a building simulation program. A reference case with a state-of-the-art base glazing was compared to the same glazing but with five different complex fenestration systems, i.e., exterior shades. The windows with exterior shades showed significant variations in glare frequencies. Energy use intensity in a prototypical office building with daylighting controls was greatly influenced for the systems with frequent glare occurrence. While the base glazing could benefit from glare control, some of the exterior shades showed significantly greater energy use when discomfort glare-based operation of interior shades was considered.

Hoffmann, Sabine↗

DOE OSTI2023

Verification of a Modeling Toolkit for the Design of Building Electrical Distribution Systems

DC electrical distribution systems offer many potential advantages over their AC counterparts. They can facilitate easier integration with distributed energy resources, improve system energy efficiency by eliminating AC/DC converters at end-use devices (e.g., laptop chargers), and reduce installation material, time, and cost. However, DC electrical distribution systems present additional design considerations, largely resulting from potentially greater magnitude and variation in cable losses. Modeling and simulation are rarely used to design such systems. However, the greater dependency of DC system energy efficiency on design choices such as distribution voltages, architecture, and integration of PV and BESS suggests that modeling and simulation may be required. Such system performance analysis is currently not a standard practice, in part due to limited availability and validation of capable software tools. This paper characterizes the accuracy of a Modelica-based Building Electrical Efficiency Analysis Model (BEEAM) toolkit, as a precursor for validating its use to perform system performance analysis and inform design decisions. The study builds upon previous verification research by characterizing complete systems comprised of commercially available equipment, and providing a more detailed analysis of simulation results. Five lighting systems with varying electrical distribution architectures were designed using market-available equipment, installed in a laboratory environment, modeled using BEEAM, and simulated using three Modelica integrated development environments (IDEs). Simulated and measured results were compared to characterize toolkit accuracy. Initial results revealed that simulated performance was mostly within ±5% of measured system-level and device-level performance. While simulation results were not found to be dependent on the IDE, some Modelica compiler interoperability issues were identified. Although the BEEAM toolkit showed promise for the targeted use case, further work is needed to determine whether the demonstrated 5% accuracy is sufficient for making real-world design decisions, and for BEEAM to advance from an interesting research tool to one that can impact real-world building projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings

As utility electricity rates evolve, pairing solar photovoltaic (PV) systems with battery storage has potential to ensure the value proposition of residential solar by mitigating economic uncertainty. In addition to batteries, load control technologies can reshape customer load profiles to optimize PV system use. The combination of PV, energy storage, and load control provides an integrated approach to PV deployment, which we call 'solar plus'. The U.S. National Renewable Energy Laboratory's Renewable Energy Optimization (REopt) model is utilized to evaluate cost-optimal technology selection, sizing, and dispatch in residential buildings under a variety of rate structures and locations. The REopt model is extended to include a controllable or 'smart' domestic hot water heater model and smart air conditioner model. We find that the solar plus approach improves end user economics across a variety of rate structures - especially those that are challenging for PV - including lower grid export rates, non-coincident time-of-use structures, and demand charges.

14 SOLAR ENERGY↗

DOE OSTI2025

Including Physics-Informed Atomization Constraints in Neural Networks for Reactive Chemistry

Machine learning interatomic potentials (MLIPs) have emerged as powerful tools for investigating atomistic systems with high accuracy and a relatively low computational cost. However, a common and unaddressed challenge with many current neural network (NN) MLIP models is their limited ability to accurately predict the relative energies of systems containing isolated or nearly isolated atoms, which appear in various reactive processes. To address this limitation, we present a mathematical technique for modifying any existing atom-centered NN architecture to account for the energies of isolated atoms. The result produces a consistent prediction of the atomization energy (AE) of a system using minimal constraints on the model. Using this technique, we build a model architecture that we call hierarchically interacting particle neural network (HIP-NN)-AE, an AE-constrained version of the HIP-NN, as well as ANI-AE, the AE-constrained version of the accurate NN engine for molecular energies (ANI). Our results demonstrate AE consistency of AE-constrained models, which drastically improves the AE predictions for the models. We compare the AE-constrained approach to unconstrained models as well as models from the literature in other scenarios, such as bond dissociation energies, bond dissociation pathways, and extensibility tests. These results show that the constraints improve the model performance in some of these tasks and do not negatively affect the performance on any tasks. The AE constraint approach thus offers a robust solution to the challenges posed by isolated atoms in energy prediction tasks.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2013

Energy Retrofit Field Study and Best Practices in a Hot-Humid Climate

Energy efficiency improvement as a component of comprehensive renovation was investigated under U.S. Department of Energy (DOE) funding of the Building America Partnership for Improved Residential Construction (BA-PIRC). Researchers at the Florida Solar Energy Center (FSEC) worked with affordable housing partners renovating foreclosed homes built from the 1950's through the 2000's in the hot-humid climate (within the Southern census region), primarily in Florida. Researchers targeted a 30% improvement in whole-house energy efficiency along with the health and safety, durability, and comfort guidelines outlined in DOE's Builders Challenge Program (Version 1) Quality Criteria.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Developing Near Optimal Control Sequences for Chiller Plants with Water-side Economizers: A Case Study in a Warm and Marine Climate

Various advanced control sequences for chiller plants with water-side economizers (WSE) have been proposed in literature, but the optimization of those controls is limited. It is possible to maximize energy savings by developing near-optimal control sequences, which are dependent on several factors such as the load profile. To address these gaps, we first identify an advanced control sequence and three key control parameters for chiller plants with WSE. Next, optimizations are performed to minimize energy consumption for seven combinations of control parameters. A chiller plant with WSE system in a warm and marine climate is studied and two load profiles are considered. The system and controls are modeled using the Modelica Buildings library. The results show optimizing the selected control parameters can reduce energy consumption by up to 11% depending on the load profile. Specifically, optimizing the cooling tower efficiency threshold in the condenser water reset control can significantly reduce energy savings for the variable load profile by efficiently shifting the load from the cooling tower to the chiller. This paper provides practical guidance for developing near-optimal control sequences for chiller plant with WSE systems considering impacts such as the load profile.

chiller plant↗

DOE OSTI2025

Akiachak Energy Efficiency Retrofit Project

The goal of the project is to reduce the overall energy use of the Akiachak Native Community (ANC) by implementing energy efficiency measures in five high-use Tribal buildings. This project will have the following outcomes: Projected annual energy savings of $17,369; projected annual reduction in fuel oil #1 of 1,200 gallons and electricity of 17,751 kWh; annual reduction in carbon dioxide emissions of approximately 60,340 pounds/year. ANC will install energy efficiency measures in the Laundry, Tribal Indian Reorganization Act (IRA) Office, Clinic, Daycare, and Police Station. ANC obtained energy audits on these buildings in 2018, and this project will implement high-payback recommendations such as replacing lighting with LEDs, installing setback thermostats and occupancy sensors, replacing furnaces with more efficient models, replacing the circulation pumps with variable speed ones, air tightening, and adding insulation. Buildings will see energy cost reductions from 15% to 40%. These retrofits will help build ANC’s long-term vision for sustainable energy usage and address the first goal of the Tribal IRA Council’s Energy Efficiency and Conservation Strategy, to “create and maintain functionally appropriate, sustainable, accessible, high quality tribal infrastructure and facilities.” ANC intends to replicate this project by using the resulting energy savings to address audit recommendations in other buildings as well as to demonstrate the value of energy efficiency to community members. Other outcomes will include an increase in community resiliency, reduced dependence on outside shipments of fuel oil, training for maintenance staff, and no-touch control of building appliances to reduce transmission of diseases such as COVID-19.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Guide to Determining Climate Zone by County: Building America and IECC 2021 Updates

This report describes the climate zone designations used by the U.S. Department of Energy (DOE) Building America Program. The report aims to help residential building stakeholders identify the appropriate climate zone designation for each county in the United States, including Hawaii and Alaska. Identifying the correct climate zone is important for many activities including residential construction projects, code compliance, energy analysis and modeling, and other analytical activities where climate zones impact the energy and moisture performance of residential buildings. This report supersedes the previous Building America publication: Guide to Determining Climate Regions by County, published in 2010. This report reflects climate designations used by the International Code Council (ICC) in the 2021 versions of the International Energy Conservation Code (IECC), the International Residential Code (IRC), and other codes produced by ICC. The information provided here and associated data should be used for the most up-to-date information regarding climate zone designations in the United States.

2021 IECC↗

DOE OSTI2022

Towards Energy-Positive Buildings through a Quality-Matched Energy Flow Strategy

Current strategies for net-zero buildings favor envelopes with minimized aperture ratios and limiting of solar gains through reduced glazing transmittance and emissivity. This load-reduction approach precludes strategies that maximize on-site collection of solar energy, which could increase opportunities for net-zero electricity projects. To better leverage solar resources, a whole-building strategy is proposed, referred to as “Quality-Matched Energy Flows” (or Q-MEF): capturing, transforming, buffering, and transferring irradiance on a building’s envelope—and energy derived from it—into distributed end-uses. A mid-scale commercial building was modeled in three climates with a novel Building-Integrated, Transparent, Concentrating Photovoltaic and Thermal fenestration technology (BITCoPT), thermal storage and circulation at three temperature ranges, adsorption chillers, and auxiliary heat pumps. BITCoPT generated electricity and collected thermal energy at high efficiencies while transmitting diffuse light and mitigating excess gains and illuminance. The balance of systems satisfied cooling and heating demands. Relative to baselines with similar glazing ratios, net electricity use decreased 71% in a continental climate and 100% or more in hot-arid and subtropical-moderate climates. Total EUI decreased 35%, 83%, and 52%, and peak purchased electrical demands decreased up to 6%, 32%, and 20%, respectively (with no provisions for on-site electrical storage). Decreases in utility services costs were also noted. These results suggest that with further development of electrification the Q-MEF strategy could contribute to energy-positive behavior for projects with similar typology and climate profiles.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Building America Case Study: Southern Energy Homes, First DOE Zero Energy Ready Manufactured Home, Russellville, Alabama

Three side-by-side lab houses were built, instrumented and monitored in an effort to determine through field testing and analysis the relative contributions of select technologies toward reducing energy use in new manufactured homes.The lab houses in Russellville, Alabama compared the performance of three homes built to varying levels of thermal integrity and HVAC equipment: a baseline HUD-code home equipped with an electric furnace and a split system air conditioner; an ENERGY STAR manufactured home with an enhanced thermal envelope and traditional split system heat pump; and a house designed to qualify for Zero Energy Ready Home designation with a ductless mini-split heat pump with transfer fan distribution system in place of the traditional duct system for distribution. Experiments were conducted in the lab houses to evaluate impact on energy and comfort of interior door position, window blind position and transfer fan operation. The report describes results of tracer gas and co-heating tests and presents calculation of the heat pump coefficient of performance for both the traditional heat pump and the ductless mini-split. A series of calibrated energy models was developed based on measured data and run in three locations in the Southeast to compare annual energy usage of the three homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗