Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “building energy simulation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Ten questions concerning agent-based modeling of occupant behavior for energy and environmental performance of buildings

We report the complexity of occupant behavior is one of the major contributors to uncertainty in building performance simulation. Agent-based modeling (ABM), a computational simulation technique, has gained attention in the occupant modeling field due to its capability and flexibility to capture the heterogeneity and dynamics of human behavior and the emergent effects. While multiple efforts in the past decade have demonstrated the usefulness of the ABM approach for simulating occupants and their impacts on building performance, several crucial matters in the ABM research still remain unexplored. This paper presents ten questions that highlight the most important issues regarding ABM research and applications for occupant behavior in the context of building performance simulation. The questions and answers aim to provide insights into current and future ABM research, and more importantly to inspire new significant questions from young researchers in the field. This research is part of the IEA EBC Annex 79 project, occupant-centric building design and operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Refining seasonal performance metrics for room air-conditioning in emerging markets: Integrating building simulations with real-world equipment performance data

Buildings significantly impact worldwide energy consumption, emphasizing the need to reduce the cooling energy demand, especially in warm climates. Minimum energy performance standards (MEPS) and seasonal performance metrics such as the Cooling Seasonal Performance Factor (CSPF) are crucial for improving room air conditioning (RAC) efficiency. However, challenges remain, particularly in emerging markets like Brazil, where seasonal performance metrics have recently been introduced. This study assesses the factors influencing country-level seasonal efficiency metrics and proposes a framework to refine these calculations by considering local climates and expected RAC usage in real-world households via building simulations. Key considerations include outdoor air temperature binning for different climates, RAC usage patterns (i.e., daytime and nighttime usages), envelope thermal performance of households, and urban heat island (UHI) effects. The results reveal that CSPF values can vary significantly based on climate conditions, with observed CSPF ranging from 4.10 to 11.59 Wh/Wh across 577 Brazilian climates. The inclusion of UHI effects led to a reduction in CSPF values by up to 29% during nighttime operations in hot urban areas. Additionally, building envelope efficiency showed contrasting impacts on RAC performance, with CSPFs reaching up to 15.35 Wh/Wh under specific optimized conditions. These findings highlight the need for transparent policymaking in RAC performance databases, facilitating the application of approaches like those proposed in this study and supporting diverse stakeholders in decision-making.

Bavaresco, Mateus↗
DOE OSTI2020

Power Grid Simulation Testbed for Transactive Energy Management Systems

To effectively engage demand-side and distributed energy resources (DERs) for dynamically maintaining the electric power balance, the challenges of controlling and coordinating building equipment and DERs on a large scale must be overcome. Although several control techniques have been proposed in the literature, a significant obstacle to applying these techniques in practice is having access to an effective testing platform. Performing tests at scale using real equipment is impractical, so simulation offers the only viable route to developmental testing at scales of practical interest. Existing power-grid testbeds are unable to model individual residential end-use devices for developing detailed control formulations for responsive loads and DERs. Furthermore, they cannot simulate the control and communications at subminute timescales. To address these issues, this paper presents a novel power-grid simulation testbed for transactive energy management systems. Detailed models of primary home appliances (e.g., heating and cooling systems, water heaters, photovoltaic panels, energy storage systems) are provided to simulate realistic load behaviors in response to environmental parameters and control commands. The proposed testbed incorporates software as it will be deployed, and enables deployable software to interact with various building equipment models for end-to-end performance evaluation at scale.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

MBMS1.0: An Open-Source Code for Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery

Membrane-based dehumidification is currently being considered as a promising solution for the building application due to its low cost and very limited energy consumption. Developing a simple and efficient open-source code simulation tool is important for boosting the optimization and evaluation of such device in HVAC community. This paper reports a first-order physics based model which accounts for the fundamental heat and mass transfer of humid-air vapor at feed side to flow stream at permeate side. The current model comprises two membrane mass transfer submodels (i.e. microstructure model and performance map model); and it adopts a segment-by-segment methodology for discretizing heat and mass transfer governing equations. The model is capable of simulating both dehumidifiers and energy recovery ventilators with parallel-flow cross-flow, and counter-flow configurations. The model was validated with the measurements at appropriate device. The practices in dehumidification and energy recovery exchangers are also discussed. The model and open-source codes are expected to become a solid fundament for developing a more comprehensive and accurate membrane-based dehumidification in the future.

Gao, Zhiming↗
DOE OSTI2023

Maximum-impact Adversary Design for Network-based Control System: A Case Study on Grid-interactive Efficient Buildings

The Internet of Things (IoT) technology has dramatically improved the efficiency of today's building operation and management. By connecting controllable devices into a communication network, control signals can be easily passed to the devices, and operating status can be acquired from measurable ends with minimal effort. However, this all-connected configuration could also expose the network-based control system (NBCS) to malicious actions, such as cyberattacks. One of the common NBCSs is the building automation system. With the promotion of grid-interactive efficient buildings (GEBs), there has been increasing attention on securing the buildings from the network perspective. This research proposes a maximum-impact adversary design framework so that the adversary can provide the most adversarial impact on the controlled system while remaining stealthy. The proposed framework is numerically demonstrated on a network-based building energy and control system. The building energy system is built in a Modelica-based simulation environment and controlled by the state-of-the-art ASHRAE Guideline 36 control sequences. The control commands at the supervisory level, generated from the Guideline 36 controller, are assumed to be sent to local devices through communication networks using the BACnet protocol. Simulation results show that the proposed maximum-impact adversary on such a system can stealthily affect the building system's performance to its maximum extent. It is anticipated that results can be used by researchers and practitioners in the building automation industry to design efficient and robust cyber-attack detection algorithms, especially for stealthy attacks.

Chu, Mengyuan↗
DOE OSTI2022

Performance analysis of novel thermal storage integrated heat pump system in a residential building at the hot climate for demand flexibility

A novel thermal energy storage integrated heat pump system was proposed to reshape the electricity load profile of residential buildings while maintaining thermal comfort. High-fidelity computer simulations are needed for evaluating the feasibility of the proposed system. This study investigates the annual performance of the proposed system through Modelica-based system simulations. A rule-based control strategy was developed to shift the electric demand of a typical single-family house in Atlanta, GA from peak to off-peak hours to utilize the Time-of-Use electricity rate to lower the energy costs for conditioning the building. For comparison, a conventional air-source heat pump system serving the same building was also developed. Simulation results indicate that the proposed system is capable of shifting around 90% of the building's electricity consumption for meeting the thermal demand from peak to off-peak hours on a daily basis. In addition, the annual power consumption and operating cost for running the HVAC system can be reduced by 6% and 34%, respectively, compared with the conventional air-source heat pump.

Shi, Liang↗
DOE OSTI2023

Comprehensive Analysis of Model Parameter Uncertainty Influence on Evaluation of HVAC Operation to Mitigate Indoor Virus: A Case Study for an Office Building in a Cold and Dry Climate

Simulation-based studies of HVAC operation to mitigate indoor virus have been conducted to understand tradeoffs between indoor air quality (IAQ) and energy consumption. However, the influence of model parameter uncertainty in these studies has not been systematically quantified, which is critical when providing guidance to building operators. To address this gap, we identify 20 model parameters for a typical medium office building system in a cold and dry climate that can influence IAQ and energy consumption for indoor virus scenarios. Next, the distributions of the parameter values are estimated from literature and a set of simulation samples for three representative days is generated that simultaneously sample all of the parameters from their distributions. Two HVAC virus mitigation strategies are studied: increased filtration using MERV 13 filters and increased ventilation, via supply of 100% outdoor air into buildings. The model parameter uncertainty leads to significant variability in the results, particularly for the IAQ because of the highly uncertain virus generation rate. Use of 100% outdoor air can be beneficial for some uncertain scenarios on the hot day, but shows less IAQ improvement and/or significant energy increases on the other days. The virus removal efficiency and pressure drop of the HVAC filter, fan efficiency, and internal heat gain are the most important parameters to determining the tradeoffs of the two strategies. Our results demonstrate how this model parameter uncertainty analysis methodology can provide practical guidance to building operators.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Defining weather scenarios for simulation-based assessment of thermal resilience of buildings under current and future climates: A case study in Brazil

In response to increasingly severe weather conditions, optimization of building performance and investment provides an opportunity to consider co-benefits of thermal resilience during energy efficiency retrofits. This work aims to assess thermal resilience of buildings using building performance simulation to evaluate the indoor overheating risk under nine weather scenarios, considering historical (2010s), mid-term future (2050s), and long-term future (2090s) typical meteorological years, and heat wave years. Such an analysis is based on resilience profiles that combine six integrated indicators. A case study with a district of 92 buildings in Brazil was conducted, and a combination of strategies to improve thermal resilience was identified. Results reflect the necessity of planning for resilience in the context of climate change. This is because strategies recommended under current conditions might not be ideal in the future. Therefore, an adaptable design should be prioritized. Cooling energy consumption could increase by 48 % by the 2050s, while excessive overheating issues could reach 37 % of the buildings. Simple passive strategies can significantly reduce the heat stress. A comprehensive thermal resilience analysis should ultimately be accompanied by a thorough reflection on the stakeholders’ objectives, available resources, and planning horizon, as well as the risks assumed for not being resilient.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Occupant-Centric key performance indicators to inform building design and operations

Building performance indicators are widely used to guide building design and track and benchmark operational performance. Traditional building performance indicators mostly focus on the energy efficiency perspective. As occupants are the primary building service recipients in residential and most commercial buildings, their comfort and wellbeing are crucial. As such, this study first identified significant attributes of occupant-centric key performance indicators (KPIs) and analyzed the diverse factors that should be considered in formulating an occupant-centric KPI. Then a suite of occupant-centric KPIs were synthesized from the review and enhancement of existing occupant-related performance metrics. The proposed occupant KPIs represent the occupant lens on three integrative aspects of building performance: resource use (including energy and water), indoor environmental quality, and human–building interactions. A simulation-based case study was conducted to demonstrate how occupant-centric KPIs can be used to quantify the impacts of building operation changes from the occupants’ point of view. Highlights: Occupant-centric metrics are currently ad hoc and limited, yet crucial to inform building design and operations. Literature was reviewed to reveal the state-of-the-art and gaps of occupant-centric metrics. A suite of occupant-centric key performance indicators (KPIs) covering five groups of building services were synthesized. Proposed occupant KPIs represent three aspects of performance: resource use and demand, occupant comfort and health, and human–building interactions. A case study using whole building simulation was conducted to demonstrate the use of occupant-centric KPIs in evaluating building operations during a power outage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Multi-Variable Parametric Analysis of Prototype Building Energy Performance Using Current and Future Weather Scenarios For Data-Driven Market Transformation Support

This project aimed to develop a public building simulation data set that may be used to inform building code development and guidelines for building innovation. The data set consists of several common building types and many representative locations across the United States. A parametric design of building properties was developed to create a range of building energy models that represent common building design decisions with a particular focus on fenestration options. The US Department of Energy prototype building energy models were altered according to a parametric building design and simulated using both current weather data and future weather estimates derived from global climate models. The resulting data set allows for pertinent exploration of building design parameters, including fenestration, within different environments across the United States in the broader context of climate change.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Precision measurement of Compton scattering in silicon with a skipper CCD for dark matter detection

Experiments aiming to directly detect dark matter through particle recoils can achieve energy thresholds of $\mathcal{O}(1\,\mathrm{eV})$. In this regime, ionization signals from small-angle Compton scatters of environmental $\gamma$-rays constitute a significant background. Monte Carlo simulations used to build background models have not been experimentally validated at these low energies. We report a precision measurement of Compton scattering on silicon atomic shell electrons down to 23$\,$eV. A skipper charge-coupled device (CCD) with single-electron resolution, developed for the DAMIC-M experiment, was exposed to a $^{241}$Am $\gamma$-ray source over several months. Features associated with the silicon K, L$_{1}$, and L$_{2,3}$-shells are clearly identified, and scattering on valence electrons is detected for the first time below 100$\,$eV. We find that the relativistic impulse approximation for Compton scattering, which is implemented in Monte Carlo simulations commonly used by direct detection experiments, does not reproduce the measured spectrum below 0.5$\,$keV. The data are in better agreement with $ab$$initio$ calculations originally developed for X-ray absorption spectroscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Analysis of Space-Conditioning Loads in Commercial Buildings

Space conditioning end-uses, which include heating, cooling, and ventilation, represent a significant fraction of commercial building energy use, with a wide variety of heating and cooling technology options available in the market. In the interest of improving the overall efficiency of heating, ventilation and air-conditioning (HVAC) technologies, governments, utilities and private sector entities have implemented a variety of market transformation policies that aim to influence consumer purchase decisions. To evaluate the costs and benefits of such programs, analysts typically postulate a hypothetical default equipment choice, and compare it to one that provides comparable service with lower energy and/or power use. The corresponding reduced operating cost provides a benefit that offsets the potential higher cost of improved efficiency. Typically, life-cycle cost or cash-flow analyses are used to quantify the net economic benefit. These analyses require the capability to assess how a given equipment design would perform across a broad range of characteristics, both of the building and of the local weather. While these assessments can be performed using customized building simulations, it is generally not practical to develop and validate detailed building simulation code to cover all the potential variations of equipment design and installation. An alternative, and somewhat simpler, approach is to solely use detailed building simulations to generate time series of heating and cooling loads in commercial buildings. These loads can then be used as input to more detailed, stand-alone engineering models that simulate HVAC system performance under different equipment designs. This approach was used to evaluate a range of high-efficiency commercial packaged air conditioner design options for the Department of Energy’s Appliance and Equipment Standards Program (DOE-EERE 2015). While there may be some loss of precision relative to full simulation, the accuracy of this approach is sufficient for practical applications of cost-benefit analysis. This report describes the development of a database of commercial building heating and cooling loads, generated using the EnergyPlus software package, a whole building energy use model supported by the Department of Energy (DOE-EERE 2020a). EnergyPlus takes as input a set of configuration files that describe the building itself (size, zoning, envelope characteristics, etc.) and the various systems within it (HVAC, lighting, water heating, etc.). This analysis uses a publicly available collection of commercial reference buildings (CRB), comprised of sixteen building types and three vintages (DOE-EERE 2020b; Deru et al 2011). Each building is simulated in eighteen different locations, covering a wide range of climatic conditions. The prototype building description files assign the type of HVAC equipment used, and capacities across climate zones.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Bay Area Regional Energy: Network Integrated Commercial Retrofits (BRICR) Project. Final Report

The BRICR project applied large-scale building energy modeling concepts with the aim of reducing the cost of energy efficiency targeting, design, and project development, and measurement of energy savings for energy efficiency programs implemented by local governments that serve small and medium commercial buildings (SMB). The project leveraged the services and resources of existing local government energy programs serving disadvantaged and hard-to-reach SMB customers. In contrast to programs run by utilities, local government programs generally do not have direct access to energy billing records for an entire class of customers in a geographic area, which prior research demonstrated useful for large-scale building energy model baseline development and calibration. , However, local governments are rich in public records that offer important clues about physical attributes and uses that, along with behavior, determine energy use. Relying only on public records, BRICR demonstrated development of credible baseline energy models for 3,792 office, retail, and hotel buildings. Publicly disclosed annual energy use data from a local energy benchmarking program and anonymized data from the Building Performance Database, the nation’s largest dataset about energy-related characteristics of buildings, were utilized to validate and calibrate energy models via an innovative method comparing distributions of energy intensity by fuel type for portfolios of buildings of similar size, vintage, and use. Portfolio calibration does not provide certainty that an energy model fits an individual building; the method is useful when billing data is not accessible – a common situation for researchers, energy service providers and ESCOs, local governments, and any party other than a utility. A software component was developed, the BRICR gem, which automates simulation when relevant data is added or edited by the user to a file saved in the standardized BuildingSync XML schema for energy audit data. The component was demonstrated as a simplified means to generate a mass of energy models corresponding to public records containing basic attributes such as building scale, location, use, year built, and aspect ratio in combination with building energy code prototype data corresponding to use and vintage. The component was also demonstrated as a simplified means to automate energy simulation when attributes are revised; the intention was to enable iterative improvement of the baseline model and energy savings estimates for common energy conservation measures as users revise relevant attributes based on their observations. In the context of institutional change and uncertainty for the participating local government energy programs, 13 whole building retrofits were completed. Impacts were measured by applying the CalTRACK2.0 methods to standardize measurement of normalized metered energy consumption. The GRIDMeter methods of stratified sampling and individual load shape analysis were applied to adjust for impacts of the effect of COVID-19 on retrofitted buildings in the context of all local buildings of similar size and use. Excluding impacts of the pandemic, retrofitted buildings demonstrated between 1.6% and 25.1% reduction in energy use. The project contributed use cases and feedback that helped inform evolution of the software tools and data formats that were combined for the first time in the BRICR project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Cellular Shade Energy Savings in a Commercial Setting

Windows cause approximately 1.7 quad of heating and cooling energy consumption in the United States. This energy consumption can be reduced by using high-efficiency window attachments. Common Venetian blinds and planar shades, such as roller shades, might block solar radiation, but they do not provide a significant improvement to window system thermal transmittance. Cellular shades have better thermal performance compared to other shading devices because of the honeycomb structure that traps air in pockets to create thermal insulation. However, evaluating the energy savings potential of cellular shades using experimental testing in commercial settings is limited. Moreover, the effect of cellular shades on daylighting and glare is yet to be evaluated using field testing. In this study, experimental testing of cellular shades was performed in a real building with emulated occupancy for both a cooling and a heating season. Compared with a room without shades, the use of cellular shades in experimental testing showed incremental energy savings of 4.6% to 9.4% for cooling and higher than 20% for heating. The experimental data were used to calibrate the baseline energy model and validate the cellular shades model. Annual simulation of cellular shades was performed for a medium office prototype building using the validated cellular shades model. The annual simulation was performed in Phoenix, Nashville, and Rochester. The annual savings for HVAC energy was 25% for Phoenix, 27% for Nashville, and 19% for Rochester.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A Data-Driven Approach to Nation-Scale Building Energy Modeling

In 2019, 125 million U.S. residential and commercial buildings consumed $412 billion in energy bills. These buildings currently consume 40% of the nation's primary energy, 73% of electricity, 80% of energy during peak electric grid use, and responsible for 39% of greenhouse gas emissions [14]. Urban-scale building energy modeling has grown significantly in the past decade, allowing individual campuses or communities of buildings to be modeled, simulated, and cost-effective solutions for intelligent management to be identified and implemented. While traditionally limited to individual counties and usually less than 2,000 buildings, the Automatic Building Energy Modeling (AutoBEM) soft-ware suite has been developed to process unconventional, nation-scale data sources to generate unique OpenStudio and EnergyPlus models of each building. Through the use of High Performance Computing (HPC) resources, every U.S. building has been simulated. This paper showcases the data layout, node partitioning, algorithmic approaches, and analytic results that were used to create, share, and analyze 124.4 million U.S. building models.

Berres, Andy↗
DOE OSTI2025

An update to the Sandia method for creating Typical Meteorological Years from a limited pool of calendar years

Typical Meteorological Years (TMYs) are essential for the efficient evaluation of energy system performance. Ideally, 30 years of weather data are required to generate TMYs, but significantly fewer years are typically available due to practical limitations. To address this issue, an update to the Sandia method was developed, referred to as the Argonne method, to create TMYs from a limited number of years. Furthermore, this method enhances candidate diversity by systematically shifting original candidate months forward or backward by specific days, creating an expanded pool of candidates. The effectiveness of the Argonne method was validated through statistical testing, comparison of monthly average weather parameters, and numerical simulations. The results demonstrate a high probability of identifying at least one shifted month whose cumulative distribution functions of weather parameters closely align with long-term distributions. In 67 % of all comparisons, the monthly average weather parameters in TMYs generated using the Argonne method exhibit better agreement with long-term averages than TMY3. Moreover, in 74 % of the 318 building simulation cases, the Argonne method outperforms TMY3 in estimating long-term average building heating and cooling demands. Therefore, the Argonne method effectively diversifies the candidate pool and produces typical years that provide more accurate estimations of long-term averages compared to TMY3 when only a limited pool of calendar years (10 years or fewer) is available.

Building energy modeling↗
DOE OSTI2022

Deep reinforcement learning with online data augmentation to improve sample efficiency for intelligent HVAC control

Deep Reinforcement Learning (DRL) has started showing success in real-world applications such as building energy optimization. Much of the research in this space utilized simulated environments to train RL-agent in an offline mode. Very few research have used DRL-based control in real-world systems due to two main reasons: 1) sample efficiency challenge---DRL approaches need to perform a lot of interactions with the environment to collect sufficient experiences to learn from, which is difficult in real systems, and 2) comfort or safety related constraints---user's comfort must never or at least rarely be violated. In this work, we propose a novel deep Reinforcement Learning framework with online Data Augmentation (RLDA) to address the sample efficiency challenge of real-world RL. We used a time series Generative Adversarial Network (TimeGAN) architecture as a data generator. We further evaluated the proposed RLDA framework using a case study of an intelligent HVAC control. With a ≈28% improvement in the sample efficiency, RLDA framework lays the way towards increased adoption of DRL-based intelligent control in real-world building energy management systems.

Kurte, Kuldeep↗
DOE OSTI2024

Outer shell symmetry for double shell capsules with aluminum ablators

Double shell targets are a promising potential avenue to obtain robust neutron yield at current laser facilities. Similar to single shell designs, double shells require the symmetric implosion of an ablator in order to uniformly compress and heat a fuel volume, with the goal of achieving thermonuclear burn. Significant differences between double and single shells include the usage of an aluminum ablator as well as a reverse ramp laser pulse. In addition, double shells require a different convergence than single shells for fuel ignition. Numerical implosion studies at various energies with comparisons to experimental outcomes are required to gain confidence that simulations can capture the ablator shape from subscale to full scale. The current work builds on previous implosion experiments conducted at 1-MJ laser energy to confirm achieved ablator symmetry at 1.25 and 1.5 MJ. Average ablator P2 and P4 shapes measured in these experiments are within 5% of the simulated shape, which merits the platforms for further experimental studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗