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

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Regional difference and related cooling electricity savings of air pollutant affected natural ventilation in commercial buildings across the US

Maintaining indoor air pollutants under acceptable levels is significant to protect occupants from exposure to excessive air pollutants in natural ventilation. In this paper, using the representative air pollutant concentration data, we present the natural ventilation usability with associated cooling energy saving potentials in different location settings (urban and city center, suburban and rural) of the US under the influence of local weather conditions and major outdoor air pollutants, i.e. PM2.5, PM10 and ozone. It is found that the impacts of air pollutants on natural ventilation are usually higher in urban/suburban areas than rural areas (up to 25% difference) with the PM2.5 being the most significant outdoor air pollutant affecting natural ventilation usage. Furthermore, ozone could become increasingly influential on natural ventilation as moving from urban to suburban/rural areas. As to the cooling energy saving considering the impacts of outdoor air pollutants, natural ventilation is estimated to save approximately 10%–40% cooling energy (800–2600 kWh per small commercial building) annually in different location settings of investigated areas across the US. The following economic analysis demonstrates that these electricity savings lead to approximately 80–540 dollars annual savings of building operation cost per building. If the time of use rate is adopted, these cost savings could further increase by approximately 20% (Los Angeles) to more than 50% (Albuquerque) depending on different rate structures, which further demonstrates the potential of adopting natural ventilation as a sustainability measurement with benefits for building owners without compromising occupants health.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Creating the Distributed Energy Resources Education Center (DEREC)

The built environment in the United States consumes 40% of the energy generated and emits roughly the same percentage of total carbon footprint. Distributed energy resources (DER), small or modular energy generation and storage technologies, present the nation with an opportunity to substantially improve those metrics while securing the nation’s energy independence. As opportunities increase for implementing such technologies, they also continue to evolve and often outpace the nation’s traditional building practices. In an effort to effectively and proactively incorporate distributed energy resources into the nation’s energy supply, Southface Energy Institute convened with national and regional partners to create the Distributed Energy Resources Education Center (DEREC). Using national model codes and their regionally amended versions as a collective starting point, the DEREC team collaborated with industry experts and identified impediments to effective implementation of DERs, developing discipline-specific curriculum to eliminate those impediments. The center, developed in collaboration with Interstate Renewable Energy Committee (IREC) and National Buildings Institute (NBI), leverages existing DER education content as well as new and dynamic training materials and online courses that collectively engage the many roles necessary for DER implementations, including designers, code officials, builders and skilled trades, and building owners who specify, inspect, build, operate, and maintain buildings with DERs.

14 SOLAR ENERGY↗
DOE OSTI2020

Methodology to assess “no-touch” building audit software using simulated utility data

Building audits are conducted in many commercial buildings to identify opportunities to reduce energy costs and improve building operation. Because audits require significant effort by building engineers, they are usually only affordable for larger commercial buildings. “No-touch” building audit tools have thus been developed to identify potential savings based on a simplified analysis of building energy consumption patterns via high-level energy data such as monthly utility bills. This paper presents a comprehensive and standardized methodology to evaluate the accuracy of no-touch audit tools in detecting and diagnosing building energy problems and quantifying potential energy savings. The test suite is based on output data from a well-characterized set of building energy models, and the methodology is illustrated by applying it to a representative no-touch building audit tool. Results show that the tool estimates building energy end uses with reasonable accuracy but is less accurate in identifying probably causes of high energy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Tradeoffs among indoor air quality, financial costs, and CO 2 emissions for HVAC operation strategies to mitigate indoor virus in U.S. office buildings

Adapting building operation during the COVID-19 pandemic to improve indoor air quality (IAQ) while ensuring sustainable solutions in terms of costs and CO 2 emissions is challenging and limited in literature. Our previous study investigated different HVAC operation strategies, including increased filtration using MERV 10, MERV 13, or HEPA filters, as well as supplying 100% outdoor air into buildings for a system initially sized for MERV 10 filtration. This paper significantly extends that research by systematically analyzing the potential financial and environmental impact for different locations in the U.S. The previous medium office building system model is improved to account for operation in different climates. New evaluation metrics are created to consider the comprehensive impact of improving IAQ on costs and CO 2 emissions, using dynamic emission factors for electricity generation depending on the location. HVAC operation strategies are studied in five different locations across the United States, with distinct climates and electricity sources. In four of the five locations, MERV 13 filtration offers the best improvement in IAQ per increase in costs and emissions relative to MERV 10. The exception is the mildest climate of San Diego, where use of 100% outdoor air provides the best IAQ with a limited increase in costs and emissions. Finally, a system not sized for HEPA filtration can lead to increased costs and emissions without much improvement in IAQ.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Very High Efficiency Dedicated Outdoor Air System Field Site Re-Evaluation

The study reported here evaluated the long-term performance of Very High Efficiency (VHE) Dedicated Outside Air Systems (DOASs) installed at eight sites that participated in field evaluation studies performed by the Northwest Energy Efficiency Alliance (NEEA) and Institute for Market Transformation (IMT) from 2015 through 2020. The study compared the energy performance of the systems in 2021-2022 to the findings of the original evaluation. It also evaluated the indoor environmental quality (IEQ) as perceived by occupants and building operator feedback before and after the system conversion. The findings of the study are important for building owners and managers who are considering adopting VHE DOASs. The study found that the systems: (1) consistently saved energy over the long term, (2) improved occupant comfort, and (3) received positive feedback from building operators. All of the sites had similar or improved energy savings over the pre-conversion system compared to the original evaluation savings, and only one site had a small reduction in energy savings. The sites averaged 48 percent whole site energy savings compared to the pre-conversion system. The continued energy performance of these sites provides strong evidence that the energy savings achieved by VHE DOAS retrofits will be sustained long term. The study also investigated the changes in occupant comfort resulting from the VHE DOAS retrofit. Responses to a survey sent to the sites’ occupants revealed that the conversion resulted in a better indoor environment for the occupants. Most respondents reported that their satisfaction increased, and dissatisfaction decreased post-conversion. Overall occupants were 43 percent more satisfied and 30 percent less dissatisfied post-conversion compared to pre-conversion. The study's findings suggest that a VHE DOAS can be a solution to improve the energy efficiency, reduce energy costs, and increase occupant comfort in buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Occupancy-Driven Stochastic Decision Framework for Ranking Commercial Building Loads

For effective integration of building operations into the evolving demand response programs of the power grid, real-time decisions concerning the use of building appliances for grid services must excel on multiple criteria, ranging from the added value to occupants' comfort to the quality of the grid services. In this paper, we present a data-driven stochastic decision-support framework to dynamically rank load control alternatives in a commercial building, addressing the needs of multiple decision criteria (e.g. occupant comfort, grid service quality) under uncertainties in occupancy patterns. We adopt a stochastic multi-criteria decision algorithm recently applied to prioritize residential on/off loads, and extend it to i) consider complex load control decisions (e.g. dimming of lights, changing zone temperature set-points) in a commercial building; and ii) systematically integrate zonal occupancy patterns to better identify short-term (and time-varying) opportunities for grid service participation. We evaluate the performance of the proposed framework for curtailment of air-conditioning, lighting, and plug-loads in a multi-zone commercial office building for a range of design choices. With the help of a prototype system that integrates an interactive \textit{Data Analytics and Visualization} frontend we demonstrate a way for the building operators to monitor and change in real-time the available flexibility in energy consumption and to develop trust in the decision recommendations by interpreting the rationale behind the ranking.

Jain, Milan↗
DOE OSTI2025

Cost-Effective Thermally Activated Building Systems to Support a Power Grid System With High Penetrations Of As-Available Renewable Energy Resources

With a goal to reduce the energy cost for building operation as well as to support renewable energy sources (RES) for the power grid reliability, quality, resilience, and dispatchability, this project developed and demonstrated a novel thermally activated building envelope system that integrates Phase Change Material (PCM)-based Thermal Energy Storage (TES) and the hydronic activation into the building envelope. The main objectives of this study are: 1) to design and laboraorty-test a novel thermally activated building envelope system that integrate PCM-based TES and the hydronic activation into building envelope, and 2) to exploit this new system to significantly reduce the energy cost of operating buildings and manage and support renewable energy sources (RES), e.g., solar and wind for the power grid reliability, quality, resilience, and dispatchability. To achieve the project objectives, a new low-cost, fire-retardant PCM packaging technology (CenoPCM) was developed specifically for high-volume building applications.

25 ENERGY STORAGE↗
DOE OSTI2025

HP-FLEX: Field demonstration of the semantics-driven configuration of a Model Predictive Control system to make heat pumps flexible

Model Predictive Control (MPC) has demonstrated significant potential for optimizing building operations and enabling demand flexibility. However, the widespread adoption of MPC is hindered by complex manual configuration and commissioning processes that must be conducted by control experts working alongside building operators. These challenges drive up costs and reduce scalability, particularly when technical human resources and building automation systems are limited, such as in small and medium commercial buildings (SMCBs). This paper demonstrates how semantic standards, specifically ASHRAE 223P, can accelerate the adoption of MPC applications for load flexibility in SMCBs. The authors present a replicable control framework, titled “HP-FLEX” that leverages a building’s semantic model to bootstrap the required data configuration for an MPC controller developed for optimizing heat pump systems as flexible grid resources. The semantic model helps streamline the deployment workflow, particularly for site setup, data/control commissioning, and model setup. This integration enhances portability, transferability, and scalability of the HP-FLEX MPC, which has been developed to support MPC-based supervisory HVAC controllers in SMCBs. Additionally, the paper details the required building and thermostat metadata information to enable the HP-FLEX MPC based on field demonstrations. The new workflow was tested in a small commercial building located in California, U.S., and demonstrated a load shifting performance of 9% based on a dynamic pricing signal that varies by the hour. This work provides a practical pathway for transitioning sophisticated building applications from custom to standardized semantic representations, supporting the broader adoption of advanced control strategies like MPC. The framework also establishes a foundation for evolving metadata requirements as applications mature while maintaining compatibility with industry standards.

Paul, Lazlo↗
DOE OSTI2025

HP-FLEX: Field Demonstration of the Semantics-Driven Configuration of a Model Predictive Control System to Make Heat Pumps Flexible

Model Predictive Control (MPC) has demonstrated significant potential for optimizing building operations and enabling demand flexibility. However, the widespread adoption of MPC is hindered by complex manual configuration and commissioning processes that must be conducted by control experts working alongside building operators. These challenges drive up costs and reduce scalability, particularly when technical human resources and building automation systems are limited, such as in small and medium commercial buildings (SMCBs). This paper demonstrates how semantic standards, specifically ASHRAE 223P, can accelerate the adoption of MPC applications for load flexibility in SMCBs. The authors present a replicable control framework, titled “HP-FLEX” that leverages a building’s semantic model to bootstrap the required data configuration for an MPC controller developed for optimizing heat pump systems as flexible grid resources. The semantic model helps streamline the deployment workflow, particularly for site setup, data/control commissioning, and model setup. This integration enhances portability, transferability, and scalability of the HP-FLEX MPC, which has been developed to support MPC-based supervisory HVAC controllers in SMCBs. Additionally, the paper details the required building and thermostat metadata information to enable the HP-FLEX MPC based on field demonstrations. The new workflow was tested in a small commercial building located in California, U.S., and demonstrated a load shifting performance of 9% based on a dynamic pricing signal that varies by the hour. This work provides a practical pathway for transitioning sophisticated building applications from custom to standardized semantic representations, supporting the broader adoption of advanced control strategies like MPC. The framework also establishes a foundation for evolving metadata requirements as applications mature while maintaining compatibility with industry standards.

Paul, Lazlo↗
DOE OSTI2021

Development of a Unified Taxonomy for HVAC System Faults

Detecting and diagnosing HVAC faults is critical for maintaining building operation performance, reducing energy waste, and ensuring indoor comfort. An increasing deployment of commercial fault detection and diagnostics (FDD) software tools in commercial buildings in the past decade has significantly increased buildings’ operational reliability and reduced energy consumption. A massive amount of data has been generated by the FDD software tools. However, efficiently utilizing FDD data for ‘big data’ analytics, algorithm improvement, and other data-driven applications is challenging because the format and naming conventions of those data are very customized, unstructured, and hard to interpret. This paper presents the development of a unified taxonomy for HVAC faults. A taxonomy is an orderly classification of HVAC faults according to their characteristics and causal relations. The taxonomy includes fault categorization, physical hierarchy, fault library, relation model, and naming/tagging scheme. The taxonomy employs both a physical hierarchy of HVAC equipment and a cause-effect relationship model to reveal the root causes of faults in HVAC systems. A structured and standardized vocabulary library is developed to increase data representability and interpretability. The developed fault taxonomy can be used for HVAC system ‘big data’ analytics such as HVAC system fault prevalence analysis or the development of an HVAC FDD software standard. A common type of HVAC equipment-packaged rooftop unit (RTU) is used as an example to demonstrate the application of the developed fault taxonomy. Two RTU FDD software tools are used to show that after mapping FDD data according to the taxonomy, the meta-analysis of the multiple FDD reports is possible and efficient.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Building the Efficiency Workforce: Preprint

Demand for high-performance homes and buildings is growing due to their marketability, environmental benefits, and increasing affordability. Growth for energy efficient technologies and building upgrades has driven expansion across many traditional industries including construction trades (which added almost 21,000 jobs) and professional services (which added 35,000 employees) in 2018, according to the 2019 U.S. Energy Employment Report (USEER). As buildings become more automated, digitized and interconnected, the workforce that supports the design, build, operations and maintenance of these buildings must evolve. The U.S. Department of Energy’s Building Technologies Office (BTO) has engaged NREL to provide a framework upon which BTO can develop their next generation workforce development strategy. The strategy will be designed to increase quantity of workers with the skills to adequately design, install, maintain and operate high- performance buildings across all building sectors (residential, commercial, industrial). This paper will summarize past BTO workforce development efforts, identify current skills gaps and hiring challenges, and present anticipated future workforce needs based on new technologies currently being developed by labs and industry. Through a literature review and a series of industry and academic workshops, NREL will present a framework that includes multiple options to best prepare the next generation workforce.

buildings↗
DOE OSTI2022

A review of computing-based automated fault detection and diagnosis of heating, ventilation and air conditioning systems

We report faults in Heating, Ventilation, and Air Conditioning (HVAC) systems of buildings result in significant energy waste in building operation. With fast-growing sensing data availability and advancement in computing, computational modeling has demonstrated strong capability to detect and diagnose HVAC system faults, hence, ensuring efficient building operation. This paper comprehensively reviews the state-of-the-art computing-based fault detection and diagnosis (FDD) for HVAC systems. Overall, the reviewed computing-based FDD methods are classified as two major approaches: knowledge-based and data-driven approaches. We then identify multiple important topics, including data availability, training data size, data quality, approach generality, capability, interpretability, and required modeling efforts, along with corresponding metrics to summarize the most updated FDD development. Generally, the knowledge-based approaches are further divided as physics-based modeling, Diagnostic Bayesian Network, and performance indicator-based methods while data-driven approaches include supervised learning, unsupervised learning, and regression and statistics-based methods. State-of-the-art FDD development, remaining challenges, and future research directions are further discussed to push forward FDD in practice. Availability of fault data, capability of existing methods to deal with complex fault situations (such as simultaneous faults), modeling interpretability for data-driven methods, and required engineering efforts for physics-based methods are identified as remaining challenges in FDD development. Improving modeling fidelity and reducing modeling efforts are essential for applying physics-based methods in real buildings. Meanwhile, addressing fault data availability, increasing algorithm adaptability, and handling multiple faults are essential to further enhance the applicability of data-driven FDD approaches.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Seminar 44, Innovative and New Ideas: BAS Best Practices for O&M Success Coaching Operators for Effective Use of Data

Regardless of a building’s inherent energy efficiency, changes in building operator behavior reduces building energy consumption by 14% on average. Giving operators readily available and easily digestible data regarding the performance of their HVAC systems increases the likelihood of energy saving actions. Many Building Automations Systems do not excel at creating user-friendly time series trend charts. This presentation presents examples of a solution to this issue developed under an award by the Department of Energy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Impact of refrigerant undercharge faults on building indoor conditions and HVAC system operation in residential Buildings: A simulation study

This study investigates the impact of refrigerant undercharge on indoor temperature and HVAC system performance in residential buildings. Simulation models for typical residential buildings in Orlando, FL and Indianapolis, IN were developed using the ResStock database. A refrigerant undercharge fault model was then applied to the simulations with varying levels of fault intensity. The paper offers an extensive analysis, revealing that variations in supply air temperature, equipment runtime, and cooling energy consumption due to the level of refrigerant undercharge faults are notably significant on a summer representative day. Similarly, on a winter representative day, changes in supply air temperature and runtime are significant as well as changes in supplemental heat energy consumption. We find that occupants may remain oblivious to these faults during the cooling season, particularly when the HVAC system is oversized; in that case, supply air temperature data could help detect a fault. Another challenge is that during the heating season, when the supplemental heater operates, it is difficult to identify a refrigerant undercharge fault using only indoor and supply air temperature data. Finally, this study finds that supply air temperature, equipment runtime, and supplemental heater energy consumption data can help in detecting refrigerant undercharge faults.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Sensor Impacts Evaluation and Verification: Expert Interview Responses

The sensor configuration/deployment method has critical impacts on energy efficient building control and thermal comfort. However, traditional sensor techniques for building operation and fault detection and diagnostics (FDD) are not necessarily optimal in terms of energy efficiency and thermal comfort, and their global effects are not thoroughly investigated. In an effort to address and overcome this limitation, a multilaboratory and multiyear project, “Sensor Impact Evaluation and Verification,” was proposed. Its purpose is to develop a framework to investigate the impacts of sensor deployment and configuration on building energy optimization, FDD, occupant thermal comfort, and potentially grid efficiency. The first project task was a literature review to establish a solid knowledge of and a background related to sensor technologies and placement. To accomplish this task, an extensive review of previous research literature was performed. A series of expert interviews were conducted to augment the findings of the literature review. This report summarizes the interview design and interview results and findings. The interview was designed and performed to (1) investigate the current status and limitations of sensor configuration, (2) identify the research gaps and expectations for potential improvements in sensor configuration and deployment, and (3) integrate expert (e.g., researcher, building operation practitioner) knowledge and experience to develop use-case scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Towards Off-policy Evaluation as a Prerequisite for Real-world Reinforcement Learning in Building Control

We present an initial study of off-policy evaluation (OPE), a problem prerequisite to real-world reinforcement learning (RL), in the context of building control. OPE is the problem of estimating a policy's performance without running it on the actual system, using historical data from the existing controller. It enables the control engineers to ensure a new, pretrained policy satisfies the performance requirements and safety constraints of a real-world system, prior to interacting with it. While many methods have been developed for OPE, no study has evaluated which ones are suitable for building operational data, which are generated by deterministic policies and have limited coverage of the state-action space. After reviewing existing works and their assumptions, we adopted the approximate model (AM) method. Furthermore, we used bootstrapping to quantify uncertainty and correct for bias. In a simulation study, we evaluated the proposed approach on 10 policies pretrained with imitation learning. On average, the AM method estimated the energy and comfort costs with 1.84% and 14.1% error, respectively.

Chen, B↗
DOE OSTI2021

Sensor impacts on building and HVAC controls: A critical review for building energy performance

Building operations rely heavily on control systems and sensors. This paper provides a sophisticated literature review on sensor systems in building/HVAC systems, particularly in the context of controls, and their impacts on energy efficiency and thermal comfort. This study aims to understand the previous and current research and identify future research opportunities on this subject. The reviewed sensor systems were used for heuristic rule-based controls, local controls, and advanced optimal controls for existing and emerging technologies. Five major aspects of sensors are reviewed here: control loops for sensors, sensor types, sensor locations, sensor data, and a sensor impact evaluation framework. To augment the literature review, comprehensive standardized interviews were also conducted with relevant industry experts and practitioners. These interviews were designed and performed to (1) identify significant factors for selecting sensor sets and current undergoing issues, (2) identify potential improvements in sensor configuration/deployment, and (3) integrate expert (e.g., researcher, building operation practitioner) knowledge and experiences to develop structured use-case scenarios. Researchers collected and analyzed 31 interview responses for this paper.

Building control↗