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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The Cost of Comfort in Your Home: Peak-Time Energy and Cost Savings from Setpoint Adjustment of Space Heating and Cooling

This poster presents the tradeoff between energy costs and thermal comfort in homes. Residential heating and cooling systems use a thermostat control to maintain a comfortable temperature range, but tighter temperature control leads to higher annual energy costs. We estimate the impact of temperature setpoint adjustment on annual energy costs using a residential building model developed at NREL. We show that increasing the allowable temperature range reduces energy costs in all five of the climate zones in the U.S. Annual costs reduced by about $100, with larger savings in areas with more heating and/or cooling loads.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Insight into Pyroelectricity and Phase Transitions in Ferroelectrics from Nonequilibrium Approach: The Case of PbTiO 3

Computational methodology is proposed to simulate time dependent temperature variations via thermostat approach. Here, the methodology is applied to study pyroelectricity under nonequilibrium conditions in prototypical ferroelectric PbTiO 3 . It is found that at room temperature the nonequilibrium effects in pyroelectricity begin manifesting above 1.0 THz and originate from the overlap with the intrinsic soft mode frequency. Therefore, the proposed computational methodology can be used to predict equilibrium pyroelectric response by choosing a frequency of temperature variation below the intrinsic polar mode frequencies for the material. Probing the dynamics of ferroelectric phase transition with the proposed methodology revealed that it takes about a nanosecond for the computational supercell to undergo phase transition. It is concluded that computational techniques capable of simulating picoseconds can be used to compute pyroelectric response from nonequilibrium dynamical approach while those that can reach nanoseconds are suitable for simulating phase transitions in ferroelectrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

U.S. Commercial Building Stock Analysis of COVID-19 Mitigation Strategies

The COVID-19 pandemic highlights the importance of improving building indoor air quality to reduce occupants' chances of contracting airborne illness. The ASHRAE Epidemic Task Force (ASHRAE-ETF) released several COVID-19 mitigation strategies at the onset of the pandemic. This study explores four of those recommendations for reducing transmission of COVID-19 inside buildings: (1) 100% outdoor air ventilation, (2) MERV-13 or better filters, (3) demand control ventilation removal, and (4) HVAC flushing mode. These recommendations were simulated and assessed using ComStock, a model of the U.S. commercial building stock. The study showed the 100% outdoor air ventilation recommendation had the largest impact on energy consumption, noncoincident peak demand, and thermostat violations. Removing demand control ventilation had the smallest national aggregate impact, installing MERV-13 filters led to slight increases in energy use and peak demand, and HVAC outdoor air flushing led to modest energy use and peak demand increases.

building energy modelling↗
DOE OSTI2025

Efficient Quantum Gibbs Samplers with Kubo–Martin–Schwinger Detailed Balance Condition

Lindblad dynamics and other open-system dynamics provide a promising path towards efficient Gibbs sampling on quantum computers. In these proposals, the Lindbladian is obtained via an algorithmic construction akin to designing an artificial thermostat in classical Monte Carlo or molecular dynamics methods, rather than being treated as an approximation to weakly coupled system-bath unitary dynamics. Recently, Chen, Kastoryano, and Gilyén (arXiv:2311.09207) introduced the first efficiently implementable Lindbladian satisfying the Kubo–Martin–Schwinger (KMS) detailed balance condition, which ensures that the Gibbs state is a fixed point of the dynamics and is applicable to non-commuting Hamiltonians. This Gibbs sampler uses a continuously parameterized set of jump operators, and the energy resolution required for implementing each jump operator depends only logarithmically on the precision and the mixing time. In this work, we build upon the structural characterization of KMS detailed balanced Lindbladians by Fagnola and Umanità, and develop a family of efficient quantum Gibbs samplers using a finite set of jump operators (the number can be as few as one), akin to the classical Markov chain-based sampling algorithm. Compared to the existing works, our quantum Gibbs samplers have a comparable quantum simulation cost but with greater design flexibility and a much simpler implementation and error analysis. Moreover, it encompasses the construction of Chen, Kastoryano, and Gilyén as a special instance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Data-driven evaluation of HVAC operation and savings in commercial buildings

Commercial buildings consumed 36% of electricity, or 1.35 trillion kWh, in the United States in 2017, and almost 30% of this energy was wasted. Much of this loss can be attributed to inefficient heating ventilation and air con­ditioning (HVAC) systems. By improving the operational conditions of HVAC, significant savings can be achieved. However, most buildings and building equipment do not use costly sub-meters to monitor and address performance issues, and on-site auditing can be expensive and insufficient. Alternatively in this study, we propose a data-driven method to identify savings opportunities using only whole building meter data and without setting foot in the building. For this purpose, we introduced two algorithms that virtually quantify the value of a thermostat setpoint setback and HVAC rescheduling. Additionally, we developed novel methods for detecting occupancy patterns and quantifying the baseload of the HVAC operation. Using a clustering algorithm, we identified those buildings for which HVAC savings was significant and further categorized the buildings based on their potential for savings. A population study of over 432 commercial buildings demonstrated a median percentage energy savings of 1.6% from a baseload reduction and 2.1% from HVAC rescheduling. Additionally, results indicate that retail buildings have the highest potential for savings among the building types studied.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Peak load reduction and load shaping in HVAC and refrigeration systems in commercial buildings by using a novel lightweight dynamic priority-based control strategy

Reducing peak power demand in a building can reduce electricity expenses for the building owner and contribute to the efficiency and reliability of the electrical power grid. For the building owner, reduced expenses come from the reduction or elimination of peak power charges on electricity bills. For the power system operator, reducing peak power demand leads to a more predictable load profile and reduces stress on the electric grid system. Herein we present a computationally inexpensive, dynamic, and retrofit-deployable control strategy to effect peak load reduction and load shaping. The effectiveness of the control strategy is examined in a simulation with 80 air-conditioning units and 40 refrigeration units. The results show that a peak demand reduction of 60 kW can be achieved relative to peak demand in a typical set point–based approach. The proposed strategy was deployed in a gymnasium building with four rooftop HVAC units, where it showed over 15% peak demand (kW) reduction savings while maintaining or lowering energy consumption (in kilowatt-hours) relative to the set point–based thermostat controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Carbon emission responsive building control: A case study with an all-electric residential community in a cold climate

In the United States, buildings account for 35% of total energy-related carbon dioxide emissions, making them important contributors to decarbonization. Carbon intensities in the power grid are time-varying and can fluctuate significantly within hours, so shifting building loads in response to the carbon intensities can reduce a building’s operational carbon emissions. This paper presents a rule-based carbon responsive control framework that controls the setpoints of thermostatically controlled loads responding to the grid’s carbon emission signals in real time. Based on this framework, four controllers are proposed with different combinations of carbon accounting methods and control rules. To evaluate their performance, we performed simulation studies using models of a 27-home, all-electric, net zero energy residential community located in Basalt, Colorado, United States. The carbon intensity data of four future years from the Cambium data set are adopted to account for the evolving resource mix in the power grid. Various performance metrics, including energy consumption, carbon emission, energy cost, and thermal discomfort, were used to evaluate the performance of the controllers. Sensitivity analysis was also conducted to determine how the control thresholds and intervals affect the controllers’ performance. Simulation results indicate that the carbon responsive controllers can reduce the homes’ annual carbon emissions by 6.0% to 20.5%. However, the energy consumption increased by 0.9% to 6.7%, except in one scenario where it decreased by 2.2%. Compared to the baseline, the change in energy cost was between –2.9% and 3.4%, and thermal discomfort was also maintained within an acceptable range. The little impact on energy cost and thermal discomfort indicates there are no potential roadblocks for customer acceptance when rolling out the controllers in utility programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Multiple simultaneous faults’ impacts on air-conditioner behavior and performance of a charge diagnostic method

Although there have been several studies that have focused on the effects of faults on the performance and on the characteristic features that could be used to detect faults, almost none of the research has studied the effects of multiple simultaneous faults. Existing fault detection and diagnosis approaches that have been developed based on single faults may struggle with simultaneous faults. Here, this paper is part of a series that present a methodology and comprehensive measurement data from a battery of laboratory tests on an air-conditioner with combinations of common faults (refrigerant charge, evaporator airflow, non-condensable gas, and liquid line restrictions) imposed, to show how the indicator variables and overall performance are impacted. The system has a microtube condenser and a fixed-orifice (FXO) expansion device, which are found to affect the features’ fault sensitivity. This experiment is the first to test these combined faults in an FXO-equipped system, so comparisons are made to a previously studied thermostatic expansion valve-equipped system. Finally, a promising charge diagnostic technology is assessed, to see how it is impacted by other faults. The faults reduced capacity by up to 42%, and efficiency by up to 39%. The charge diagnostic performed well, even with multiple faults present.

42 ENGINEERING↗
DOE OSTI2023

Sensitivity analysis of an automated fault detection algorithm for residential air-conditioning systems

The state of the art of fault detection and diagnosis (FDD) for residential air-conditioning systems is expensive and not yet amenable to widespread implementation. FDD for homes can significantly reduce utility costs, and increase the lifespan of the equipment. The cost barriers currently, however, make FDD for homes economically unviable for large scale implementation. In prior work, we offered a solution to reduce FDD costs by proposing an automated fault detection algorithm to serve as a screening step before more expensive FDD tests can be conducted. The algorithm uses only the home thermostat and local weather information to identify thermodynamic parameters and detect high-impact air-conditioning faults, including those that occur during equipment installation. We had tested the algorithm on a single EnergyPlus™ model of a home in Orlando, Florida. The thermodynamic parameter identification process is highly nonconvex involving several local optimal solutions. In this paper we propose a novel method to select the best model for fault detection from among the list of local optimal solutions to make the algorithm more robust to homes of different construction, without which the fault detection process would be infeasible. Another unique contribution of the paper is implementing the solution on real-world data. We also bring the algorithm closer to market by testing it on real-world data. We implement the algorithm on data obtained from experiments conducted by the Florida Solar Energy Center (FSEC) on a laboratory home equipped with a heat pump where faults were intentionally added for a period of seven months. The algorithm successfully detected an undercharge fault with 70.6% accuracy, concurrent duct leakage and undercharge faults with 85.2% accuracy, and duct leakage faults with 69.1% accuracy. A sensitivity analysis is also performed on EnergyPlus models of nine types of homes that vary in construction to demonstrate the robustness of the algorithm. Finally, the algorithm achieves an average accuracy of 71% for no-fault condition, 77% for 40% undercharge fault, and 76% for duct-leak fault.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A review of select human-building interfaces and their relationship to human behavior, energy use and occupant comfort

In recent years, research has emerged to quantitatively and qualitatively understand occupants' interactions with buildings. However, there has been surprisingly little research on building interfaces and how their design, context (e.g., location), and underlying logic impact their usability and occupants’ perceived control, as well as the resulting comfort and energy performance. This means that research is needed to better understand how occupants interact with building interfaces in both commercial and residential applications; both applications are important to address as there are many differences in interface types, level of control and understanding, and even expectations of engagement. Herein, this paper provides a cursory review and discussion of select common building interfaces: windows, window shades/blinds, thermostats, and lighting controls. The goal of this paper is to review literature related to these human-building interfaces to explore interface characteristics, current design and use challenges, and relationships between building interfaces and occupants. Human-building interface interactions are complex, more research is needed to understand design, use, and characteristics. Common themes emerged throughout the literature review to explain occupant interactions (or lack of interactions) with building interfaces, which included thermal and visual comfort, ease and access of control, interface/control placement, poor interface/control design, lack of understanding, and social-behavioral dynamics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Intersecting heuristic adaptive strategies, building design and energy saving intentions when facing discomfort environment: A cross-country analysis

Occupants' adaptive strategies play an important role in the energy consumption of office buildings. Previous research has mostly focused on the adaptive strategies triggered by occupants' indoor discomfort; however, it is crucial to understand if specific adaptive strategies are linked to occupants' energy-saving intentions. This study explores the relationships among employees’ heuristic decision-making in their first choice of adaptive strategies (technological solutions or personal adjustments) when facing extreme discomfort conditions, and their energy-saving intentions, then links these patterns with building design, workplace contextual factors, and demographics. A cross-sectional survey was collected among university employees from China, Brazil, Italy, Poland, Switzerland, and the US. Our results demonstrated that the accessibility to indoor environmental controls (IECs) and office type are the significant factors for adaptive strategies. There was a positive relationship between the number of IEC features and the percentage of employees choosing a technological solution. When feeling too hot, occupants in private offices are more likely to adopt a technological solution, whereas occupants in cubicles are more likely to choose a personal adjustment. Occupants with energy-saving intentions are less likely to choose thermostat adjustments or use portable devices as adaptive strategies than their counterparts. Lastly, the cluster analysis suggests females were more likely to use adaptive strategies for energy-saving purposes than males. The majority of occupants would turn on/off lighting to save energy. The study provides the contributions in the connection between the heuristic decision-making process and energy-saving intentions and recommendations on design strategies for building architects, engineers, and managers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Power allocation by load aggregator with heterogeneous loads using weighted projection

With the recently increasing adoption of transactive energy markets, the role of a load aggregator is becoming increasingly important. Among the many tasks of an aggregator, the task of managing the electricity consumption among a group of grid-interactive efficient buildings according to the demand on the grid is taken up. Specifically, here, the task of allocating a certain amount of power among the participating customers while respecting their preferences and comfort is considered. Modeling this as an aggregate flexibility, the virtual battery conditions that are employed to verify the feasibility of a candidate power profile are derived. A feasible power profile, when allocated, satisfies specified comfort bands. To determine the ideal power requirement of the loads, the model-free control method is employed. The feasible power profile is allocated by embedding the customers’ preferences through weights, posing the power constraint as a hyperplane, and employing a weighted projection from the ideal power requirements onto the constraint plane to solve the considered task. The proposed method is computationally efficient and scalable to any number of heterogeneous thermostatically controlled loads in buildings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Experimental investigation on thermal inertia characterization of commercial buildings for demand response

Characterizing the thermal inertia of commercial buildings is of great importance in quantifying demand flexibility. Experimental tests can be used to investigate the thermal inertia of commercial buildings. However, existing studies tend to be qualitative and have limited scope. In this study, a comprehensive field test has been performed to assess the thermal inertia of commercial buildings. In this field test, six buildings are selected with different sizes, vintages, and types of heating, ventilation, and air conditioning (HVAC) systems to represent the majority of the U.S. commercial building stock. We quantify the thermal inertia with building operation data collected under various thermostat excitation signals. We then studied the relationship between thermal inertia and intrinsic properties, such as floor area, HVAC system, etc., as well as the operation condition indicators such as outdoor air temperature, zone temperature, and occupancy. The testing results indicate that the median values of the normalized charge response time and the normalized discharge response time of the five buildings are 1~5 hr/ °C and -5~-1 hr/ °C, respectively. The results also show that the thermal inertia of commercial buildings may be sensitive to the HVAC system type but not the floor area or location of zones, i.e., core vs. perimeter. Finally, our results suggest that the relationships between the charging/discharging normalized response time and the zone/outdoor temperature may vary among zones and be highly nonlinear.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Energy performance of an operational government building retrofitted with ceiling phase change material tiles in a mixed-humid climate

The aging U.S. building stock requires various retrofit measures to enhance their energy efficiency. Here, this study explores the integration of thermal energy storage and advanced building controls as viable retrofit solutions for load flexibility and peak demand response while maintaining the occupants' comfort. A detailed assessment is conducted on the energy use of an administrative building in Sumner County, Kansas, focusing on the implementation of phase change materials (PCMs) in the ceiling of occupied zones. First, a time-resolved, whole-building energy model is developed in EnergyPlus, incorporating complex thermal behaviors such as air exchange between the plenum space and occupied zones, envelope leakage, and operational schedules. The model is then validated using experimental field test data, and subsequently a parametric assessment of key PCM properties and application strategies is performed to evaluate cooling electricity demand benefits. The parametric study shows that the optimal retrofit strategy, comprising a PCM with 23°C peak melting temperature, 0.125 in. (3.17 mm) thickness, and 150 kJ/kg latent heat, combined with active controls that include 8 h of precooling, forced convection under the ceiling, and a 2°C thermostat setback during peak hours, can result in a maximum load shift during the peak period of 99.6 % and the total electricity savings during the peak period of 98.9 % for the optimum case and thus provide significant cost savings under time-of-use pricing scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Machine learning-enhanced MPC for demand flexibility in small commercial buildings: An experimental study

Small- and medium-sized commercial buildings (SMCBs) represent the majority of U.S. commercial building stock and a significant share of peak electricity demand, yet they often lack centralized building automation systems, representing a significant untapped resource for urban energy management. This infrastructure gap makes advanced control implementation challenging, limiting the potential for widespread demand flexibility. Model Predictive Control (MPC) has shown strong potential for load shifting, peak demand reduction, and cost savings, but its effectiveness is hindered by unmeasured disturbances such as internal heat gains. This paper presents a Hybrid MPC framework that integrates a physics-based gray-box building thermal model, identified using a lumped disturbance (LD) approach, with a machine learning (ML) model for forecasting unmeasured disturbances. The hybrid approach is designed for buildings with multiple individually controlled heat pump and thermostat pairs, common in SMCBs, and aims to optimize coordinated scheduling of multiple heat pumps under dynamic electricity pricing while respecting comfort constraints. The methodology is validated through both simulations of case study buildings and experimental studies at a highly-instrumented test facility. Simulation results show that the Hybrid MPC achieves substantial load shifting and peak demand reduction, approaching the performance of an ideal MPC with perfect disturbance knowledge, and outperforming a conventional MPC without disturbance forecasting. In experiments, the Hybrid MPC reduced daily HVAC energy costs by 8.7%, peak-price time load (load shifting) by 41.7%, and peak demand by 29.2% compared to baseline control, demonstrating comparable benefits to the 11.6% cost savings, 42.9% load shifting, and 23.2% peak reduction of the ideal MPC. These results demonstrate that the proposed hybrid modeling approach can significantly improve MPC performance in real-world SMCB applications without requiring additional disturbance measurements.

Demand Flexibility↗
DOE OSTI2021

Evaluation of cooling setpoint setback savings in commercial buildings using electricity and exterior temperature time series data

Commercial buildings account for a significant amount of total energy produced in the US, and the Heating Ventilation and Cooling (HVAC) systems are one of the most significant components of their overall consumption. In this study, we proposed a new data-driven approach to evaluate HVAC cooling systems in commercial buildings and identify savings opportunities. The focus is an investigation of the impact of thermostat setpoint setback but using only whole building, electricity data taken at 15-min intervals for the analysis. We conducted a comparative study of setpoint setback characteristics on 432 commercial buildings with 5 building usage types across the United States. To accomplish this, both piecewise and Random Forest regression algorithms were employed using electricity and exterior temperature datasets to identify operational characteristics and the effective setpoints in the building to determine the corresponding savings opportunities. Both occupied and unoccupied time periods were studied across cooling degree days (CDD), when air conditioning is typically operational. Here the results show that in commercial buildings, on average, cooling systems account for 9.5% of total consumption. When a one degree setback during the cooling season is applied, an average of approximately 1.1% of annual consumption is achieved; retail and office buildings demonstrate the highest potential for savings. Additionally, we identified that the number of cooling degree days and base to peak ratio (BPR) are the most important variables for predicting the magnitude of the consumption of cooling systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

City-level impacts of building tune-ups: Findings from Seattle's building tune-ups program

Many U.S. cities are implementing policies to reduce greenhouse gas (GHG) emissions of their buildings. These range from building energy benchmarking and disclosure to building performance standards (BPS) that require buildings to meet specific targets of energy use or emissions. The City of Seattle adopted a climate action plan in 2013 that set a goal of zero net GHG emissions in the road transportation, buildings, and waste sectors by 2050, with a number of near and long term actions. Seattle implemented mandatory building tune-ups in 2016, applying to commercial buildings larger than 50,000 sqft. Building tune-ups1 involve assessment and implementation of operational and maintenance (O + M) improvements to achieve energy and water efficiency, such as changes to thermostat set points or adjusting lighting or irrigation schedules. Seattle's tune-ups program covered 27 such improvements in HVAC, lighting, domestic hot water, and envelope systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Why is it still too warm or cold in my house? Examining the relationships between energy efficient capital and household energy insecurity

Here, this paper examines the relationships between energy efficient (EE) capital technology and household energy insecurity in the United States. The theoretical model of these relationships employs household production theory to capture the demand for and production of household energy services, and a stochastic production frontier approach to describe how having access to and the usage intensity of EE capital technology could help alleviate inefficiency in the production of household energy services. A working hypothesis formulated from the theoretical model posits that having EE capital technology in the home will reduce the level of household energy insecurity experienced. The extent of energy insecurity experienced is inferred from an energy insecurity index value assigned to each household, generated via the application of a dichotomous Rasch model to questions contained in the 2015 Residential Energy Consumption Survey. Noting the potential simultaneous relationship that exists between a household having access to and the usage intensity of EE capital technology and the experience of being energy insecure, an instrumental variables approach was employed to estimate a series of ordered logit models. Results suggest access to EE capital technology in the form of Energy Star® appliances, Energy Star® windows, or a SMART thermostat does not reduce the probability of experiencing a greater level of energy insecurity. Nor does the usage intensity of EE capital. Thus, policy instruments designed to alleviate household energy insecurity may need to go beyond simply helping households obtain EE capital technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗