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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 127 records · Page 7

How can we combine urban cooling strategies to effectively cool cities over the entire diurnal cycle?

The urban heat island effect generally peaks in the night/evening hours and, in some cases, an urban cool island effect during daytime has been reported. These patterns are observed mainly because of the widespread use of impervious and thermally massive materials (like concrete and asphalt) in the built environment and their ability to store energy during the daytime and release it at night. Unfortunately, most urban cooling strategies, such as cool (white), green, and blue spaces, provide better thermal performance during the daytime than at night. Hence, such solutions are not ideal for nighttime heat mitigation. In this study, we investigate the effect of the thermal storage capacity of existing buildings on nighttime urban air temperature for a hot arid city—Phoenix, and a hot humid city—Atlanta. The study uses regional scale atmospheric modeling to compare the nighttime urban cooling capability of thermally light buildings (Cross-laminated timber buildings in this case) with concrete buildings. The results show that the adoption of thermally light buildings reduce nighttime air temperatures, and slightly increases daytime air temperatures. On the other hand, cool roof adaption could reduce urban air temperature significantly during the daytime and slightly at night. Therefore, together with cool roofs, thermally light buildings may be able to cool the surrounding air by an average of about 1°C throughout the diurnal cycle, providing thermal comfort and reducing cooling demand during all hours.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Advanced HVAC Humidity Control for Hot-Humid Climates

During this project we develop and validate a cost-effective, integrated control solution to improve humidity control and comfort for energy-efficient homes in hot-humid climates. This study focuses on developing a strategy that is effective, field tested, and practical for builders to install with minimal disruption to standard practices. A successful solution would simplify the transition to high-performance humidity control and be the basis for design and installation guidance. By relying on the central system as a starting point, the strategy employed minimizes system complexity and cost for builders, while improving comfort and operating cost for homeowners. The solution strategy was to coordinate the cooling, dehumidification, and ventilation functions of central, ducted HVAC systems to better control indoor humidity, improve occupant thermal comfort, and capture energy savings. The primary strategic goals were to: (1) optimize dehumidification by the central air-conditioning system, particularly during part-load conditions, using conventional equipment with modified control settings and lower system airflows; (2) maximize ventilation during heating/cooling on-cycles, to “bank” and condition outdoor ventilation air, and minimize ventilation during off-cycles; (3) quantify the effectiveness and energy impact of the dehumidification and ventilation strategies, while identifying a metric that would be useful to evaluate latent effectiveness. For the test houses in our study, located in Richmond Hill, Georgia; Houston, Texas; and Monroe, Louisiana we observed: (1) the indoor humidity did not exceed 60% RH during the monitored cooling season for 99% of the time in Richmond Hill, 96% of the time in Houston, and 90% of the time in Monroe; (2) the dehumidification strategy improved the steady-state latent capacity of the HVAC system at design conditions by 16% to 49% at the Houston test house and by 28% to 71% at the Monroe test house, depending on which mode the system was operating in; and (3) the good results at the test houses were primarily due to the amount of time the air-conditioning system operated in ramping or dehumidification modes, or both, particularly during the early cooling season. This study demonstrates that air conditioners or heat pumps with a single-stage compressor can provide good humidity control without the need for a two-stage or variable-stage compressor system. The airflow and control settings for ramping and dehumidification modes are critical to control indoor humidity in hot-humid climates, particularly during part-load and shoulder season conditions. The dehumidification strategy used in this study did not jeopardize the mechanical reliability of the cooling equipment. The strategies used in this study are applicable across various equipment brands, models, and efficiency levels, and also applicable to a broad range of homes in hot-humid climates. Results will vary by specific equipment, location, and house configuration and construction.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Performance evaluation of underground thermal storage integrated dual-source heat pump systems

The increasing demand for electricity stresses the existing electric grids. Buildings consume 73% of all U.S. electricity and are responsible for 30% of U.S. greenhouse gas emissions. Integrating thermal energy storage (TES) in building heating/cooling systems, which consume considerable electricity, can mitigate the challenges to electric grids. Here, this study reports on a novel thermal energy storage device integrated heat pump system to reshape the building electricity demand profile while maintaining thermal comfort. The annual performance of the proposed system has been evaluated through a dynamic system simulation with high fidelity in the Modelica platform. The dynamic model of the novel hybrid component named ‘dual purpose underground thermal battery’ was developed and validated. It was then incorporated into the system model. Given a time-of-use tariff, a rule-based control strategy was designed to shift the electric demand and switch the heat pump source for a typical single-family house in different climate zones of the United States. The system performance of the new TES-integrated dual-source heat pump was compared with that of a conventional air-source heat pump system. The results indicate that the proposed system can reduce the annual HVAC electricity cost by up to 52% while saving 45.2% on electricity consumption. In the Northern areas, the annual peak load of the HVAC system can be reduced by 64.9%. However, this reduction is less in the Southern areas as the system’s higher efficiency in winter dominates the overall energy-saving potential.

25 ENERGY STORAGE↗

A hierarchical framework for aggregating grid-interactive buildings with thermal and battery energy storage

The behind-the-meter (BTM) thermal and battery energy storage can help improve energy efficiency, reduce energy costs, and enhance energy resilience, particularly in rural areas and for disadvantaged communities. Aggregating numerous BTM energy storage systems can act as a price influencer with a significant source of load shifting and peak demand reduction. An integrated and scalable control mechanism is required to effectively utilize energy storage systems and flexible building loads to maximize the economic benefits, considering various distribution system constraints. Here, this paper presents an innovative hierarchical coordination framework for energy storage and flexible load in buildings, considering various factors such as electricity prices, thermal comfort, and distribution system modeling and constraints. At the upper level, a distribution system operator optimizes the power flow to minimize its power procurement costs from the electricity wholesale market, while at the lower level, aggregators determine the optimal dispatch of battery and thermal energy storage systems in multiple buildings on behalf of end-users to minimize operating costs according to the power prices. These problems are solved using a game-theoretic approach through negotiations between the distribution system operator and aggregators as a bi-level decision model. Simulation case studies have been performed for a test distribution network with a number of building end-users using energy storage systems to quantify the performance of aggregators. The results demonstrate that the proposed strategy can reduce peak load for a reliable electricity distribution network while saving electricity bills for customers.

25 ENERGY STORAGE↗

Yonkers Urban Development II: Leveraging NASA Earth Observations to Support Modeling Urban Cooling Interventions and Urban Heat Vulnerability in Yonkers, New York

The City of Yonkers, New York, located in Westchester County, is experiencing rising temperatures which are a growing threat to the health and safety of its residents. Furthermore, the risk of heat-related illnesses and mortality disproportionately affects neighborhoods in Yonkers historically subjected to race-based housing segregation. To better understand these inequities, Groundwork Hudson Valley and NASA DEVELOP collaborated for a second term to evaluate community-level heat vulnerability, landcover distribution, street-level thermal comfort, and modeled urban cooling interventions. This team applied 2019 5-year American Community Survey (ACS) data and social and biophysical heat vulnerability variables established by the New York State Department of Health (NYSDOH), along with land surface temperature (LST) data collected from Landsat 8 Thermal Infrared Sensor (TIRS), and ISS ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to identify communities in Yonkers in need of prioritized cooling intervention at the census tract level. Data from the Real-Time Mesoscale Analysis (RTMA) provided relevant meteorological data for the ENVI-met model to conduct street-level thermal observations and model tree canopy cooling interventions in the Yonkers neighborhoods of Kimball and Old 7th Ward. The project results will support the prioritization and equitable distribution of cooling infrastructure in identified neighborhoods. Additionally, Groundwork Hudson Valley will use the analyses as a heat literacy tool to improve advocacy efforts and inform both residents and officials about how investment in deliberate modification to tree canopy cover improves the city’s thermal environment and helps mitigate extreme heat.

Tamara Barbakova↗

Energy burden aware and thermal resilience informed thermal energy storage system planning for disadvantaged communities

Disadvantaged communities often face a disproportionate energy burden because they need to allocate a higher percentage of their income to energy costs. More importantly, climate change-induced extreme weather events, such as heat waves and severe cold snaps, exacerbate these communities’ energy burdens. As a result, low- and medium-income communities are more likely to experience energy supply disruptions, increased health risks, and elevated energy bills because of inadequate thermal insulation and airtightness in their houses. Thermal energy storage (TES) systems, such as large-scale (community-level) geothermal energy storage and small-scale (building-level) phase change material (PCM)–based storage, have a great potential to improve building energy efficiency and to enhance thermal comfort, load shifting, and integration with renewable energy. The objective of this study is to optimally allocate building level PCM-based TES systems at the community level by considering energy equity and extreme weather effects. To this end, we developed an energy burden and thermal resilience–informed TES system planning framework, which includes three modules: (1) a community-level energy burden and thermal resilience assessment module, (2) building-level a TES system integration and assessment module, and (3) a community-level optimal planning module. Case studies were conducted on four disadvantaged communities in Montgomery and Shelby Counties in Tennessee with energy burdens >10% and with high percentages of people of color. The results indicate that this comprehensive planning framework can assist disadvantaged communities in reducing their energy burden and in bolstering their resilience against the adverse effects of climate change.

Shen, Zhenglai↗

Dynamic Simulation of Human Thermoregulation and Heat Transfer for Spaceflight Applications

Models of human thermoregulation and heat transfer date from the early 1970s and have been developed for applications ranging from evaluating thermal comfort in spacecraft and aircraft cabin environments to predicting heat stress during EVAs. Most lumped or compartment models represent the body as an assemblage cylindrical and spherical elements which may be subdivided into layers to describe tissue heterogeneity. Many existing models are of limited usefulness in asymmetric thermal environments, such as may be encountered during an EVA. Conventional whole-body clothing models also limit the ability to describe local surface thermal and evaporation effects in sufficient detail. A further limitation is that models based on a standard man model are not readily scalable to represent large or small subjects. This work describes development of a new human thermal model derived from the 41-node man model. Each segment is divided into four concentric, constant thickness cylinders made up of a central core surrounded by muscle, fat, and skin, respectively. These cylinders are connected by the flow of blood from a central blood pool to each part. The central blood pool is updated at each time step, based on a whole-body energy balance. Results show the model simulates core and surface temperature histories, sweat evaporation and metabolic rates which generally are consistent with controlled exposures of human subjects. Scaling rules are developed to enable simulation of small and large subjects (5th percentile and 95th percentile). Future refinements will include a clothing model that addresses local surface insulation and permeation effects and developing control equations to describe thermoregulatory effects such as may occur with prolonged weightlessness or with aging.

Miller, Thomas R.↗

Reinforcement Learning Control for Buildings Co-Optimizing Energy, Comfort, and Indoor Air Quality: An Annual Assessment

Efficient control of Heating, Ventilation, and Air Conditioning (HVAC) systems is crucial for optimizing energy use and maintaining indoor comfort in buildings. Traditional control methods, such as PID control, cannot handle energy use trade-offs among multiple components in the building energy system at a supervisory level. Reinforcement learning (RL) presents a promising solution, offering adaptive and data-driven control strategies that optimize performance over time. However, RL also faces several challenges, including the conflicts encountered in co-optimizing energy savings, occupant comfort, and indoor air quality, and the requirement for extensive interactions with the environment in training. We proposed a flexible simulation platform that integrates a hybrid model for RL training and designed an RL agent to control the entire central HVAC system, focusing on co-optimizing energy consumption, thermal comfort, and indoor air quality ($\text{CO}_{2}$ and PM2.5 concentrations). Finally, we evaluated the RL agent's performance over an annual cycle. Our findings indicate that the RL agent can effectively manage the HVAC system with 14.7 % energy savings annually and balance multiple objectives, which demonstrates significant potential for improving HVAC system control and sustainability in buildings.

Guo, Fangzhou↗

Impact analysis of personalized thermostat demand response

Demand response (DR) aims to curtail peak electric load to avoid running inefficient power plants, reduce costly transmission capacity increases, and improve grid reliability. One method of DR for residential settings involves the utility or third part remotely adjusting thermostat temperatures. Cooling setpoints may be increased 2°F – 6°F for hours, irrespective of occupant comfort. To maintain their comfort, occupants override these setpoint changes impacting the reliability of DR services provided to the grid. This paper presents a preliminary impact analysis of replacing the current DR approach of uniform thermostat setbacks for an entire population with personalized and context aware DR based on a dynamic model of occupant thermal comfort behavior. Over 151k interactions with ecobee thermostats are analyzed to predict the impact of such personalized DR on overrides, energy curtailment magnitude, and reliability.

Kane, Michael↗

Two-point and multiple-point spot heating and cooling

Apparatus and methods for producing thermal comfort using two point or multipoint heating or cooling that is applied to portion of a human body part to produce a warm or cool sensation over a larger area than that where the heating or cooling is directly applied. The body is induced to heat or cool itself by adjusting its neutral temperature setpoints. Increased warming perception from two-point, multipoint, and switching point stimulation causes downward adaptation in the neutral skin temperature of the user. Because spot heating and cooling sources operate at higher temperature differences from the skin than do area sources, they create a stronger perceived thermal sensation for the same power consumption. Point heating or cooling, rather than whole-area heating, can result in power savings and cost savings while improving occupant comfort.

Arens, Edward↗

Investigation of pre-cooling as a recommended measure to improve residential buildings’ thermal resilience during heat waves

More intense heat waves are expected to occur more frequently in the twenty-first century. During severe heat waves, cooling capacity shortfall and overheating are likely to occur in residential buildings, and this will adversely affect occupant's thermal comfort and productivity. We propose a strategy of pre-cooling the house during off-peak hours to mitigate overheating during heat waves. Additionally, simulation results of a prototype single-family house show that adopting the rule-based control (RBC) of pre-cooling thermostat setpoint schedule is effective in reducing thermal discomfort, and that the efficacy of pre-cooling depends upon several building characteristics. An optimized control (OC) of the thermostat setpoint schedule was developed based on the simulation of a prototype building. A simplified yet improved RBC (IRBC) pre-cooling schedule was then extracted from the OC schedule for practical implementation at a larger scale. The effects of the RBC schedule and IRBC schedule were evaluated in the King District of Fresno, which contains 814 residential buildings. Results show that both thermostat setpoint schedules can reduce overheating effectively and that IRBC is slightly better than RBC for most buildings. The findings support the California government's recommendation on pre-cooling to mitigate overheating, which can be further improved with an optimized thermostat setpoint schedule broadcast to residents through early alert messages before a heat wave.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Sensor Impact Evaluation at Different Sensor Locations in a Multi-zone Office Building

FY 2022 Q1 deliverables include the development of an emulator that can evaluate the sensor impacts at different sensor locations (i.e., thermostat locations) in a multizone office building. This report presents the detailed procedure of developing the emulator and using the emulator for preliminary sensor impact analysis. In designing new multizone buildings or retrofitting existing buildings, the room thermostat locations or subzoning design has been often determined by best practices without considering the effects of this design in terms of energy or thermal comfort. In subzoning design, the total number of thermostats is usually smaller than the total number of rooms. As a result, one thermostat in one room often controls the indoor temperature of several other adjacent rooms. For example, five zones might share one thermostat located in one of the zones. Because the demands for thermal load in different zones could be different for the multizone buildings, this subzoning design can compromise control performance and waste building energy consumption. Furthermore, for multizone buildings, subzoning could introduce thermal discomfort for zones. This issue has not be thoroughly investigated in simulation/field studies, and the US Department of Energy’s Oak Ridge National Laboratory explored the impacts of subzoning design through modeling and experimental study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Quantifying Occupant Health and Productivity for Deep Retrofits: Beyond Traditional IEQ Studies

As energy-efficiency standards for both new construction and existing building renovations become more stringent, further reductions become less tractable and more expensive. With increasing interest and rising investment in healthy built environments, integrating energy efficiency with improved occupant experience (i.e., health, comfort, and work performance) offers a new path to drive deep energy retrofits. However, the difficulty in quantifying and verifying health and productivity gains from building upgrades leads to lower valuation of human benefits in practice. Building codes and standards have progressive energy targets but often give minimum requirements to occupant health for factors such as ventilation and thermal comfort. State and federal laws in the United States that govern the energy service performance contract (ESPC) have no clear and consistent guidance on quantifying non-energy benefits and incorporating them into a formal cost-effectiveness analysis. This paper presents a methodology to measure a building’s potential performance improvement regarding occupant health based on existing evidence correlating IEQ to occupant outcomes. Health improvement measures are integrated with a building energy model to identify and measure the impact of holistic improvement strategies. The net present value of these measures is determined based on the investment costs required to attain those improvements, energy savings, and personnel gains. We will discuss results from one pilot building, which showed nearly $50 per square foot 20-year net present value using the integrated approach.

Keene, Kevin M.↗

Building energy efficiency and load flexibility optimization using phase change materials under futuristic grid scenario

This work investigates the energy savings and load flexibility capacity of phase change material (PCM) integrated into building envelope under a future energy generation scenario, where 80% of the energy load comes from renewable sources. Using community-scale modeling, we first determine the net thermal storage required to fully manage the demand variability at a utility grid, and then using whole-building simulations we optimize operating parameters - such as PCM thickness, latent heat, interior setpoint profile, PCM distribution, and heat transfer coefficient - to determine the optimal conditions required for maximum energy reduction and load flexibility without compromising occupants' thermal comfort. The optimal PCM-integrated envelope proposed in this study can provide annual load flexibility up to 33.6% and annual energy savings up to 10.8% in a lightweight residential building located in Baltimore, MD. This study is relevant given the increasing contributions of renewable energy in the total energy generation mix, leading to a significant time-imbalance between peak energy demand and peak energy production. While thermal energy storage using PCM is a recognized technique, there is no known prior study dedicated to examining the thermal performance of PCM-integrated envelope under future energy generation scenarios. This study bridges the research gap by investigating a practical way to implement PCMs in the buildings and maximize the energy efficiency as well as load flexibility related benefits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Comparing land surface temperature and mean radiant temperature for urban heat mapping in Philadelphia

Many cities are experiencing more frequent extreme heat during hot summers. With the rise of global temperature, the thermal comfort in urban areas become even worse. Quantitative information of the spatial distributions of urban heat has become increasingly important for resilience and adaptation to climate change in cities. This study compares satellite-derived land surface temperature (LST) and urban microclimate modeling-based mean radiant temperature (Tmrt) for mapping the urban heat distributions in Philadelphia, Pennsylvania, USA. Here, the LST was estimated based on Landsat 8 thermal imagery with a spatial resolution of around 100 m, while the Tmrt was simulated based on high resolution LiDAR and national aerial imagery program multispectral aerial imageries with a spatial resolution of 1 m. Result shows that both LST and Tmrt show a similar general pattern of the urban heat across the study area, while the Tmrt presents much more details of the heat variations street by street and neighborhood by neighborhood. The LST tends to have a stronger relationship with the Tmrt on building roofs, which are usually not the place for human activities. This studyprovides evidence for choosing more appropriate metrics in urban heat-related studies.

54 ENVIRONMENTAL SCIENCES↗

Optimizing HVAC Operations in Multi-unit Buildings for Grid Demand Response

The thermal inertia of buildings, along with the flexibility associated with thermostatically controlled loads (TCL) allows heating ventilation and cooling (HVAC) systems to be used for grid demand response (DR). In this work, we consider an HVAC system that serves multiple units in a residential building to meet their space heating requirements. We aim to determine the optimal power flow to each unit that minimizes the power costs incurred by the building's occupants while keeping in consideration their thermal comfort. The DR program is assumed to allow the building temperatures to deviate from the set-points up to a maximum limit. Despite the complex, non-linear structure of the problem, we show how the optimal solutions can be obtained efficiently using quadratic programming. Since HVAC systems can run on either electricity or natural gas, we study the efficacy of the DR regime for both hourly electricity prices and flat gas prices over the course of 24 hours. Finally, we run simulations to determine the optimal thermal power and the evolution of unit temperatures for various energy pricing schemes.

Naqvi, Syed A.↗

Bio-Contamination Control for Spacesuit Garments - A Preliminary Study

This paper outlines a preliminary study to review, test, and improve upon the current state of spacesuit bio-contamination control. The study includes an evaluation of current and advanced suit materials, ground and on-orbit cleaning methods, and microbial test and analysis methods. The first aspect of this study was to identify potential anti-microbial textiles and cleaning agents, and to review current microbial test methods. The anti-microbial cleaning agent and textile market survey included a review of current commercial-off-the-shelf (COTS) products that could potentially be used as future space flight hardware. This review included replacements for any of the softgood layers that may become contaminated during an extravehicular activity (EVA), including the pressure bladder, liquid cooling garment, and ancillary comfort undergarment. After a series of COTS anti-microbial textiles and clean ing agents were identified, a series of four tests were conducted: (1) a stacked configuration test that was conducted in order to review how bio-contamination would propagate through the various suit layers, (2) a individual materials test that evaluated how well each softgood layer either promoted or repressed growth, (3) a cleaning agent test that evaluated the efficacy on each of the baseline bladders, and (4) an evaluation of various COTS anti-microbial textiles. All antimicrobial COTS materials tested appeared to control bacteria colony forming unit (CFU) growth better than the Thermal Comfort Undergarment (TCU) and ACES Liquid Cooling Garment (LCG)/EMU Liquid Cooling Ventilation Garment (LCVG) materials currently in use. However, a comparison of fungi CFU growth in COTS to current suit materials appeared to vary per material. All cleaning agents tested in this study appeared to inhibit the level of bacteria and fungi growth to acceptable levels for short duration tests. While several trends can be obtained from the current analysis, a series of test improvements are described for future microbial testing.

Rhodes, Richard↗

How good are learning-based control v.s. model-based control for load shifting? Investigations on a single zone building energy system

Both model predictive control (MPC) and deep reinforcement learning control (DRL) have been presented as a way to approximate the true optimality of a dynamic programming problem, and these two have shown significant operational cost saving potentials for building energy systems. Furthermore, there is still a lack of in-depth quantitative studies on their approximation levels to the true optimality, especially in the building energy domain. To fill in the gap, this paper provides a numerical framework that enables the evaluation of the optimality levels of different controllers for building energy systems. This framework is then used to comprehensively compare the optimal control performance of both MPC and DRL controllers with given computation budgets for a single zone fan coil unit system. Note the optimality is estimated based on a user-specific selection of trade-off weights among energy costs, thermal comfort and control slew rates. Compared with the best optimality we can find through expensive optimization simulations, the best DRL agent can maximally approximate the optimality by 96.54%, which outperforms the best MPC whose optimality level is 90.11%. However, due to the stochasticity, the DRL agent is only expected to approximate the optimality by 90.42%, which is almost equivalent to the best MPC. Except for Proximal Policy Optimization (PPO), all DRL agents can have a better approximation to the optimality than the best MPC, and are expected to have better approximation than the MPC with a prediction horizon of 32 steps (15 min per step). In terms of reducing energy cost and thermal discomfort, MPC can outperform the rule-based control (RBC) by 18.47%–25.44%. DRL can be expected to outperform RBC by 18.95%–25.65% ,and the best DRL control policy can outperform RBC by 20.29%–29.72%. Although the comparison of the optimality level is performed in a perfect setting, e.g., MPC assumes perfect models, and DRL assumes a perfect offline training process and online deployment process, this can shed insight on their capabilities of approximating to the original dynamic programming problem.

24 POWER TRANSMISSION AND DISTRIBUTION↗