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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 OSTI2022

Systems and methods for radiative cooling and heating

Systems and methods for radiative cooling and heating are provided. For example, systems for radiative cooling can include a top layer including one or more polymers, where the top layer has high emissivity in at least a portion of the thermal spectrum and an electromagnetic extinction coefficient of approximately zero, absorptivity of approximately zero, and high transmittance in at least a portion of the solar spectrum, and further include a reflective layer including one or more metals, where the reflective layer has high reflectivity in at least a portion of the solar spectrum.

Yu, Nanfang↗
DOE OSTI2023

Systems and methods for radiative cooling and heating

Systems and methods for radiative cooling and heating are provided. For example, systems for radiative cooling can include a top layer including one or more polymers, where the top layer has high emissivity in at least a portion of the thermal spectrum and an electromagnetic extinction coefficient of approximately zero, absorptivity of approximately zero, and high transmittance in at least a portion of the solar spectrum, and further include a reflective layer including one or more metals, where the reflective layer has high reflectivity in at least a portion of the solar spectrum.

Yu, Nanfang↗
DOE OSTI2023

A General Purpose Real-Time Optimization Strategy Applied to Minimizing Simultaneous Heating and Cooling in Buildings

Supervisory control strategies in heating, ventilating, and air-conditioning (HVAC) systems hold the potential for significant energy savings but they are difficult to set up and often depend on unreliable sensor measurements. In this paper, we propose a sensor-free approach to minimizing the energy penalties due to simultaneous heating and cooling in variable-air-volume (VAV) systems with reheat. A general-purpose real-time optimizer is described that is easy to set-up and integrate with existing control logic. A cost function is derived that quantifies the simultaneous heating and cooling penalty that does not require any sensor measurements. The optimizer then minimizes this cost function by automatically adjusting the supply temperature setpoint in the air-handling unit. The paper describes the approach and shows results from application from field trials on a 27-zone building.

Salsbury, Timothy↗
DOE OSTI2025

Electrical and Thermal Load Impacts of Three District Heating and Cooling Designs for an Existing Community in Washington, DC

District energy systems that provide building heating and cooling are a promising option to provide low-cost, energy efficient heating and cooling solutions for communities. As some buildings move to electrified heating designs, there may be significant increases in electric grid demand, particularly in the winter. District energy systems may be able to help reduce these high electrical demands on the electric grid, while also providing decreased overall energy consumption with an increased flexibility in electrical energy usage. To evaluate and compare district options for district-based heating and cooling, an existing neighborhood of Washington, DC consisting of 35 existing buildings was selected as a case study. This study models and compares a fourth generation (4G) district heating and cooling systems that provide hot and chilled water from a central plant directly to each prosumer and a fifth generation (5G) district heating and cooling systems that provide near-ambient water via geothermal boreholes to interface with an energy transfer station with a heat pump at each prosumer. These district systems are compared against a baseline of the non-connected buildings with their self-contained and current HVAC systems. The neighborhood was selected as a good candidate for a district system for its diversity of loads (mix of different commercial and property types) and the availability of building characteristics. URBANopt District Energy Systems (DES) was used to model the buildings and create initial Modelica models for the district systems. Finally, the DES models were tuned and simulated in Dymola, and the outputs were post-processed for verification and to calculate the electrical and thermal grid impact metrics. This is the first documentation of this workflow and its complete analysis. The three designed systems are compared via their grid metrics including: total energy consumption, electrical demand peak loads, daily peak-to-valley ratios, and system ramping. A detailed discussion is provided about how each system impacts and interacts with the electric grid.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Exploring the dependence of gas cooling and heating functions on the incident radiation field with machine learning

ABSTRACT Gas cooling and heating functions play a crucial role in galaxy formation. But, it is computationally expensive to exactly compute these functions in the presence of an incident radiation field. These computations can be greatly sped up by using interpolation tables of pre-computed values, at the expense of making significant and sometimes even unjustified approximations. Here, we explore the capacity of machine learning to approximate cooling and heating functions with a generalized radiation field. Specifically, we use the machine learning algorithm XGBoost to predict cooling and heating functions calculated with the photoionization code cloudy at fixed metallicity, using different combinations of photoionization rates as features. We perform a constrained quadratic fit in metallicity to enable a fair comparison with traditional interpolation methods at arbitrary metallicity. We consider the relative importance of various photoionization rates through both a principal component analysis (PCA) and calculation of SHapley Additive exPlanation (shap) values for our XGBoost models. We use feature importance information to select different subsets of rates to use in model training. Our XGBoost models outperform a traditional interpolation approach at each fixed metallicity, regardless of feature selection. At arbitrary metallicity, we are able to reduce the frequency of the largest cooling and heating function errors compared to an interpolation table. We find that the primary bottleneck to increasing accuracy lies in accurately capturing the metallicity dependence. This study demonstrates the potential of machine learning methods such as XGBoost to capture the non-linear behaviour of cooling and heating functions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The reservoir network: A new network topology for district heating and cooling

Thermal district networks are effective solutions to substitute fossil fuels with renewable energy sources for heating and cooling. Moreover, thermal networking of buildings allows energy efficiency to be further increased. The waste heat from cooling can be reused for heating in thermal district systems. Because of bidirectional energy flows between prosumers, thermal networks require new hydraulic concepts. In this work, we present a novel network topology for simultaneous heating and cooling: the reservoir network. The reservoir network is robust in operation due to hydraulic decoupling of transfer stations, integrates heat sources and heat sinks at various temperature levels and is flexible in terms of network expansion. Furthermore, we used Modelica simulations to compare the new single-pipe reservoir network to a basecase double-pipe network, taking yearly demand profiles of different building types for heating and cooling. The electric energy consumed by the heat pumps and circulations pumps differs between the reservoir and base case networks by less than 1%. However, if the reservoir network is operated with constant instead of variable mass flow rate, the total electrical consumption can increase by 48% compared to the base case. As with any other network topology, the design and control of such networks is crucial to achieving energy efficient operation. Investment costs for piping and trenching depend on the district layout and dimensioning of the network. If a ring layout is applied in a district, the reservoir network with its single-pipe configuration is more economical than other topologies. For a linear layout, the piping costs are slightly higher for the reservoir network than for the base case because of larger pipe diameters.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Plate heat exchanger for heating or cooling bulk solids

A heat exchanger includes an inlet for receiving bulk solids, a plurality of heat transfer plate assemblies, a plurality of spacers disposed between adjacent heat transfer plate assemblies, and supports for supporting the heat transfer plate assemblies. The heat transfer plate assemblies include a first plate having a first pair of holes extending therethrough, the first plate having channels extending along a surface thereof, for the flow of fluid through the channels, and a second plate bonded to the first plate to enclose the channels, the second plate including a second pair of holes generally aligned with the first pair of holes to form through holes to facilitate flow of the fluid through the through holes and the channels.

Byman, Ashley D.↗
DOE OSTI2023

Geospatial Characterization of Low-Temperature Heating and Cooling Demand in the United States

Geothermal resources at temperatures below 150 degrees C have great potential as energy sources for various direct-use applications including heating and cooling in residential and commercial buildings. This study geospatially quantifies U.S. heating and cooling demand in residential, commercial, and manufacturing sectors; heating demand in the agricultural sector; and cooling demand in data centers at the county level through end-use energy consumption, expenditure, and commissioned power analyses. Heating and cooling demand in the residential sector was estimated using energy consumption data obtained from the U.S. Energy Information Administration accounting for different U.S. climate zones. For commercial sector analysis, the end-use major fuel energy intensity at the census division level was disaggregated to the county level with respect to principal building activities. Heating and cooling demand analysis for the manufacturing sector was based on end-use energy consumption for direct-use total process categorized by the North America Industry Classification System. Fuel expenditures in the U.S. Department of Agriculture Farm Production Expenditures were examined for heating demand analysis in the agricultural sector, particularly for the greenhouse, nursery, and floriculture production category. Lastly, commissioned power for data centers in the United States were explored for cooling demand analysis. Results indicated a significant fraction of U.S. primary energy consumption is used for low-temperature heating and cooling applications. Heating and cooling demand in residential and commercial sectors is significantly affected by the number of housing units and climate zone designations, while heating and cooling demand in manufacturing and agricultural sectors and data centers are mainly dependent on the number of facilities and their locations. Maps were generated visualizing where heating and cooling demand is high and, overlain with geothermal resource maps, can indicate locations where geothermal energy can supply this heating and cooling demand.

cooling demand↗
DOE OSTI2023

Geospatial Characterization of Low-Temperature Heating and Cooling Demand in the United States: Preprint

Geothermal resources at temperatures below 150 degrees C have great potential as energy sources for various direct-use applications including heating and cooling in residential and commercial buildings. This study geospatially quantifies U.S. heating and cooling demand in residential, commercial, and manufacturing sectors; heating demand in the agricultural sector; and cooling demand in data centers at the county level through end-use energy consumption, expenditure, and commissioned power analyses. Heating and cooling demand in the residential sector was estimated using energy consumption data obtained from the U.S. Energy Information Administration accounting for different U.S. climate zones. For commercial sector analysis, the end-use major fuel energy intensity at the census division level was disaggregated to the county level with respect to principal building activities. Heating and cooling demand analysis for the manufacturing sector was based on end-use energy consumption for direct-use total process categorized by the North America Industry Classification System. Fuel expenditures in the U.S. Department of Agriculture Farm Production Expenditures were examined for heating demand analysis in the agricultural sector, particularly for the greenhouse, nursery, and floriculture production category. Lastly, commissioned power for data centers in the United States were explored for cooling demand analysis. Results indicated a significant fraction of U.S. primary energy consumption is used for low-temperature heating and cooling applications. Heating and cooling demand in residential and commercial sectors is significantly affected by the number of housing units and climate zone designations, while heating and cooling demand in manufacturing and agricultural sectors and data centers are mainly dependent on the number of facilities and their locations. Maps were generated visualizing where heating and cooling demand is high and, overlain with geothermal resource maps, can indicate locations where geothermal energy can supply this heating and cooling demand.

cooling demand↗
DOE OSTI2022

Coupling Subsurface and Above-Surface Models for Optimizing the Design of Borefields and District Heating and Cooling Systems

Accurate dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange for seasonal energy storage. Current modeling approaches in building and district energy simulation tools typically consider heat conduction through the ground between boreholes without flowing groundwater. While detailed simulation tools for subsurface heat and mass transfer exist, these fall short in simulating above-surface energy systems. To support the design and operation of such systems, the study developed a coupled model including a software package for building and district energy simulation, and software for detailed heat and mass transfer in the subsurface. For the first, it uses the open-source Modelica Buildings Library, which includes dynamic simulation models for building and district energy and control systems. For the heat and mass transfer in the soil, it uses the TOUGH simulator. The TOUGH family of codes can model heat and multi-phase, multi-component mass transport for a variety of fluid systems, as well as chemical reactions, in fractured porous media. The study validated the coupled modeling approach by comparing the simulation results with one from the g-function based ground response model. It then looked into effects when the water table and the regional groundwater flow are considered in the ground, from the perspective of heat exchange between borehole and ground, and the electrical consumption of the district heating and cooling systems. To access the simulation models, please find the links in the submission: -- For coupled approach validation: see model Buildings.Fluid.Geothermal.Borefields.Examples.BorefieldsWithTough and Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from the "Modelica Building Library" resource, branch issue1495_tough_interface, commit a2667c0. -- For the study of the effect of water table: see model Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO, commit 760de49. -- For the study of the effect of regional groundwater flow: see Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO_3D, commit c2a2d2a. The coupling interface script "GrounResponse.py" can be found from the above links in the folder Buildings/Resources/Python-Sources. Also, the needed files for TOUGH simulation are in the folder Buildings/Resources/Python-Sources/ToughFiles that can be accessed through the above links. A brief description of these files is given below; detailed specifications for the first three files may be found in the TOUGH3 Users Guide (Jung et al., 2018) https://tough.lbl.gov/documentation/tough-manuals/. (1) INCON - initial conditions for each grid block (2) INFILE - main input file with material properties and control parameters (3) MESH - description of the computational grid (4) readsave - Modelica/TOUGH interface program: read the final output of TOUGH simulation after TOUGH time step and prepare for transfer to Modelica for next Modelica time step (5) readsave.inp - input parameters for program readsave (6) writeincon - Modelica/TOUGH interface program: write the output of Modelica after Modelica time step and prepare for transfer to TOUGH as initial conditions for the next TOUGH step (7) writeincon.inp - input parameters for program writeincon

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Fifth-Generation District Heating and Cooling Substations: Demand Response with Artificial Neural Network-Based Model Predictive Control

District heating and cooling (DHC) is considered one of the most sustainable technologies to meet the heating and cooling demands of buildings in urban areas. The fifth-generation district heating and cooling (5GDHC) concept, often referred to as ambient loops, is a novel solution emerging in Europe and has become a widely discussed topic in current energy system research. 5GDHC systems operate at a temperature close to the ground and include electrically driven heat pumps and associated thermal energy storage in a building-sited energy transfer station (ETS) to satisfy user comfort. This work presents new strategies for improving the operation of these energy transfer stations by means of a model predictive control (MPC) method based on recurrent artificial neural networks. The results show that, under simple time-of-use utility rates, the advanced controller outperforms a rule-based controller for smart charging of the domestic hot water (DHW) thermal energy storage under specific boundary conditions. By exploiting the available thermal energy storage capacity, the MPC controller is capable of shifting up to 14% of the electricity consumption of the ETS from on-peak to off-peak hours. Therefore, the advanced control implemented in 5GDHC networks promotes coupling between the thermal and the electric sector, producing flexibility on the electric grid.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Design Heating and Cooling Load Calculation Versus Building Load Simulation for Cold Climate Heat Pumps: Understanding the "Gap"

This report explores the differences between Manual J-equivalent block load calculations and building HVAC energy simulation results using EnergyPlus™ calculations when designing cold climate heat pump systems for residential use. This study will help HVAC researchers and advanced designers understand the impacts of oversizing heat pumps on home energy use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Application of thermal energy storage with electrified heating and cooling in a cold climate

Ground source heat pumps (GSHPs) have been shown to be an effective means of decarbonizing building heating and cooling, but the operation of these systems at scale presents challenges to sites and the grid due to increases in peak demand. Here, in this study, we investigate how the use of Thermal Energy Storage (TES), in the form of stratified water storage, could reduce the peak daily demand associated with GSHP systems and thus improve their cost effectiveness. This system was compared to a Combined Heat and Power (CHP) plant, to investigate the potential cost and emissions impacts of electrification on large energy users transitioning from high efficiency fossil fuel equipment. This study builds on previous research by using a significant campus area, and investigating the various impacts of an electrified system versus a state of the art fossil fuel system. An established method of TRNSYS modeling is used for the heat pumps and borehole heat exchangers (BHEs), along with the TES. The GSHP system with TES is modeled to follow industry standards and sized to provide an optimal balance of capital and operating costs. Costs were investigated for a unique large energy user rate structure, as well as for a more common generalized rate structure. The results show that the addition of TES to the GSHP system could reduce operating costs by 4.5%, but still incurs a 5.64% cost increase from the baseline CHP system. It is also shown, however, that a tactical integration of heat pumps into the CHP system is the most cost effective solution, only increasing the operating costs by 4.71%. Likewise, the impacts of different rate structures are highlighted, with the TES only resulting in 0.75% cost savings under the generalized utility rate. Furthermore, it is shown that thermal storage has great potential for demand reduction, with the addition of storage incurring a decrease of 7–22% in annual peak demand kW, dependent on the rate structure.

25 ENERGY STORAGE↗
DOE OSTI2022

Heating and Cooling Energy Modeling of 3D-Printed Concrete Construction of Residential Buildings [Slides]

3D printed concrete construction (C3DP) is an emerging technology that comes with the associated benefits of high thermal mass walls. We investigated using BEopt software the heating and cooling energy use of a single story C3DP-constructed house. We then compared the heating/cooling energy use of the C3DP house against the corresponding energy use in a traditional timber (wood) frame construction (WFC), as well as a concrete masonry unit (CMU) construction. Both peak energy use for heating and cooling (Btu), as well as base energy use for both heating and cooling (MMBtu/yr) of the C3DP design were compared against the WFC and CMU baseline construction of identical geometries and orientations across all eight climate zones defined in the International Energy Conservation Code (IECC). The BEopt models for all three constructions (C3DP, WFC, and CMU) were built to comply with the 2018 IECC code. Results indicate that C3DP construction has significant heating and cooling energy benefits in certain climate zones, with the highest peak cooling energy savings (9% compared to WFC, and 5% compared to CMU) in the IECC Climate Zone 1 in the month of July. The peak heating and cooling energy demand reduction of C3DP were found to be more significant than the base heating and cooling energy demand in all IECC climate zones. The 2018 IECC compliance-related U-Factor adjustments of all models also resulted in more peak energy savings of the C3DP design in the cooling-dominated climate zones (climate zones 1 and 2), moderate energy savings in moderate climate zones (climate zones 3, 4, and 6), and little to no change in energy savings in very cold climates (climate zones 7 and 8).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

helios: An R package to process heating and cooling degrees for GCAM

helios is an open-source R package that estimates population-weighted heating and cooling degree-hours (HDH and CDH) and degree-days (HDD and CDD) at various temporal (e.g., energy dispatch segments, monthly, yearly) and spatial scales (e.g., U.S. states, global political regions, countries). The degree hour and degree day outputs from helios are used to inform electricity demand load in the Global Change Analysis Model (GCAM) as well as in GCAM-USA (which is the version of GCAM with U.S. state-level details). helios uses a workflow with four steps: processing raw data; calculating heating and cooling degrees; visualizing performance diagnostics; and outputing results in various formats. There are two sources of widely-used climate data compatible with helios: (1) hourly climate data with 12-km resolution that are dynamically downscaled with the Weather Research and Forecasting (WRF) model and projected using a thermal global warming (TGW) approach; and (2) daily climate data with 0.5-degree resolution from the Coupled Model Intercomparison Project (CMIP) that is bias-adjusted and statistical downscaled by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). In summary, helios is a model that standardizes methodology of heating and cooling degrees-hours and degree-days using publicly available data and advance the understanding of the impact of spatial and temporal temperature variability on building energy services.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Component-Level Analysis of Heating and Cooling Loads in the U.S. Residential Building Stock

The residential building sector accounts for a substantial portion of total energy consumption in the United States and offers a significant opportunity for energy reduction and decarbonization through improvements in energy efficiency. Heating and air conditioning are the primary contributors to residential energy usage and electricity system peak demand. However, due to the diversity of the housing stock and the complexity of factors affecting heating and cooling demand, identifying the relative contributions to heating and cooling loads poses challenges. To address this, we applied the ResStock analysis tool to simulate 550,000 building energy models, providing statistical representation of residential buildings in the contiguous United States. We introduced outputs that quantified the heating and cooling influence of different components of a home, such as air leakage, envelope components (ceilings, walls, windows, foundations), internal heat gains from people, lighting, plug loads, and duct losses and gains. Leveraging the granularity of ResStock, we present a dataset to enable deeper understanding of the contributors to heating and cooling loads as a function of housing characteristics such as location, envelope efficiency, and building type. This work aims to support prioritization of research and development and informed decision-making for residential building decarbonization.

building simulation↗
DOE OSTI2024

Techno-economic feasibility of geothermal energy production using inactive oil and gas wells for district heating and cooling systems in Tuttle, Oklahoma

Oil and gas wells have been drilled in the United States and often encounter hot co-produced water possibly suitable for geothermal direct-use applications. Here this study evaluated geothermal resources, heating and cooling demand, and techno-economic potential of four oil and gas wells repurposed for geothermal energy production to serve two public schools and 250 nearby houses in Tuttle, Oklahoma, USA. Subsurface geology in the study area primarily consists of Permian to Mississippian sandstone and limestone formations approximately from 2 km to 3.5 km depth. With a geothermal gradient of 25.3 °C/km, the temperature of geothermal energy production was estimated as 68.2 °C at 2.1 km. The potential of calcite scaling within boreholes and pipes was minimal. Using the characterized reservoir properties, techno-economic analyses were conducted for evaluating levelized costs of geothermal energy production for direct-use heating and cooling and district heating systems with five different production scenarios. Heating and cooling demand in two schools and 250 houses and additional 0.3 MW and 0.6 MW base heating loads for potential geothermal direct-use applications in the study area were also incorporated in the modeling. Results indicated that the levelized cost of heating of geothermal district heating systems utilizing existing wells were significantly lower than those of conventional geothermal energy systems that include well drillings. The geothermal energy production with doublet and quartet configurations was generally sufficient to supply total annual heating demand in the district, while a peaking boiler was used to supply peak loads. Doublet configurations showed higher production temperature with a lower thermal drawdown than the quartet configurations. The doublet system at 2.1 km production depth with 9.3 kg/s flow rate represented the optimal levelized cost of $71/MWh and 91.2% utilization factor. These results imply that the Tuttle geothermal district heating system is techno-economically feasible and comparable to geothermal district heating systems in the United States and the regional natural gas rate for residentials by recycling inactive oil and gas wells with no drillings.

15 GEOTHERMAL ENERGY↗