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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Assessment of advanced solvent-based post-combustion CO 2 capture processes using a bi-objective optimization technique

We report the optimized performance of two advanced CO 2 capture processes is compared to that of a monoethanolamine (MEA) baseline for a gas-powered CO 2 capture retrofit of an existing coal-fired facility. The advanced temperature-swing processes utilize piperazine and mixed-salt solvents. The mixed-salt treatment involves the use of ammonia for CO 2 absorption and potassium carbonate primarily to control ammonia slip. The processes are represented in terms of energy duty requirements within a modular heat integration code developed for CO 2 capture modeling and optimization. The model includes a baseload coal plant, a gas-fired subsystem containing gas turbines and a heat recovery steam generator (HRSG), and a CO 2 capture facility. A formal bi-objective optimization procedure is applied to determine the design (e.g., detailed HRSG components and pressure levels, gas turbine capacity, CO 2 capture capacity) and time-varying operations of the facility to simultaneously maximize net present value (NPV) and minimize total capital requirement (TCR), while meeting a maximum CO 2 emission intensity constraint. For a realistic scenario constructed using historical data, optimization results indicate that both advanced processes outperform MEA in both objectives, and the mixed-salt process in turn outperforms the piperazine process. Specifically, for the scenario considered, the base case mixed-salt process achieves 16% greater NPV and 14% lower TCR than the MEA process, and 10% greater NPV and 5% lower TCR than the piperazine process. A five-case sensitivity study of the mixed-salt process indicates that it is competitive with the piperazine process and consistently outperforms the MEA process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Modeling of HVAC operational faults in building performance simulation

Operational faults are common in the heating, ventilating, and air conditioning (HVAC) systems of existing buildings, leading to a decrease in energy efficiency and occupant comfort. Various fault detection and diagnostic methods have been developed to identify and analyze HVAC operational faults at the component or subsystem level. However, current methods lack a holistic approach to predicting the overall impacts of faults at the building level—an approach that adequately addresses the coupling between various operational components, the synchronized effect between simultaneous faults, and the dynamic nature of fault severity. This study introduces the novel development of a fault-modeling feature in EnergyPlus which fills in the knowledge gap left by previous studies. This paper presents the design and implementation of the new feature in EnergyPlus and discusses in detail the fault-modeling challenges faced. The new fault-modeling feature enables EnergyPlus to quantify the impacts of faults on building energy use and occupant comfort, thus supporting the decision making of timely fault corrections. Including actual building operational faults in energy models also improves the accuracy of the baseline model, which is critical in the measurement and verification of retrofit or commissioning projects. As an example, EnergyPlus version 8.6 was used to investigate the impacts of a number of typical operational faults in an office building across several U.S. climate zones. Finally, the results demonstrate that the faults have significant impacts on building energy performance as well as on occupant thermal comfort. Finally, the paper introduces future development plans for EnergyPlus fault-modeling capability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
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 OSTI2021

Technoeconomic assessment of hydrogen cogeneration via high temperature steam electrolysis with a light-water reactor

Increased electricity production from renewable energy resources, coupled with low natural gas (NG) prices, has caused existing light-water reactors (LWRs) to experience diminishing returns from the electricity market. This reduction in revenue is forcing LWRs to consider alternative revenue streams, such as introduction hydrogen production or desalination, to remain profitable. This paper performs a technoeconomic assessment (TEA) regarding the viability of retrofitting existing pressurized-water reactors (PWRs) to produce green hydrogen (H 2 ) via high-temperature steam electrolysis (HTSE). Such an integration would allow nuclear facilities to expand into additional markets that may be more profitable in the long term and eliminate CO 2 emissions from the hydrogen production process. Here, to accommodate such an integration, a detailed single market levelized cost of hydrogen (LCOH) and multimarket analyses were conducted of HTSE process operation, requirements, costing, and flexibility. Alongside this costing analysis, market analyses were conducted on the electric and hydrogen markets in the PJM interconnect. Utilizing a novel stochastic, dispatch optimization approach results suggest that a positive gain is achievable, and by operating in multiple markets, the nuclear facility can avoid the sale of electricity during times of low electricity market pricing, while maintaining the ability to capitalize on the high electricity market pricing. It should be noted that the analysis conducted is a differential cash flow analysis and, as such, does not present profit levels. LCOH analysis results demonstrate the potential exists to produce hydrogen at a cost as low as $1.20/kg. This price is lower than traditional steam methane reforming (SMR) allowing nuclear based hydrogen production to disrupt the existing hydrogen production market.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A comparison of building system parameters between affordable and market-rate housing in New York City

Low-income households in the United States experience higher than average energy burdens (defined as the proportion of household income spent on energy utilities), and many of these households struggle to simultaneously pay for rent, energy, and basic household necessities. The analysis presented here in this study examines whether the underlying characteristics of buildings and their energy systems could contribute to this disparity for affordable housing residents in New York City. It combines an energy audit dataset of 7,328 multifamily buildings with a database of properties receiving local, state, or federal housing subsidies. The results of this analysis indicate that the building-level installed equipment in large (greater than 50,000 square feet) affordable housing buildings in New York City is more efficient than that in market-rate buildings, but this trend largely disappears when considering overall building characteristics, such as location, size, or age. Significant differences in the types of systems installed in affordable and market-rate housing are also observed, as well as the types of energy efficiency recommendations made by energy auditors. However, these latter data were not normalized by building system characteristics, as that analysis is much more difficult to interpret for categorical data such as heating system type. These findings indicate that retrofit policies and building performance standards focused on affordable housing will likely need to account for underlying differences in building characteristics between affordable and market-rate housing to achieve intended impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Decarbonization of heat pump dual fuel systems using a practical model predictive control: Field demonstration in a small commercial building

In the transition from fossil fuel to electrified heating, a concerning trend is emerging in certain regions of the US. Owners of buildings with gas-based systems leave them in place after adding heat pumps (HPs). Existing control solutions for these hybrid (dual fuel) systems are rudimentary and fall short of realizing the full carbon reduction potential of these systems. Model predictive control (MPC) is often regarded as the benchmark for achieving optimal control in integrated systems. However, in the case of small-medium commercial buildings (SMCBs), the control and communication infrastructure required to facilitate the implementation of such advanced controls is often lacking. This paper presents a field implementation of easy-to-deploy MPC for a dual fuel heating system consisting of HPs and a gas-fired furnace (GF) for SMCBs. The control system is deployed on an open-source middleware platform and utilizes low-cost sensor devices to be used for real SMCBs without major retrofits. Here, we demonstrated this MPC in a real office building with 5 HPs and 1 GF for 2 months. The test results showed that MPC reduced 27% of cost while completely eliminating GF usage by shifting 23% of the thermal load from occupied-peak time to non-occupied-non-peak times.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗
DOE OSTI2025

Advances in supervisory control strategies for a heat pump centric HVAC system − a comprehensive review on applications

There is an increase in research investigating the development and deployment of supervisory controllers that enable high efficiency electrically driven vapor compression heat pumps operating within grid interactive efficient buildings to provide demand side management. This paper reviews over sixty relevant case studies within this domain that focus on commercial off-the-shelf heat pumps whose primary task is providing space conditioning. The concept of a heat pump-centric heating, ventilation, and air-conditioning system is introduced, accompanied by a detailed overview of various kinds of electric heat pumps and building-level thermal energy storage configurations. Additionally, the different types of supervisory controller designs, including rule-based control and model predictive control, are discussed, along with the various methods for communication between a supervisory controller and a downstream heat pump’s local controller. A comparative analysis is conducted in order to categorize the reviewed case studies based on their system design, supervisory control algorithm, and validation methodology. This detailed analysis allows the review to establish current research trends, identify potential gaps, and suggest future directions for the development of this technology. Overall, the authors recommend that more future research be devoted to low-cost practical retrofits that allow for easy integration of active thermal energy storage within heat pump-centric heating, ventilation, and air-conditioning system systems that utilize direct expansion heat pumps. We also suggest more research into the development and deployment of supervisory controllers that can properly communicate with commercial off-the-shelf heat pump local controller available control inputs, e.g., zone temperature setpoint. Lastly, more rigorous experimental demonstrations of advanced supervisory control within real and or closed-loop, transient/ quasi-steady state environments are necessary to reduce industry wide skepticism of this technology.

Demand side management↗
DOE OSTI2019

Integrating physics-based models with sensor data: An inverse modeling approach

Physics-based building energy models (e.g., EnergyPlus) rely on some unknown input parameters (e.g., zone air infiltration) that are hard to measure, leading to uncertainty in simulation results especially for existing buildings with varying operating conditions. With the increasing deployment of smart thermostats, zone air temperature data are readily available, posing a new opportunity for building energy modeling if such data can be harnessed. This study presents a novel inverse modeling approach which inverses the zone air heat balance equation and uses the measured zone air temperature to analytically calculate the zone air infiltration rate and zone internal thermal mass (e.g., furniture, interior partitions), which are two important model parameters with great variability and difficult to measure. This paper introduces the technical concept and algorithms of the inverse models, their implementation in EnergyPlus, and verification using EnergyPlus simulated building performance data. The inverse modeling approach provides new opportunities for integrating data from massive IoT sensors and devices to enhance the accuracy of simulation results which are used to inform decision making on energy retrofits and efficiency improvements of existing buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Nexus of thermal resilience and energy efficiency in buildings: A case study of a nursing home

Extreme weather events become more frequent and severe due to climate change. Although energy efficiency technologies can influence thermal resilience of buildings, they are traditionally studied separately, and their interconnections are rarely quantified. This study developed a methodology of modeling and analysis to provide insights into the nexus of thermal resilience and energy efficiency of buildings. In this work, we conducted a case study of a real nursing home in Florida, where 12 patients died during Hurricane Irma in 2017 due to HVAC system power loss, to understand and quantify how passive and active energy efficiency measures (EEMs) can improve thermal resilience to reduce heat-exposure risk of patients. Results show that passive measures of opening windows and doors for natural ventilation, as well as miscellaneous load reduction, are very effective in eliminating the extreme dangerous occasions. However, to maintain safe conditions, active measures such as on-site power generators and thermal storage are also needed. The nursing home was further studied by changing its location to two other cities: San Francisco (mild climate) and Chicago (cold winter and hot summer). Results revealed that the EEMs' impacts on thermal resilience vary significantly by climate and building characteristics. The study also estimated the costs of EEMs to help stakeholders prioritize the measures. Passive measures that may not save energy may greatly improve thermal resilience, and thus should be considered in building design or retrofit. Findings from this study indicate energy efficiency technologies should be evaluated not only by their energy savings performance but also by their influence on a building's resilience to extreme weather events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Ten questions on future and extreme weather data for building simulation and analysis in a changing climate

Weather plays a significant role in building operations as it directly influences HVAC loads and in turn the building energy and thermal performance. In a changing climate, future trends and extreme weather events become critical concerns in the global building decarbonization and clean energy transition. This paper aims to address ten key questions concerning extreme and future weather data for building applications, and more importantly to identify research gaps and guide the curation and selection of future and extreme weather data for use in building performance simulation and assessment. The paper intends to inform architects and engineers, operators, owners, policy makers, and other stakeholders on considering the impacts of future and extreme weather data and adopting strategies for selecting and applying this data in various use cases related to building design, operation, and retrofit for energy efficiency, electrification, and climate resilience.

Yan, Da↗
DOE OSTI2025

Integration of renewable energy generation and storage systems for emissions reduction in an islanded campus microgrid

Microgrid connected building communities are projected to play an integral part in the clean energy transition. These types of systems, when integrated with distributed energy resources (DERs) such as combined heat and power (CHP), district heating and cooling, renewable generation, and energy storage, can provide clean, reliable power to critical facilities and vulnerable communities. The intermittent nature of renewable generation is a challenge when integrating renewables into any grid system, but particularly in islanded microgrids. The University of Texas at Austin (UT) operates an islanded microgrid powered by a CHP plant, while also utilizing district heating and cooling systems and thermal energy storage (TES). High fidelity operating data was used to develop a validated reduced order model of UT’s integrated campus energy systems to serve as a testbed for use in a case study. Hypothetical renewable energy installations on land owned by UT in west Texas were modeled and integrated into the validated campus models along with battery energy storage (BES). Simulations showed that a combination of renewable energy from wind, and optimally controlled 24-hour thermal and battery storage systems could reduce carbon dioxide emissions on campus by 45.4%. The additional retrofit of burner systems to utilize hydrogen natural gas blends resulted in an overall annual emissions reduction of 54.7%. Carbon capture and storage eliminated the majority of the remaining emissions with increased plant energy expenditure. The presented simulations display the practical limitations of a CHP system complemented by renewable generation and short-term storage in eliminating emissions. Furthermore, results highlight the need for further research and development in long duration storage technologies and hydrogen fueled turbines to increase penetration of renewable energy and reduce emissions.

CHP↗
DOE OSTI2022

Nondestructive neutron imaging diagnosis of acidic gas reduction catalyst after 400-Hour operation in natural gas furnace

Residential natural gas furnaces are the primary space-heating devices in US homes, leading to substantial environmental impact caused by the acidic components in the furnace combustion gases. Here, to experimentally demonstrate acidic gas reduction in a furnace, a monolithic catalyst was fabricated and was called the AGR. A commercially-available condensing furnace was retrofitted with the AGR, and a 400-hour reliability and durability test was conducted. The results showed that the AGR significantly reduced acidic gases in the flue gas and produced condensate with neutral pH. Challenges were also revealed: inappropriate condensate drainage caused incomplete combustion and amorphous carbon deposits. To nondestructively survey the internal state of the AGR, neutron computed tomography (NCT) was employed to produce spatially resolved 2D and 3D representations of the 2-L, aged AGR component. The NCT results confirm the integrity of the AGR component, which consists of two blocks, without deformation or damage to AGR channels. The distribution of the particle accumulation in the middle of the top block was visibly heavier than the entrance and exit of the top block. The representative cross-section views revealed significant aggregation in the central region but not at the rim. The spatially resolved details provide in-depth diagnosis, evaluation, and understanding of the AGR. The insights can enable new AGR designs that realize a uniform and self-cleaning flow pattern, alleviate significant particle aggregation, and thus enhance AGR-enabled furnace performance. The neutron imaging method demonstrates the good potential that can diagnose faults and improve the design, optimization, and production processes of novel catalysts and other components or systems with heavy metal shell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Unlocking naphtha from polyolefins using Ni-based hydrocracking catalysts

Naphtha (C 5 -C 12 alkanes) is a platform feedstock in the petroleum industry and an ideal target for reutilizing plastic waste at scale. Hydrocracking has emerged as a promising technology for deconstructing polyolefins to naphtha. However, contemporary catalysts rely on Pt to achieve high rates, while earth-abundant metals (EAM) perform poorly. Herein, we develop high-performance Ni/BEA catalysts for polyolefin hydrocracking, achieving complete low-density polyethylene (LDPE) deconstruction with 80 % maximum naphtha yield within 12 h at 250 °C, 60 bar H 2 , and a catalyst-to-polymer ratio of 1:100. These catalysts are versatile, accommodating virgin resins and commercial polymer products, and are directly reusable and regenerable. Comparative analysis highlights that 5Ni/BEA(25) exhibits the highest naphtha productivity of 11.4 $\huge{(}$$\frac{g_{Naphtha}}{g_{cat}{•h}}$$\huge{)}$, surpassing previously reported Pt- and EAM-based catalysts by 2.5–6.2x. Technoeconomic and life-cycle analyses reveal naphtha from LDPE hydrocracking is economically and environmentally competitive to fossil-fuel-derived naphtha. In conclusion, these advancements pave the way for the industrial implementation of earth-abundant Ni-based catalysts in polyolefin hydrocracking, followed by retrofitting steam crackers to address plastics waste at scale.

Circular Economy↗
DOE OSTI2019

Global optimization of multicomponent distillation configurations: Global minimization of total cost for multicomponent mixture separations

We introduce a global optimization framework for determining the minimum cost required to distill any ideal or near-ideal multicomponent mixture into its individual constituents using a sequence of columns. This new framework extends the Global Minimization Algorithm (GMA) previously introduced by Nallasivam et al. (2016); and we refer to the new framework as the Global Minimization Algorithm for Cost (GMAC). GMAC guarantees global optimality by formulating a nonlinear program (NLP) for each and every distillation configuration in the search space and solving it using global optimization solvers. In conclusion, the case study presented in this work not only demonstrates the need for developing such an algorithm, but also shows the flexibility and effectiveness of GMAC, which enables process engineers to design and retrofit energy efficient and cost-effective distillation configurations.

42 ENGINEERING↗
DOE OSTI2020

A scoping review of non-destructive testing (NDT) techniques in building performance diagnostic inspections

Understanding building envelope thermodynamics is an essential foundation of building sciences, mainly due to the envelope’s role as a boundary layer for exterior environments, as well as a container and regulator of internal microclimates. This paper presents a scoping literature review of select Non-destructive Testing (NDT) techniques for building envelope scanning and surveying for thermodynamic diagnostics. The investigation focuses specifically on reviewing six NDT techniques: Ground Penetrating Radar (GPR), Light Detection and Ranging (LiDAR)/Laser Scanning, Thermography, Ultrasound, Close-Range Photogrammetry and Through Wall Imaging Radar (TWIR). The aim is to identify knowledge gaps in terms of their use in accurately characterizing envelope compositions for further integration in Building Energy Modeling (BEM). Each technique was evaluated according to set categories imbibed from the American Society of Heating, Refrigerating, and Air Conditioning Engineering (ASHRAE) Standard 211P that showcase the technique’s ability to extract various relevant information. A framework is then developed to inform users on how to use hybrid NDT-based workflows applied in building envelope energy audits. The study concludes by discussing possibilities of utilizing NDT in large-scale audit automation, BEM integration, and developing built environment policies focusing on increasing existing building performance through retrofitting design.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Cost-effectiveness Analysis on Measures to Improve China's Coal-fired Industrial Boiler

Tackling coal-burning industrial boiler is becoming one of the key programs to solve the environmental problem in China. Assessing the economics of various options to address coal-fired boiler is essential to identify cost-effective solutions. This paper discusses our work in conducting a cost-effectiveness analysis on various types of improvement measures ranging from energy efficiency retrofits to switch from coal to other fuels in China. Sensitivity analysis was also performed in order to understand the impacts of some economic factors such as discount rate and energy price on the economics of boiler improvement options. The results show that nine out of 14 solutions are cost-effective, and a lower discount rate and higher energy price will result in more energy efficiency measures being cost-effective. Both monetary and non-monetary barriers to energy-efficiency improvement are discussed and policies to tackle these barriers are recommended. Our research aims at providing a methodology to assess cost-effective solutions to boiler problems.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Enabling CCS via Low-temperature Geothermal Energy Integration for Fossil-fired Power Generation

Here, among the key barriers to commercial scale deployment is the cost associated with CO 2 capture. This is particularly true for existing large, fossil-fired assets that account for a large fraction of the electricity generation fleet in developed nations, including the U.S. Fitting conventional combustion technologies with CO 2 capture systems can carry an energy penalty of thirty percent or more, resulting in an increased price of power to the grid, as well as an overall decrease in net plant output. Taken together with the positive growth in demand for electricity, this implies a need for accelerated capital build-out in the power generation markets to accommodate both demand growth and decreased output at retrofitted plants. In this paper, the authors present the results of a study to assess the potential to use geothermal energy to provide boiler feedwater preheating, capturing efficiency improvements designed to offset the losses associated with CO 2 capture. Based on NETL benchmark cases and subsequent analysis of the application using site-specific data from the North Valmy power plant, several cases for CO 2 capture were evaluated. These included geothermally assisted MEA capture, CO2BOLs capture, and stand-alone hybrid power generation, compared with a baseline, no-geothermal case. Based on Case 10, and assuming 2.7 MMlb/h of geothermally sourced 150 ºC water, the parasitic power load associated with MEA capture could be offset by roughly seven percent, resulting in a small (~1 percent) overall loss to net power generation, but at levelized costs of electricity similar to the no-geothermal CCS case. For the CO 2 BOLs case, the availability of 150°C geothermal fluid could allow the facility to not only offset the net power decrease associated with CO 2 BOLs capture alone, but could increase nameplate capacity by two percent. The geothermally coupled CO 2 BOLs case also decreases LCOE by 0.75 ¢/kWh relative to the non-hybrid CO 2 BOLs case, with the improved performance over the MEA case driven by the lower regeneration temperature and associated duty for CO 2 BOLs relative to MEA.

24 POWER TRANSMISSION AND DISTRIBUTION↗