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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Reducing Wind Curtailment through Transmission Expansion in a Wind Vision Future

The Department of Energy's 2015 Wind Vision study, which analyzed an ambitious scenario where wind power served 35% of U.S. electricity consumption in 2050, showed the potential for wind energy to provide substantial health, environmental, and economic benefits. Using a commercial unit commitment and economic dispatch model, we build on this research by assessing the hourly operational feasibility of a similar high wind future in the Western United States. Our detailed simulations found no hours of unmet load or reserve violations with more than 35% potential wind (and 12% potential solar) available on the system, which highlights the technical possibility of integrating large amounts of wind energy. However, absent significant changes to the western grid, we find that substantial wind curtailment could be an issue, as it could degrade the potential for wind power to reduce fuel costs and lowering the emission benefits. To assess the value of transmission to mitigate wind curtailment, we model a suite of transmission expansion scenarios. We find that wind curtailment could be reduced by approximately half under a scenario where new transmission is based only on proposed projects. This avoided wind curtailment could lower annual production costs and reduce carbon dioxide emissions substantially. Greater transmission expansion was found to yield further benefits, although the marginal benefits of these new lines were found to decline. Overall, these results suggest that power systems operation can be realized with more than 35% wind penetration, but that transmission expansion is likely to play a vital role.

17 WIND ENERGY↗
DOE OSTI2022

Defining the Prototype Convenience Store Building Characteristics

The US Department of Energy supports the development of commercial building energy codes and standards. To support commercial building energy research activities and the development of commercial building energy codes and standards, continuous efforts have been made to convert 30 prototype building models (20 different building types), which cover 80% of US commercial building floor space, to OpenStudio prototype buildings. Additionally, the suite of prototype building models was expanded to include the addition of new building prototype models (e.g., courthouse, college building). This report documents the building and system characteristics of the prototype convenience store building model. Multiple sources, including databases, documented projects, and personal communications, were used to define the prototype convenience store building characteristics, and a one-story, 3,000 ft 2 building was considered as the prototype convenience store to represent an average-sized convenience store in the United States. The Oak Ridge National Laboratory team defined the operational hours of the convenience store as 17 hours per day. The types of exterior walls, roof, and floor were defined as brick wall, metal surfacing roof, and slab-on-grade floor, respectively. Double glazing was selected, and the window-towall ratio was set as 15% on the front side. For the system part, packaged system and centralized water heater were selected for the space heating and cooling system and water heater system, respectively. In terms of the refrigerator system, the number of refrigerators and freezers were determined as eight closed cases and two walk-in units.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

PSCAD Modules Representing PV Generator

Photovoltaic power plants (PVPs) have been growing in size, and the installation time is very short. With the cost of photovoltaic (PV) panels dropping in recent years, it can be predicted that in the next 10 years the contribution of PVPs to the total number of renewable energy power plants will grow significantly. In this project, the National Renewable Energy Laboratory (NREL) developed a dynamic modeling of the modules to be used as building blocks to develop simulation models of single PV arrays, expanded to include Maximum Power Point Tracker (MPPT), expanded to include PV inverter, or expanded to cover an entire PVP. The focus of the investigation and complexity of the simulation determines the components that must be included in the simulation. The development of the PV inverter was covered in detail, including the control diagrams. Both the current-regulated voltage source inverter and the current-regulated current source inverter were developed in PSCAD. Various operations of the PV inverters were simulated under normal and abnormal conditions. Symmetrical and unsymmetrical faults were simulated, presented, and discussed. Both the three-phase analysis and the symmetrical component analysis were included to clarify the understanding of unsymmetrical faults. The dynamic model validation was based on the testing data provided by SCE. Testing was conducted at SCE with the focus on the grid interface behavior of the PV inverter under different faults and disturbances. The dynamic model validation covers both the symmetrical and unsymmetrical faults.

14 SOLAR ENERGY↗
DOE OSTI2014

Adaptive multiconfigurational wave functions

A method is suggested to build simple multiconfigurational wave functions specified uniquely by an energy cutoff Λ. These are constructed from a model space containing determinants with energy relative to that of the most stable determinant no greater than Λ. The resulting Λ-CI wave function is adaptive, being able to represent both single-reference and multireference electronic states. We also consider a more compact wave function parameterization (Λ+SD-CI), which is based on a small Λ-CI reference and adds a selection of all the singly and doubly excited determinants generated from it. We report two heuristic algorithms to build Λ-CI wave functions. The first is based on an approximate prescreening of the full configuration interaction space, while the second performs a breadth-first search coupled with pruning. The Λ-CI and Λ+SD-CI approaches are used to compute the dissociation curve of N{sub 2} and the potential energy curves for the first three singlet states of C{sub 2}. Special attention is paid to the issue of energy discontinuities caused by changes in the size of the Λ-CI wave function along the potential energy curve. This problem is shown to be solvable by smoothing the matrix elements of the Hamiltonian. Our last example, involving the Cu{sub 2}O{sub 2}{sup 2+} core, illustrates an alternative use of the Λ-CI method: as a tool to both estimate the multireference character of a wave function and to create a compact model space to be used in subsequent high-level multireference coupled cluster computations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Predictive Engineering Tools for Novel Fuels

This project was funded through the Campus Executive Fellowship at University of California (UC) Berkeley, and had two principal aims. First, it sought to explore predictive tools for estimating fuel properties based on molecular structure, with the goal of identifying promising candidates for new fuels to be synthesized. Second, it sought to investigate the possibility of increasing engine efficiency by substituting air for a working fluid with higher efficiency potential employed in a closed loop, namely a mixture of argon and oxygen. In pursuing the predictive tool for novel fuels, a new model was built that proved to be highly predictive of autoignition characteristics for a wide variety of hydrocarbons, esters, ethers and alcohols, and reasonably predictive for furan and tetrahydrofuran compounds, the target class of novel fuels. Obtaining more “training data” for the model improved its predictive capabilities, and further reductions in the uncertainty of the predictions would be possible with more training data. In investigating the concept of a closed-loop engine cycle using an argon-oxygen working fluid, substantial progress was made. Initial engineering models were built showing the feasibility of the concept; numerous collaborations were formed with industry and academic partners; external funding was secured from the California Energy Commission (CEC) to build a dedicated engine platform for research; and this engine platform was designed and constructed. Experimental work and associated modeling studies will take place in late 2016 and early 2017.

10 SYNTHETIC FUELS↗
DOE OSTI2012

Energy and Cost Savings of Retro-Commissioning and Retrofit Measures for Large Office Buildings

This paper evaluates the energy and cost savings of seven retro-commissioning measures and 29 retrofit measures applicable to most large office buildings. The baseline model is for a hypothetical building with characteristics of large office buildings constructed before 1980. Each retro-commissioning measure is evaluated against the original baseline in terms of its potential of energy and cost savings while each retrofit measure is evaluated against the commissioned building. All measures are evaluated in five locations (Miami, Las Vegas, Seattle, Chicago and Duluth) to understand the impact of weather conditions on energy and cost savings. The results show that implementation of the seven operation and maintenance measures as part of a retro-commissioning process can yield an average of about 22% of energy use reduction and 14% of energy cost reduction. Widening zone temperature deadband, lowering VAV terminal minimum air flow set points and lighting upgrades are effective retrofit measures to be considered.

Wang, Weimin↗
DOE OSTI2017

A New Distributed Optimization for Community Microgrids Scheduling

This paper proposes a distributed optimization model for community microgrids considering the building thermal dynamics and customer comfort preference. The microgrid central controller (MCC) minimizes the total cost of operating the community microgrid, including fuel cost, purchasing cost, battery degradation cost and voluntary load shedding cost based on the customers' consumption, while the building energy management systems (BEMS) minimize their electricity bills as well as the cost associated with customer discomfort due to room temperature deviation from the set point. The BEMSs and the MCC exchange information on energy consumption and prices. When the optimization converges, the distributed generation scheduling, energy storage charging/discharging and customers' consumption as well as the energy prices are determined. In particular, we integrate the detailed thermal dynamic characteristics of buildings into the proposed model. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of proposed model.

alternating direction method of multipliers (ADMM)↗
DOE OSTI2018

An Interactive Visualization Tool for Large-Scale Building Stock Modeling

Recent advancements in data science and high-performance computing are making it easier to run millions of building simulations, but meaningful visualization of such large datasets remains a challenge. This paper presents a new tool developed to view the results of large-scale OpenStudio simulations of national, regional, or local building stocks. The tool processes millions of simulations to calculate measure savings, utility bills, carbon emissions, primary energy, and cost-effectiveness metrics at a high geographic resolution. Interactive visualizations of the building characteristics, consumption, and measure savings data include proportional symbol maps and histogram plots and can be filtered by any building characteristic.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Selection of Global Climate Model Data for Downscaling With Generative Machine Learning and Use in the Power Planning for Alignment of Climate and Energy Systems Project

The range of results from climate models and scenarios is important to the understanding of uncertainty in power planning analysis. A U.S. Department of Energy-funded analytic project called Power Planning for Alignment of Climate and Energy Systems is developing data and analytic methods to reflect the effects of climate change on key variables for power system planning, as part of the Grid Modernization Lab Consortium. This project will select and prepare global climate model results for use in power system planning models. A related report (Evaluation of Global Climate Models for Use in Energy Analysis) assesses the performance of various global climate models from the Coupled Model Intercomparison Project Phase 6 data archive for their historical skill with respect to energy system performance and for their future projections under multiple climate change scenarios. Building from that report, we describe the selection of a climate scenario (Shared Socioeconomic Pathway [SSP] 2-4.5) and five climate models: TaiESM1, EC-Earth3-CC, GFDL-CM4, EC-Earth3-Veg, and MPI-ESM1-2-HR. We describe the model selection criteria, which were based on the quality of the match between model results under historical conditions and on the representation of the range of future values for several variables. These results will be downscaled via an open-source generative machine learning method called Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Leveraging generative AI for urban digital twins: a scoping review on the autonomous generation of urban data, scenarios, designs, and 3D city models for smart city advancement

The digital transformation of modern cities by integrating advanced information, communication, and computing technologies has marked the epoch of data-driven smart city applications for efficient and sustainable urban management. Despite their effectiveness, these applications often rely on massive amounts of high-dimensional and multi-domain data for monitoring and characterizing different urban sub-systems, presenting challenges in application areas that are limited by data quality and availability, as well as costly efforts for generating urban scenarios and design alternatives. As an emerging research area in deep learning, Generative Artificial Intelligence (GenAI) models have demonstrated their unique values in content generation. This paper aims to explore the innovative integration of GenAI techniques and urban digital twins to address challenges in the planning and management of built environments with focuses on various urban sub-systems, such as transportation, energy, water, and building and infrastructure. The survey starts with the introduction of cutting-edge generative AI models, such as the Generative Adversarial Networks (GAN), Variational Autoencoders (VAEs), Generative Pre-trained Transformer (GPT), followed by a scoping review of the existing urban science applications that leverage the intelligent and autonomous capability of these techniques to facilitate the research, operations, and management of critical urban subsystems, as well as the holistic planning and design of the built environment. Based on the review, we discuss potential opportunities and technical strategies that integrate GenAI models into the next-generation urban digital twins for more intelligent, scalable, and automated smart city development and management.

3D city modeling↗
DOE OSTI2013

Theoretical Research in Weak-Electromagnetic and Strong Interactions (Final Report)

Project: Theoretical and Experimental Research in Weak, Electromagnetic and Strong Interactions: Investigators: S. Nandi, K.S. Babu, F. Rizatdinova Institution: Oklahoma State University, Stillwater, OK 74078. This completed project focused on the cutting edge research in theoretical and experimental high energy physics. In theoretical high energy physics, the two investigators (Nandi and Babu) worked on a variety of topics in model-building and phenomenological aspects of elementary particle physics. This includes unification of particles and forces, neutrino physics, Higgs boson physics, proton decay, supersymmetry, and collider physics. Novel physics ideas beyond the Standard Model with testable consequences at the LHC have been proposed. These ideas have stimulated the experimental community to look for new signals. The contributions of the experimental high energy physics group has been at the D0 experiment at the Fermilab Tevatraon and the ATLAS experiment at the Large Hadron Collider. At the D0 experiment, the main focus was search for the Higgs boson in the WH channel, where improved limits were obtained. At the LHC, the OSU group has made significant contributions to the top quark physics, and the calibration of the b-tagging algorithms. The group is also involved in the pixel detector upgrade. This DOE supported grant has resulted in 5 PhD degrees during the past three years. Three postdoctoral fellows were supported as well. In theoretical research over 40 refereed publications have resulted in the past three years, with several involving graduate students and postdoctoral fellows. It also resulted in over 30 conference presentations in the same time period. We are also involved in outreach activities through the Quarknet program, where we engage Oklahoma school teachers and students in our research.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Building America Top Innovations 2012: Building Science-Based Climate Maps

This Building America Top Innovations profile describes the Building America-developed climate zone map, which serves as a consistent framework for energy-efficiency requirements in the national model energy code starting with the 2004 IECC Supplement and the ASHRAE 90.1 2004 edition. The map also provides a critical foundation for climate-specific guidance in the widely disseminated EEBA Builder Guides and Building America Best Practice Guides.

Building America↗
DOE OSTI2025

Utilizing AI and Spatial Data to Identify & Rapidly Disseminate Energy Infrastructure Insights

GeoGov Summit Final Presentation entitled "Utilizing AI and Spatial Data to Identify & Rapidly Disseminate Energy Infrastructure Insights". Maintaining the integrity of energy infrastructure plays a critical role in ensuring energy security. Robust foundational AI models using data from federal, state, industry, and other sources can help address integrity risk management & mitigation issues as well as evaluate extended use strategies. Trusted foundational models can help with industry adoption and accelerate innovation by enhancing integrity predictions, reduce costs, and informing infrastructure build-out. Coordination, collaboration & data sharing to develop robust models to aid in: Optimizing operations; Minimizing costs; Ensuring energy security.

Advanced Infrastructure Integrity Model (AIIM)↗
DOE OSTI2012

A comparison of thermal zone aggregation methods

The impact of increasing energy prices on building operation budgets has fueled demand for more energy-efficient structures. Existing building energy simulation tools generate an immense amount of data yet comparatively little knowledge. This paper introduces a framework that allows aggregation-based model reduction to operate on geometric building information models. The resulting aggregation sequence provides designers with faster simulations and affords insight into complex multi-scale thermal interactions. A comparison of the trade-off between simulation speed and accuracy for three hierarchical cluster partitioning methods concludes the discussion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Estimating Building Simulation Parameters via Bayesian Structure Learning

Many key building design policies are made using sophisticated computer simulations such as EnergyPlus (E+), the DOE flagship whole-building energy simulation engine. E+ and other sophisticated computer simulations have several major problems. The two main issues are 1) gaps between the simulation model and the actual structure, and 2) limitations of the modeling engine's capabilities. Currently, these problems are addressed by having an engineer manually calibrate simulation parameters to real world data or using algorithmic optimization methods to adjust the building parameters. However, some simulations engines, like E+, are computationally expensive, which makes repeatedly evaluating the simulation engine costly. This work explores addressing this issue by automatically discovering the simulation's internal input and output dependencies from 20 Gigabytes of E+ simulation data, future extensions will use 200 Terabytes of E+ simulation data. The model is validated by inferring building parameters for E+ simulations with ground truth building parameters. Our results indicate that the model accurately represents parameter means with some deviation from the means, but does not support inferring parameter values that exist on the distribution's tail.

Energy Modeling↗
DOE OSTI2020

Dynamic metrics of natural ventilation cooling effectiveness for interactive modeling

The evaluation of natural ventilation potential for cooling indoor spaces during the early design phases is of great interest to researchers and practitioners. Among various definitions and usages for natural ventilation potential (NVP) in early design evaluation, this paper reviews and identifies the key performance indicators, and proposes two new dynamic metrics—natural ventilation cooling effectiveness (NVCE) and climate potential utilization ratio (CPUR). The metrics are dynamically responsive to various design options, in both steady and transient states, allowing consideration of thermal mass. Assisting in design development processes, the metrics quantify how well indoor spaces make use of natural ventilation’s cooling capacity. Case studies are presented to demonstrate how NVCE and CPUR enable designers to evaluate the predicted performance and how to apply the information to improve building design. Finally, the results of the design iterations showed that the relationship among various design parameters should be dynamically understood in order to evaluate the performance of natural ventilation, confirming that “the more the airflow, the greater the potential,” and “the heavier the thermal mass, the greater the energy saving” were not always true.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Optimal Dispatch Controller for Fuel Cell-Integrated Building: Preprint

Stationary fuel cells can generate both electrical power and heat, making it them a promising local source to serve building loads. In this paper, we develop an optimal energy dispatch controller to operate a fuel cell-integrated building. The controller leverages the inherent thermal in the building to lower reduce its operating cost and allows the building to participate in providing grid services. The proposed controller is tested in a co-simulation setup, where the real building is represented as a high-fidelity model in EnergyPlus.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗