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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

A modeling framework for optimal energy management of a residential building

Residential buildings are currently equipped with energy production facilities, e.g., solar rooftops and batteries, which in conjunction with smart meters, can function as smart energy hubs coordinating the loads and the resources in an optimal manner. This paper presents a mathematical model for the optimal energy management of a residential building and proposes a centralized energy management system (CEMS) framework for off-grid operation. The model of each component of the hub is integrated within the CEMS. The optimal decisions are determined in real-time by considering these models with realistic parameter settings and customer preferences. Model predictive control (MPC) is used to adapt the optimal decisions on a receding horizon to account for the deviations in the system inputs. Simulation results are presented to demonstrate the feasibility and effectiveness of the proposed CEMS framework. Results show that the proposed CEMS can reduce the energy cost and energy consumption of the customers by approximately 17% and 8%, respectively, over a day. In conclusion, using the proposed CEMS, the total charging cycles of the ESS were reduced by more than 50% in a day.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Infrared spectra of jennite and tobermorite from first-principles

The infrared absorption spectra of jennite, tobermorite 14 Å, anomalous tobermorite 11 Å, and normal tobermorite 11 Å are simulated within a density-functional-theory scheme. The atomic coordinates and the cell parameters are optimized resulting in structures which agree with previous studies. The vibrational frequencies and modes are obtained for each mineral. The vibrational density of states is analyzed through extensive projections on silicon tetrahedra, oxygen atoms, OH groups, and water molecules. The coupling with the electric field is achieved through the use of density functional perturbation theory, which yields Born effective charges and dielectric constants. The simulated absorption spectra reproduce well the experimental spectra, thereby allowing for a detailed interpretation of the spectral features in terms of the underlying vibrational modes. In the far-infrared part of the absorption spectra, the interplay between Ca and Si related vibrations leads to differences which are sensitive to the calcium/silicon ratio of the mineral.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Crystal structure and luminescence properties of a novel red-emitting phosphor BaAlBO{sub 3}F{sub 2}:Eu{sup 3+}

A series of novel red-emitting phosphors BaAlBO{sub 3}F{sub 2}:xEu{sup 3+} (0.001≤x≤0.08) were first synthesized via a high temperature solid-state reaction. X-ray diffraction and photoluminescence spectroscopy were used to characterize the crystal structure and photoluminescence properties of the phosphor, respectively. The phosphor can be effectively excited with a 395 nm light, and shows a dominant {sup 5}D{sub 0}−{sup 7}F{sub 2} emission with chromatic coordination of 0.628 and 0.372. The optimal doping concentration is about 0.04. Rietveld refinement results and the luminescence behavior of Eu{sup 3+} indicate that the Eu{sup 3+} ion occupies a C{sub 3} symmetry site, and the host BaAlBO{sub 3}F{sub 2} has a hexagonal structure with P-6 space group. In addition, the phosphor could be a potential candidate as red-emitting phosphor for application in white light-emitting diode. - Graphical abstract: The luminescence behavior and Rietveld refinement of BaAlBO{sub 3}F{sub 2}:Eu{sup 3+} indicate that the red-emitting phosphor has potential application in white LED and the host has a hexagonal structure with P-6 space group. - Highlights: • A novel red-emitting phosphor BaAlBO{sub 3}F{sub 2}:Eu{sup 3+} is first synthesized. • The crystal structure of BaAlBO{sub 3}F{sub 2} is confirmed. • The phosphor shows potential application in white LED.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Optimization Methods for Evaluating PEV Charging Considering Customer Behavior

Plug-in electric vehicles (PEVs) can be connected to grid through electrical vehicle supply equipment (EVSE) to provide various grid services in addition to battery charging. This paper evaluates loading condition of a distribution system with a medium penetration of PEVs considering different charging strategies and public EVSE availability. A mobility and charging flexibility model is proposed to capture PEVs’ temporal availability and varying charging capability at different parking locations. Detailed trip information extracted from the National Household Travel Survey is used to represent travel and parking patterns. An optimization method is then proposed to coordinate PEV charging to effectively shift load from peak to off-peak hours. One of the prototypical feeders developed by the Pacific Northwest National Laboratory is studied in different scenarios.

Wu, Di↗
DOE OSTI2020

A Hierarchical Volt-var Optimization with Discrete Variables in Unbalanced Distribution Systems

This paper proposes a framework to determine the optimal active and reactive power dispatch of distributed photovoltaic (PV) generation, switched capacitors, and voltage regulators in multi-phase unbalanced distribution systems. The objectives of the optimal dispatch are minimization of the energy loss, PV real power curtailment, and switching operations of capacitors and voltage regulators, in addition to elimination of voltage violation and reverse power flow. The optimization problem is formulated in rectangular coordinates as a nonlinear, nonconvex problem with discrete variables. A hierarchical twostage framework is proposed to effectively handle those discrete variables and reduce the computational time compared to the unified approach in which all variables are solved simultaneously. The efficacy of the proposed approach and the accuracy of the obtained numerical solution is validated using the unbalanced multi-phase IEEE 34-bus with 15-minute load and PV data.

Nguyen, Quan H.↗
DOE OSTI2023

Distributed Load Shedding Application Architecture and Bi-Level Predictive Estimator Algorithm

Increasing penetrations of distributed renewables are decreasing the effectiveness of traditional decentralized under-frequency load shedding (UFLS) schemes. As more distribution circuits begin to back-feed the transmission system, operation of traditional UFLS may exacerbate frequency instability. This paper presents the conceptual framework for a data-rich environment to coordinate UFLS across multiple distribution providers based on the laminar coordination framework in order to ensure optimal adaptive setting of UFLS relays. Communication and control are enabled through a distributed implementation of the IEC 61968-1 Common Information Model message bus structure. In addition to the proposed architecture, a novel adaptive UFLS scheme informed by a bi-level state estimator to create optimal relay setpoints is introduced. Initial simulation results are presented for the IEEE 14-bus test system on scenarios leading to mis-operation of traditional UFLS.

Anderson, Alexander A.↗
DOE OSTI2026

Disruption of starch biosynthesis and triacylglycerol degradation impairs growth but improves photosynthesis in Arabidopsis

Enhancing lipid accumulation by redirecting carbon from starch to triacylglycerol (TAG) in vegetative tissues is a promising strategy for developing high-energy-density crops for bioenergy production. However, our understanding of how starch and TAG metabolism interact and how this interaction affects growth and photosynthesis is incomplete. Here, we investigated the metabolic and physiological consequences of disrupting starch biosynthesis and TAG turnover in Arabidopsis thaliana by generating single, double, and triple mutants involving ADG1 (starch biosynthesis), TGD1 (lipid trafficking), and SDP1\\\\\\\\r\\\\\\\\n(TAG lipase). Unexpectedly, elimination of starch biosynthesis lowered TAG levels in the high-TAG-accumulating tgd1 mutant, primarily through enhanced TAG breakdown. This decline was completely reversed by sucrose supplementation, suggesting that TAG degradation was induced by carbon limitation.\\\\\\\\r\\\\\\\\nGenetic suppression of TAG turnover via SDP1 disruption in the starchless tgd1 adg1-1 background led to a nine-fold rise in leaf TAG accumulation in the tgd1 sdp1 adg1-1 triple mutant, together with enhanced photosynthetic performance. However, this metabolic reprogramming incurred growth penalties.\\\\\\\\r\\\\\\\\nOur results highlight the role of dynamic TAG turnover in maintaining metabolic balance and photosynthesis in starch-deficient backgrounds. These findings underscore the need for refined metabolic engineering strategies that coordinate TAG biosynthesis and degradation to optimize lipid accumulation in bioenergy crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

ALS/Milo: BL402 RSXD data analysis

Suite of tools designed to simply data collection, extraction, reduction, and plotting for resonant soft x-ray scattering experiments performed at ALS beamline 4.0.2; speeds up the process of converting data into meaningful information for users to publish experimental results. * Python software routines for processing CCD images, including reciprocal space maps, diffraction peak alignment, resonant spectral profiles, line-cut comparisons, coordinate transforms, etc. * Scan file generator, optimized for typical uses cases, reduces burden on users by handling complex operations behind the scenes of a simplified user interface * Deployed at beamline endstation computers; packaged and deployable as standardized PyPI package * Under version control (git) and hosted on LBL-sponsored repository (bitbucket)

Shafer, Padraic↗
DOE OSTI2025

NEXT Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR Phase I & II)

The Ohio State University’s ARPA-E NEXTCAR project was a multi-phase, multi-year research, development, and demonstration program focused on improving the energy efficiency of connected and automated vehicles (CAVs). The team developed and validated advanced vehicle motion and powertrain control algorithms that coordinate propulsion and automation systems to optimize energy use. Key technologies included Dynamic Skip Fire engine control, predictive eco-driving functions such as Eco-Approach and Departure (Eco-AND) and Eco-Adaptive Cruise Control (Eco-ACC), and powertrain-agnostic optimization frameworks for hybrid, plug-in hybrid, and battery electric vehicles. The project successfully demonstrated up to 30% energy-efficiency improvement during real-world testing at the Transportation Research Center and the American Center for Mobility. The outcomes provide a foundation for scalable, cost-effective deployment of energy-optimized CAV technologies across the automotive industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Coordination of Energy Storage and Distributed Generation for Voltage Control and Peak-valley Filling

The increasing penetration of distributed energy resources (DERs) in distribution network (DN) poses challenges on voltage control. In addition, the growing integration of DERs also reshapes the traditional load profile. To comprehensively address the voltage control and peak-valley filling in DN, this paper proposes a model predictive control (MPC) based optimization framework. The proposed method can achieve coordinated voltage control and peak-valley filling by adjusting the reactive power output from distributed generations (DGs) and the charging/discharging of energy storage systems (ESS). The performance of the proposed method is demonstrated by simulations on a modified IEEE-123 bus system.

Zhang, Zhengfa [University of Tennessee, Knoxville↗
DOE OSTI2016

Design of specially adapted reactive coordinates to economically compute potential and kinetic energy operators including geometry relaxation

Quantum dynamics simulations require prior knowledge of the potential energy surface as well as the kinetic energy operator. Typically, they are evaluated in a low-dimensional subspace of the full configuration space of the molecule as its dimensionality increases proportional to the number of atoms. This entails the challenge to find the most suitable subspace. We present an approach to design specially adapted reactive coordinates spanning this subspace. In addition to the essential geometric changes, these coordinates take into account the relaxation of the non-reactive coordinates without the necessity of performing geometry optimizations at each grid point. The method is demonstrated for an ultrafast photoinduced bond cleavage in a commonly used organic precursor for the generation of electrophiles. The potential energy surfaces for the reaction as well as the Wilson G-matrix as part of the kinetic energy operator are shown for a complex chemical reaction, both including the relaxation of the non-reactive coordinates on equal footing. A microscopic interpretation of the shape of the G-matrix elements allows to analyze the impact of the non-reactive coordinates on the kinetic energy operator. Additionally, we compare quantum dynamics simulations with and without the relaxation of the non-reactive coordinates included in the kinetic energy operator to demonstrate its influence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

QM/MM Simulation (B3LYP) of the RNase A Cleavage-Transesterification Reaction Supports a Triester AN+DN Associative Mechanism with an O2´ H Internal Proton Transfer

The mechanism of the backbone cleavage transesterification step of the RNase A enzyme remains controversial even after 60 years of study. We report QM/MM free energy calculations for two optimized reaction paths based on an analysis of all structural data and identified by a search for reaction coordinates using a reliable quantum chemistry method (B3LYP), equilibrated structural optimizations, and free energy estimations. Both paths are initiated by nucleophilic attack of the ribose O2? oxygen on the neighboring diester phosphate bond and both reach the same product state (PS) (a O3??O2? cyclic phosphate and a O5? hydroxyl terminated fragment). Path 1, resembles the widely accepted dianionic transition state (TS) general acid (His 119)/base (His 12) classical mechanism. However, this path has a barrier (25 kcal/mol) higher than that of the rate limiting hydrolysis step and a very loose TS. In Path 2, the proton initially coordinating the O2? migrates to the non-bridging O1P in the initial reaction path rather than directly to the general base resulting in a triester (substrate as base) AN+DN mechanism with a monoanionic weakly stable intermediate. The structures in the transition region are associative with low barriers (TS1 10, TS2 7.5 kcal/mol). The Path 2 mechanism is consistent with the many results from enzyme and buffer catalyzed and uncatalyzed analog reactions and leads to a PS consistent with the reactive state for the following hydrolysis step. The differences between the consistently estimated barriers in Path 1 and 2 lead to a 1011 difference in rate strongly supporting the less accepted triester mechanism.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2021

Deep Learning Coordinate-Free Quantum Chemistry

Computing quantum chemical properties of small molecules and polymers can provide insights valuable to physicists, chemists and biologists when designing new materials, catalysts, biological probes and drugs. Deep learning can compute quantum chemical properties accurately in a fraction of the time required by commonly used methods such as density functional theory (DFT). However, many of these deep learning architectures require energy minimized molecular geometries as input, which is also computationally expensive, and decreasing the reproducibility and throughput of these methods. In this study, we demonstrate that accurate quantum chemical computations can be performed without optimized geometries by operating in the coordinate-free domain using deep learning on graph encodings. Furthermore, we also find that the choice of graph-encoding architecture substantially affects the performance of these methods. The Wave architecture outperforms graph convolution architectures, particularly on complex molecules. Furthermore, the structures of these graph encoding architectures provide an opportunity to probe an important, outstanding question in quantum mechanics: What types of quantum chemical properties can be represented by local-variable models? We find that Wave, a local-variable model, is more accurately calculates quantum chemical properties. Graph convolutional architectures require global variables, and are not as effective as as Wave. We anticipate that coordinate-free, deep-learning models of quantum chemistry will become valuable tools in chemistry and biology, enabling researchers to rapidly screen chemical databases or identify new molecules using automated, de-novo design algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Optimal Sizing of PV and Energy Storage in an Electric Vehicle Extreme Fast Charging Station

This paper proposes an optimization model for the optimal sizing of photovoltaic (PV) and energy storage in an electric vehicle extreme fast charging station considering the coordinated charging strategy of the electric vehicles. The proposed model minimizes the annualized cost of the extreme fast charging station, including investment and maintenance cost of PV and energy storage, cost of purchasing energy from utility and demand charge. The decision variables are capacity of invested PV and the power and energy ratings of invested energy storage. To further reduce the annualized cost of the extreme fast charging station, the charging strategy of electric vehicles are integrated into the optimization model and coordinated with the power output of PV and charging/discharging of energy storage. Results of numerical simulations indicate that investment of PV and energy storage could help reduce the annualized cost of the extreme fast charging station significantly. Meanwhile, the impacts of various parameters on the optimal solution are investigated by sensitivity analysis.

Liu, Guodong↗
DOE OSTI2019

Integrated distribution system and urban district planning with high renewable penetrations

Recent efforts to reduce energy consumption and greenhouse gas emissions have resulted in the development of sustainable, smart districts with highly energy efficient buildings, renewable distributed energy resources (DERs), and support for alternative modes of transportation. However, there is typically little if any coordination between the district developers and the local utility. Most attention is paid to the district's annual net load and generation without considering their instantaneous imbalance or the connecting network's state. This presents an opportunity to learn lessons from the design of distribution feeders for districts characterized by low loads and high penetrations of DERs that can be applied to the distribution grid at large. The aim of this overview is to summarize current practices in sustainable district planning as well as advances in modeling and design tools for incorporating the power distribution system into the district planning process. Recent developments in the modeling and optimization of district power systems, including their coordination with multi-energy systems and the impact of high penetration levels of renewable energy, are introduced. Sustainable districts in England and Japan are reviewed as case studies to illustrate the extent to which distribution system planning has been considered in practice. Finally, newly developed building-to-grid modeling tools that can facilitate coordinated district and power system design with utility involvement are introduced, along with suggestions for future research directions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Offline Arterial Signal Timing Optimization based on Virtual Phase Link Model - A Real-world Case Study

Conventional signal timing for arterial usually takes bottom-up approaches. Engineers optimize each individual intersection first and then coordinate them by adjusting the offsets. This work is based on the Virtual Phase-Link (VPL) model, a street traffic model designed for online traffic model predictive control, to obtain a top-down offline arterial signal timing. We Studied the Shallowford Rd. in Chattanooga, TN and found that the inconsistency in intersection capacities along the arterial could lead to some intersections becoming bottlenecks. Signal timing is a significant factor that affect the intersection capacities. We realized that the VPL-based model can guarantee the consistency in intersections along an arterial. We therefore adopted the VPL-based model and developed an offline signal timing optimization approach. The proposed timing derived from the VPL-based offline signal timing optimization showed very good results in simulation. The Chattanooga Department of Transportation adopted the optimized timing obtained from the proposed approach and gave positive feedbacks to the research team. We also collected field experiment data, which demonstrated overall energy reductions and speed improvements on some sections of the Shallowford Rd. arterial. We will continue the experiment when the COVID-19 pandemic impact subsides to have a more robust quantitative evaluation.

Wang, Qichao↗