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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Optimal Managed Fast-Charging Model for Electric Vehicle Fleets with High Utilization and Multiple Charge-Acceptance Curves

A predictive control/scheduling optimization model is proposed for managed charging of an electric vehicle (EV) fleet - under time-of-use energy and demand prices, high vehicle utilization frequency (short dwell times), multiple charge- acceptance curves (configurable charging rates), and flexible vehicle demand. This context is particularly relevant for flight schools (small electric aircraft) or other commercial facilities where an EV fleet performs multiple operating and fast-charging sessions on the same day. The proposed model performs both the operational and charging scheduling of the vehicles, which is not typically done for residential managed charging and significantly increases problem complexity. The problem is formulated as a MILP model and a case study of a small fast-charging station is presented. Results demonstrate a significant reduction in operating cost, mainly from peak shaving during high demand price periods, achieved by coordinating the operation of different vehicles, chargers and charging rates.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2023

An Investigation on the Pollen-Induced Soiling Losses in Utility-Scale PV Plants

Soiling, the accumulation of dust and other contaminants on the surface of photovoltaic (PV) modules, is a common factor that can negatively impact the performance of PV systems. In this study, the authors aim to analyze the impact of pollen on soiling losses in PV systems located in North Carolina, USA, particularly during the spring season. The performance data of two utility-scale PV plants was collected and analyzed using the two soiling extraction methods. Environmental data, including croplands and vegetation was also collected and analyzed to identify correlations with soiling losses. The results of the study may help improve understanding of necessary operation and maintenance activities for PV plants and provide new insights into the phenomenon of pollen deposition on PV systems.

correlation↗
DOE OSTI2024

Utility-Scale Shared Energy Storage Deployment: Challenges, Research Gaps, and Opportunities

Although community energy storage (CES) and behind-the-meter (BTM) energy storage systems have been widely used to offer homeowners and communities a variety of localized benefits, their scalability and grid support functionalities are limited. On the other hand, utility-scale shared energy storage (USES) systems may offer a number of benefits for grid integration, scalability, and economic viability. When compared to BTM and CES alternatives, these large-scale systems provide more storage capacity, more efficient operations, and more economically viable options. The deployment of USES presents opportunities for optimizing grid performance, integrating renewable energy resources, and improving energy security at the community level. However, significant research gaps exist in optimizing the integration and operation of these systems, especially to allocate energy for consumer use, grid services, and enhancing energy resilience. This paper reviews the literature in this regard, focusing on the opportunities, research gaps, and challenges associated with USES deployment. Firstly, the paper provides an overview of USES systems and emphasizes their benefits. Secondly, the key challenges are identified, and research gaps associated with the operation and integration of these systems are highlighted. Lastly, some potential solutions and opportunities that can be adopted to facilitate the rapid deployment and management of USES are presented. Technological, economic, regulatory, and environmental aspects are also discussed in this paper, providing an overview of the current state and future prospects of this technology.

Gautam, Mukesh [BATTELLE (PACIFIC NW LAB)] (ORCID:↗
DOE OSTI2021

Sequence Impedance Measurement of Utility-Scale Wind Turbines and Inverters – Reference Frame, Frequency Coupling, and MIMO/SISO Forms

Sequence impedance responses with or without considering frequency coupling in both MIMO and SISO forms are increasingly used for the stability analysis of three-phase power electronic systems; however, many aspects of sequence impedance measurement are not fully explored. It is not clear if the sequence impedance has a reference frame similar to the dq impedance. If so, the role of the grid voltage angle estimation in aligning the sequence impedance reference frame has not been discussed. Additionally, existing methods for measuring the sequence impedance with frequency coupling are complicated, are not feasible for large wind turbines and inverters, and provide the sequence impedance responses in only either MIMO or SISO form. This paper presents a sequence impedance measurement method that considers the frequency coupling, performs reference frame alignment, demonstrates the impact of the grid voltage angle estimation, and obtains the sequence impedance response in both MIMO and SISO forms. This paper demonstrates the proposed method and practical problems associated with the sequence impedance measurement of utility-scale wind turbines and inverters on a 1.9-MW Type III wind turbine and a 2.2-MVA inverter using an impedance measurement system built around a 7-MW/13.8-kV grid simulator and a 5-MW dynamometer.

17 WIND ENERGY↗
DOE OSTI2021

Fault Detection Utilizing Convolution Neural Network on Timeseries Synchrophasor Data From Phasor Measurement Units

An end-to-end supervised learning method is proposed for fault detection in the electric grid using Big Data from multiple Phasor Measurement Units (PMUs). The approach consists of preprocessing steps aimed at reducing data noise and dimensionality, followed by utilization of six classification models considered for detecting faults. Three of the models were variants of Convolutional Neural Network (CNN) architectures that consider a single type of measurement (voltage, current or frequency) at all PMUs or all types together also at all PMUs. CNN based models were compared to traditional methods of Logistic Regression (LR), Multi-layer Perceptron (MLP) and Support Vector Machine (SVM). Evaluation was conducted on two-year data measured by PMUs at 37 locations in a large electric grid. Here, the response variable for classification were extracted from the grid-wide outage event log. Experiments show that CNN-based models outperformed traditional methods on one year out-of-sample outage detection over the entire grid.

42 ENGINEERING↗
DOE OSTI2025

The Statistical Spread of Transmission Outages on a Fast Protection Time Scale Based on Utility Data

When there is a fault, the protection system automatically removes one or more transmission lines on a fast time scale of less than one minute. The outaged lines form a pattern in the transmission network. We extract these patterns from utility outage data, determine some key statistics of these patterns, and then show how to generate new patterns consistent with these statistics. The generated patterns provide a new and easily feasible way to model the overall effect of the protection system at the scale of a large transmission system. This new data-driven generative modeling of protection is expected to contribute to simulations of disturbances in large grids so that they can better quantify the risk of blackouts. Analysis of the pattern sizes suggests an index that describes how much outages spread in the transmission network at the fast timescale.

Transmission↗
DOE OSTI2023

A TCN-Based Hybrid Forecasting Framework for Hours-Ahead Utility-Scale PV Forecasting

This paper presents a Temporal Convolutional Network (TCN) based hybrid PV forecasting framework for enhancing hours-ahead utility-scale PV forecasting. The hybrid framework consists of two forecasting models: a physics-based trend forecasting (TF) model and a data-driven fluctuation forecasting (FF) model. Three TCNs are integrated in the framework for: i) blending the inputs from different Numerical Weather Prediction sources for the TF model to achieve superior performance on forecasting hourly PV profiles, ii) capturing spatial-temporal correlations between detector sites and the target site in the FF model to achieve more accurate forecast of intra- hour PV power drops, and iii) reconciling TF and FF results to obtain coherent hours-ahead PV forecast with both hourly trends and intra-hour fluctuations well preserved. To automatically identify the most contributive neighboring sites for forming a detector network, a scenario-based correlation analysis method is developed, which significantly improves the capability of the FF model on capturing large power fluctuations caused by cloud movements. Here, the framework is developed, tested, and validated using actual PV data collected from 95 PV farms in North Carolina. Simulation results show that the performance of 6 hours ahead PV power forecasting is improved by 20% - 30% compared with state-of-the-art methods.

42 ENGINEERING↗
DOE OSTI2022

GalR, GalX and AraR co-regulate $\tiny {D}$-galactose and $\tiny{L}$-arabinose utilization in Aspergillus nidulans

Filamentous fungi produce a wide variety of enzymes in order to efficiently degrade plant cell wall polysaccharides. The production of these enzymes is controlled by transcriptional regulators, which also control the catabolic pathways that convert the released monosaccharides. Two transcriptional regulators, GalX and GalR, control d-galactose utilization in the model filamentous fungus Aspergillus nidulans, while the arabinanolytic regulator AraR regulates l-arabinose catabolism. d-Galactose and l-arabinose are commonly found together in polysaccharides, such as arabinogalactan, xylan and rhamnogalacturonan I. Therefore, the catabolic pathways that convert d-galactose and l-arabinose are often also likely to be active simultaneously. In this study, we investigated the interaction between GalX, GalR and AraR in d-galactose and l-arabinose catabolism. For this, we generated single, double and triple mutants of the three regulators, and analysed their growth and enzyme and gene expression profiles. Our results clearly demonstrated that GalX, GalR and AraR co-regulate d-galactose catabolism in A. nidulans. GalX has a prominent role on the regulation of genes of d-galactose oxido-reductive pathway, while AraR can compensate for the absence of GalR and/or GalX.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Development of genetic tools for heterologous protein expression in a pentose‐utilizing environmental isolate of Pseudomonas putida

Abstract Pseudomonas putida has emerged as a promising host for the conversion of biomass‐derived sugars and aromatic intermediates into commercially relevant biofuels and bioproducts. Most of the strain development studies previously published have focused on P. putida KT2440, which has been engineered to produce a variety of non‐native bioproducts. However, P. putida is not capable of metabolizing pentose sugars, which can constitute up to 25% of biomass hydrolysates. Related P. putida isolates that metabolize a larger fraction of biomass‐derived carbon may be attractive as complementary hosts to P. putida KT2440. Here we describe genetic tool development for P. putida M2, a soil isolate that can metabolize pentose sugars. The functionality of five inducible promoter systems and 12 ribosome binding sites was assessed to regulate gene expression. The utility of these expression systems was confirmed by the production of indigoidine from C6 and C5 sugars. Chromosomal integration and expression of non‐native genes was achieved by using chassis‐independent recombinase‐assisted genome engineering (CRAGE) for single‐step gene integration of biosynthetic pathways directly into the genome of P. putida M2. These genetic tools provide a foundation to develop hosts complementary to P. putida KT2440 and expand the ability of this versatile microbial group to convert biomass to bioproducts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Galactomannan utilization by Cellvibrio japonicus relies on a single essential α‐galactosidase encoded by the aga27A gene

Plant mannans are a component of lignocellulose that can have diverse compositions in terms of its backbone and side-chain substitutions. Consequently, the degradation of mannan substrates requires a cadre of enzymes for complete reduction to substituent monosaccharides that can include mannose, galactose, and/or glucose. One bacterium that possesses this suite of enzymes is the Gram-negative saprophyte Cellvibrio japonicus, which has 10 predicted mannanases from the Glycoside Hydrolase (GH) families 5, 26, and 27. Here we describe a systems biology approach to identify and characterize the essential mannan-degrading components in this bacterium. The transcriptomic analysis uncovered significant changes in gene expression for most mannanases, as well as many genes that encode carbohydrate active enzymes (CAZymes) when mannan was actively being degraded. A comprehensive mutational analysis characterized 54 CAZyme-encoding genes in the context of mannan utilization. Growth analysis of the mutant strains found that the man26C, aga27A, and man5D genes, which encode a mannobiohydrolase, α-galactosidase, and mannosidase, respectively, were important for the deconstruction of galactomannan, with Aga27A being essential. Our updated model of mannan degradation in C. japonicus proposes that the removal of galactose sidechains from substituted mannans constitutes a crucial step for the complete degradation of this hemicellulose.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Triose phosphate utilization limitation: an unnecessary complexity in terrestrial biosphere model representation of photosynthesis

Triose phosphates are the principal product of photosynthesis. They are used within the chloroplast for starch synthesis, or translocated to the cytosol where they are used to fuel sucrose synthesis. Use of triose phosphate releases inorganic phosphate, and is under strict metabolic control that matches the supply of triose phosphate from the Calvin-Benson cycle to the demand for carbon by sinks (Heldt & Heldt, 2011; McClain & Sharkey, 2019). However, a low rate of triose phosphate utilization (TPU) can deplete the phosphate pool, restrict ATP synthesis and reduce the availability of ATP to power the Calvin-Benson cycle, thereby limiting photosynthesis (Sharkey, 1985).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Novel Approach for Bounding the Stress Experienced by the Core of Utility-Scale Printed Circuit Heat Exchangers Under Thermohydraulic Loads

Printed circuit heat exchangers (PCHEs) have rapidly gained popularity since being introduced nearly three decades ago, and they are currently widely deployed in the petrochemical and aviation industry. Their compactness, thermohydraulic efficiency, inherent suitability for high temperature/pressure fluids containment, and demonstrated durability are some of the reasons the nuclear industry is seeking to adopt this technology as well. However, the relatively strict nuclear-related regulatory design code, especially when classified as critical to the safety of the reactors, is posing challenges to adopting the technology. From stress analysis point of view, one undesirable feature of PCHEs is their geometrical complexity, which is implied by their multilength-scale features. As a result, a full-scale model of a utility-scale exchanger cannot simply be solved on a computer because meshing such components results in a vast number of degrees-of-freedom. Here, this work seeks to address the challenge of stress analyses to PCHEs by presenting a method to simplify the geometry of PCHE designs. The models proposed by this work can be practically analyzed on a standard computer and provide a path for implementing ASME design rules. The analyses presented herein are divided into five separate investigations. Each is carried out to incrementally simplify the analyzed model by addressing features such as the shapes of the flow passages, the complex distribution of stress in large components, the three-dimensionality of the stress and strain, the thermal stresses caused by thermohydraulic operation observed experimentally and more.

42 ENGINEERING↗
DOE OSTI2020

Evaluating factors influencing infrasonic signal detection and automatic processing performance utilizing a regional network

Physical and deployment factors that influence infrasound signal detection and assess automatic detection performance for a regional infrasound network of arrays in the Western U.S. are explored using signatures of ground truth (GT) explosions (yields). Despite these repeated known sources, published infrasound event bulletins contain few GT events. Arrays are primarily distributed toward the south-southeast and south-southwest at distances between 84 and 458 km of the source with one array offering azimuthal resolution toward the northeast. Events occurred throughout the spring, summer, and fall of 2012 with the majority occurring during the summer months. Depending upon the array, automatic detection, which utilizes the adaptive F-detector successfully, identifies between 14% and 80% of the GT events, whereas a subsequent analyst review increases successful detection to 24%–90%. Combined background noise quantification, atmospheric propagation analyses, and comparison of spectral amplitudes determine the mechanisms that contribute to missed detections across the network. This analysis provides an estimate of detector performance across the network, as well as a qualitative assessment of conditions that impact infrasound monitoring capabilities. Finally, the mechanisms that lead to missed detections at individual arrays contribute to network-level estimates of detection capabilities and provide a basis for deployment decisions for regional infrasound arrays in areas of interest.

58 GEOSCIENCES↗
DOE OSTI2022

Biochemical and Regulatory Analyses of Xylanolytic Regulons in Caldicellulosiruptor bescii Reveal Genus-Wide Features of Hemicellulose Utilization

Microbial deconstruction of lignocellulose for the production of biofuels and chemicals requires the hydrolysis of heterogeneous hemicelluloses to access the microcrystalline cellulose portion. This work extends previous in vivo and in vitro efforts to characterize hemicellulose utilization by integrating genomic reconstruction, transcriptomic data, operon structures, and biochemical characteristics of key enzymes to understand the deployment and functionality of hemicellulases by the extreme thermophile Caldicellulosiruptor bescii .

Biotechnology & Applied Microbiology↗
DOE OSTI2025

Modification and analysis of context-specific genome-scale metabolic models: methane-utilizing microbial chassis as a case study

ABSTRACT Context-specific genome-scale model (CS-GSM) reconstruction is becoming an efficient strategy for integrating and cross-comparing experimental multi-scale data to explore the relationship between cellular genotypes, facilitating fundamental or applied research discoveries. However, the application of CS modeling for non-conventional microbes is still challenging. Here, we present a graphical user interface that integrates COBRApy, EscherPy, and RIPTiDe, Python-based tools within the BioUML platform, and streamlines the reconstruction and interrogation of the CS genome-scale metabolic frameworks via Jupyter Notebook. The approach was tested using -omics data collected for Methylotuvimicrobium alcaliphilum 20Z R , a prominent microbial chassis for methane capturing and valorization. We optimized the previously reconstructed whole genome-scale metabolic network by adjusting the flux distribution using gene expression data. The outputs of the automatically reconstructed CS metabolic network were comparable to manually optimized i IA409 models for Ca-growth conditions. However, the CS model questions the reversibility of the phosphoketolase pathway and suggests higher flux via primary oxidation pathways. The model also highlighted unresolved carbon partitioning between assimilatory and catabolic pathways at the formaldehyde-formate node. Only a very few genes and only one enzyme with a predicted function in C1 metabolism, a homolog of the formaldehyde oxidation enzyme ( fae1-2 ), showed a significant change in expression in La-growth conditions. The CS-GSM predictions agreed with the experimental measurements under the assumption that the Fae1-2 is a part of the tetrahydrofolate-linked pathway. The cellular roles of the tungsten (W)-dependent formate dehydrogenase ( fdhAB ) and fae homologs ( fae1-2 and fae3 ) were investigated via mutagenesis. The phenotype of the f dhAB mutant followed the model prediction. Furthermore, a more significant reduction of the biomass yield was observed during growth in La-supplemented media, confirming a higher flux through formate. M. alcaliphilum 20Z R mutants lacking fae1-2 did not display any significant defects in methane or methanol-dependent growth. However, contrary to fae1, the fae1-2 homolog failed to restore the formaldehyde-activating enzyme function in complementation tests. Overall, the presented data suggest that the developed computational workflow supports the reconstruction and validation of CS-GSM networks of non-model microbes. IMPORTANCE The interrogation of various types of data is a routine strategy to explore the relationship between genotype and phenotype. An efficient approach for integrating and cross-comparing experimental multi-scale data in the context of whole-genome-based metabolic network reconstruction becomes a powerful tool that facilitates fundamental and applied research discoveries. The present study describes the reconstruction of a context-specific (CS) model for the methane-utilizing bacterium, Methylotuvimicrobium alcaliphilum 20Z R . M. alcaliphilum 20Z R is becoming an attractive microbial platform for the production of biofuels, chemicals, pharmaceuticals, and bio-sorbents for capturing atmospheric methane. We demonstrate that this pipeline can help reconstruct metabolic models that are similar to manually curated networks. Furthermore, the model is able to highlight previously overlooked pathways, thus advancing fundamental knowledge of non-model microbial systems or promoting their development toward biotechnological or environmental implementations.

Kulyashov, M. A.↗
DOE OSTI2023

(Invited) Utilization of Bio-CO 2 and Bio-Methane for Fuel Production: Integration Solid Oxide Electrolyzer, Low Energy Plasma Reformer with Fischer-Tropsch Synthesis

Transition to renewable energy is essential to achieve climate protection objectives. Besides storing electricity for later use, fuel production using renewable energy is an essential part of reducing fossil dependance. The highest value application in current markets is the production of liquid transportation fuels such as sustainable aviation fuels (SAF) from sustainable, ideally biogenic carbon resources. A system is presented for processing anaerobic digester gas for liquid hydrocarbon production. Bio-CO 2 is processed through a solid oxide electrolysis cell and bio-CH 4 through a low energy plasma reformer. The combined synthesis gas is supplied to a Fischer-Tropsch reactor for the production of liquid hydrocarbons. The combination of technologies nearly doubles the yield of biofuel by utilizing the bio-CO 2 in addition to the bio-CH 4 . Here, the product fuel is all bio-carbon but it also embodies renewable electric energy in a high-value, storable and transportable liquid hydrocarbon.

09 BIOMASS FUELS↗