Search NASA⌕ Search

SEARCH · Search NASA

Results for “Control Allocation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Central transcriptional regulator controls photosynthetic growth and carbon storage in response to high light

Carbon capture and biochemical storage are some of the primary drivers of photosynthetic yield and productivity. To elucidate the mechanisms governing carbon allocation, we designed a photosynthetic light response test system for genetic and metabolic carbon assimilation tracking, using microalgae as simplified plant models. The systems biology mapping of high light-responsive photophysiology and carbon utilization dynamics between two variants of the same Picochlorum celeri species, TG1 and TG2 elucidated metabolic bottlenecks and transport rates of intermediates using instationary 13 C-fluxomics. Simultaneous global gene expression dynamics showed 73% of the annotated genes responding within one hour, elucidating a singular, diel-responsive transcription factor, closely related to the CCA1/LHY clock genes in plants, with significantly altered expression in TG2. Transgenic P. celeri TG1 cells expressing the TG2 CCA1/LHY gene, showed 15% increase in growth rates and 25% increase in storage carbohydrate content, supporting a coordinating regulatory function for a single transcription factor.

09 BIOMASS FUELS↗
DOE OSTI2016

Down-regulation of KORRIGAN -like endo-β-1,4-glucanase genes impacts carbon partitioning, mycorrhizal colonization and biomass production in Populus

Here, a greater understanding of the genetic regulation of plant cell wall remodeling and the impact of modified cell walls on plant performance is important for the development of sustainable biofuel crops. Here, we studied the impact of down-regulating KORRIGAN-like cell wall biosynthesis genes, belonging to the endo-β-1,4-glucanase gene family, on Populus growth, metabolism and the ability to interact with symbiotic microbes. The reductions in cellulose content and lignin syringyl-to-guaiacyl unit ratio, and increase in cellulose crystallinity of cell walls of PdKOR RNAi plants corroborated the functional role of PdKOR in cell wall biosynthesis. Altered metabolism and reduced growth characteristics of RNAi plants revealed new implications on carbon allocation and partitioning. The distinctive metabolome phenotype comprised of a higher phenolic and salicylic acid content, and reduced lignin, shikimic acid and maleic acid content relative to control. Plant sustainability implications of modified cell walls on beneficial plant-microbe interactions were explored via co-culture with an ectomycorrhizal fungus, Laccaria bicolor . A significant increase in the mycorrhization rate was observed in transgenic plants, leading to measurable beneficial growth effects. These findings present new evidence for functional interconnectedness of cellulose biosynthesis pathway, metabolism and mycorrhizal association in plants, and further emphasize the consideration of the sustainability implications of plant trait improvement efforts.

09 BIOMASS FUELS↗
DOE OSTI2018

Optimal allocation of series FACTS devices in large‐scale systems

Series flexible AC transmission systems devices, such as the variable series reactor, have the ability to continuously regulate the transmission line reactance so as to control power flow. This study presents a new approach to optimally locating such devices in the transmission network considering multiple operating states and contingencies. To investigate optimal investment, a single target year planning with three different load patterns is considered. The transmission contingencies may occur under any of the three load conditions and the coupling constraints between base case and contingencies are included. A reformulation technique transforms the original mixed integer non‐linear programming model into mixed integer linear programming model. To further relieve the computational burden and enable the planning model to be directly applied to practical large‐scale systems, a two‐phase decomposition algorithm is introduced. Detailed numerical simulation results on IEEE 118‐bus system and the Polish 2383‐bus system illustrate the efficient performance of the proposed algorithm.

Zhang, Xiaohu↗
DOE OSTI2017

Prototype Design, Analysis, and Results for a Liquid Radiological Waste Control Room

Human factors researchers at Idaho National Laboratory are collaborating with a utility partner to address human factors in the modernization of their radiological waste control room. The collaborating utility, Palo Verde, plans to remove all control boards associated with the liquid radiological waste system, which include controls, indicators, and alarm systems, and replace them with modernized digital instrumentation and controls and displays. To be sure the new system either supports current operational performance or enhances it, researchers have carried out three planning and analysis activities: expert operator review, function allocation analysis, and human factor principles and design applications. Researchers utilized access to expert operators to gain information about the system. Operators were asked to detail a procedure exemplifying typical interactions with the liquid radiological waste system and provide it to Idaho National Laboratory with a list of functionalities to incorporate (Section 4.1). Later, operators were asked to provide additional feedback to inform a prototype with adequate realism to support sound analysis of the system design (Section 4.2). Other operators not associated with the utility partner were also involved in experiment design and prototype evaluation (Section 4.2). Due to the extent of the upgrade, care was given to measure the change in the operator’s role (Section 7). As part of the modernization, some plant systems are expected to be equipped with automation or sensors that send information directly to the control where previously operators were required to enter controlled areas to find the information. Such updates made slight changes to operator role requirements, but the impact was negligible. The way the system is operated will remain largely the same, but operator convenience and safety is expected to increase. Additionally, to map operator tasks during the selected procedure, an Operational Sequence Diagram was created (Section 7.1). The diagram helped to account for every interaction and piece of equipment needed to create the prototype design. Alternatively, the diagram can be created following the final design to identify any function reallocations due to redesign. Human factors principles were also applied to the design. An ergonomic assessment was performed on the workspace resulting in various recommendations for placing and designing the new workstation (Section 6). A 3 D mockup of the control room was created to depict the options available with in-depth descriptions of each. Furthermore the prototype design incorporates well known human factors principles. However, to be sure the principles are sound in the control room context, the researches have designed an experiment to measure the impact design decision has on operator performance. The experiment is described in detail in Section 5. Lastly, a tool emerged as this effort began called the NUREG 0711 Crosswalk (Section 8). The tool has multiple uses, but it was primarily intended to communicate how the researcher’s action directly mapped to specific results suggested in the Nuclear Regulatory Commission review guideline. The tool also maps how current results impact future decisions in the modernization process.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Power allocation for visible light communication

A system and method for providing optical multiple input and multiple output data communication using optical signals includes a plurality of light sources, a plurality of photodetectors, and at least one controller. The plurality of light sources are configured to emit optical signals to communicate data. The plurality of photodetectors are configured to sense the optical signals, and are embedded in at least one receiver. At least one of the plurality of photodetectors is configured to receive the optical signals from two or more of the plurality of light sources. The controller is configured to assign a transmit power to at least some of the plurality of light sources based on parameters of the plurality of photodetectors.

Brandt-Pearce, Maite↗
DOE OSTI2022

Hierarchical Transactive Control of Flexible Building Loads Under Distribution LMP

With grid modernization efforts, future distribution networks, which consist of various distributed generators and flexible loads, will be more flexible and active. All new network components of distributed energy resources (DERs) drive and enable the transition towards a market-based distribution net-work that seeks the optimal allocation of all DERs. To address challenges associated with DERs, one promising solution is to utilize demand-side flexibility of building loads facilitated by demand response (DR) programs and provide ancillary grid services through distribution-level markets. Under this new paradigm, this paper proposes an efficient DR management strategy incorporating emerging price signals of distribution markets, i.e., distribution locational marginal price (DLMP), based on a hierarchical transactive control approach. The proposed approach establishes a two-layer decision-making framework; the upper layer formulates a bilevel model to obtain an optimal demand response (ODR) under DLMP, and the lower layer employs model-free control to dispatch the (aggregated) ODR to individual end users. Numerical case studies using a modified IEEE 33 test network are performed to verify the effectiveness of the proposed approach; load shifting and peak shaving for the distribution system operator and payments’ reduction for end users while maintaining their comfort.

Park, Byungkwon↗
DOE OSTI2024

Perturbation of tonoplast sucrose transport alters carbohydrate utilization for seasonal growth and defense metabolism in coppiced poplar

Abstract Nonstructural carbohydrate reserves of stems and roots underpin overall tree fitness and productivity under short-rotation management practices such as coppicing for bioenergy. While sucrose and starch comprise the predominant stem carbohydrate reserves of Populus, utilization for fitness and agricultural productivity is understood primarily in terms of starch turnover. The tonoplast sucrose transport protein SUT4 modulates sucrose export from source leaves to distant sinks during photoautotrophic growth, but the possibility of its involvement in remobilizing carbohydrates from storage organs during heterotrophic growth has not been explored. Here, we used PtaSUT4-knockout mutants of Populus tremula × P. alba (INRA 717-1B4) in winter (cool) and summer (warm) glasshouse coppicing experiments to assess SUT4 involvement in reserve utilization. Conditions preceding and supporting summer sprouting were considered favorable for growth, while those preceding and supporting cool temperature sprouting were suboptimal akin to conditions associated with coppicing as generally practiced. Epicormic bud emergence was delayed in sut4 mutants following lower temperature ‘winter’ but not summer coppicing. Winter xylem hexose increases were observed in control but not in sut4 stumps after coppicing. The magnitude of starch and sucrose reserve depletion was similar in control and sut4 stumps during the winter and did not explain the sprouting and xylem hexose differences. However, winter maintenance costs appeared higher in sut4 based partly on Krebs cycle intermediate levels. In control plants, bark accrual of abundant defense metabolites, including salicinoids and condensed tannins, was higher in summer than in winter, but this increase of summer defense allocations was attenuated in sut4 mutants. Temperature-sensitive trade-offs between growth and other priorities may therefore depend on SUT4 in Populus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Future SDN-HPON Control Plane Architecture and Protocol for On-Demand Terabit End-to-End Extreme-Scale Science Applications

The UC Davis team conducted architecture, algorithm and experimental studies for next generation ultra-high-bandwidth optical networks in support of extreme-scale science applications. In particular, over the course of this 3-year project, the UC Davis team achieved the following main accomplishments: Designed a network architecture for automated multi-domain service provisioning: Designed information exchange schemes between autonomous systems (domains) Designed application programming interfaces to orchestrate resource reservation in data centers, high performance computation facilities, and communication networks belonging to different autonomous systems Experimentally assessed the multi-domain network architecture in a distributed field trial set-up connecting premises in three continents Designed a broker-based orchestrated multi-domain optical networking framework supporting observe-analyze-act cycle based cognitive inter-domain service provisioning: Designed an inter-domain operation mechanism, e.g., topology abstraction, for the broker plane and domain managers to collaboratively accomplish inter-domain service provisioning while respecting the autonomy of each administrative domain Designed an alien wavelength monitoring scheme and an artificial neural network based optical signal-to-noise ratio estimator for quality-of-transmission aware inter-domain service provisioning Developed a deep neural network based multi-domain traffic predictor and a cognitive routing and spectrum assignment algorithm to realize knowledge-based autonomous traffic engineering in multi-domain networks Implemented an optical signal-to-noise ratio estimator and traffic predictor with Google’s Tensor flow and assessed their performance using experimental and synthetic data Demonstrated the benefits of the proposed cognitive schemes with experiments ona two-domain elastic optical network testbed and evaluations on a six-domain simulation framework Built a two-domain software-defined networking control plane testbed using the ONOS platform and demonstrated the workflow of broker and domain manager cooperation, including hierarchical performance monitoring, topology abstraction and cognitive resource allocation. Designed self-learning cognitive service provisioning schemes using advanced machine learning technologies: Designed a self-taught anomaly detection framework for optical networks, including an unsupervised data clustering module for pattern recognition, a supervised data regression and classification module for online anomaly detection, and the system operation principle Experimentally validated the effectiveness of the self-taught anomaly detection framework with various failure/anomaly scenarios. Designed a self-learning autonomic routing, modulation and spectrum assignment (RMSA) provisioning framework for elastic optical networks with deep reinforcement learning. Designed effective modeling and training mechanisms for the self-learning RMSA framework Conducted extensive numerical simulations with various traffic patterns and topologies to verify the advantage of the self-learning RMSA framework.

42 ENGINEERING↗
DOE OSTI2019

Coordination of thermostatically controlled loads with unknown parameters

Apparatus and methods are disclosed for coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives including bidding and market clearing strategies designed to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. In one examples of the disclosed technology, a method of operating a load includes estimating a set of values for unmeasured parameters of the load's thermal environment based on output measurements of the thermal environment, determining an energy response based on the estimated set of values for the unmeasured parameters, and transmitting a bid for power for a finite time period based on the determined energy response to the coordinator. A clearing price is received from the coordinator responsive to the transmitted bid and power is sent to the load responsive to the received clearing price.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Techno-Economic Viability of Flexible Dispatch of Unconventional Geothermal Systems

Flexible geothermal operations could boost project returns through the allocation of improved power purchase agreements and/or exploitation of power price arbitrage opportunities. In this study, we investigated the techno-economic feasibility of variable flow rate control and time-of-day pricing in closed-loop geothermal systems. We considered U-shaped multilateral system configurations and modeled a variety of technical system parameters. These designs were simulated using a slender-body theory (SBT) model for transient heat transfer and fluid flow. This subsurface model was integrated into the flexible geothermal economic model (FGEM) tool to evaluate the overall flexible geothermal system techno-economics. Future hourly ambient temperature conditions were based on the Sup3rCC dataset. Published datasets were used for future hourly wholesale electricity prices. We analyzed four operating strategies: 1) baseload operation, 2) seasonal dispatch (high flow rate during summer and nominal flow rate during the rest of the year), 3) net generation maximization by varying flow rate to maximize net power output, and 4) revenue maximization by varying flow rate to maximize revenue. We ran all four scenarios for a multiloop configuration with 12 lateral passes, 7-km vertical depth and 87-km total drilling length. Furthermore, we assumed a 60 degrees C/km geothermal gradient and ambient temperature and wholesale electricity prices for New Mexico as a typical state location. The nominal flow rate was set to 80 kg/s. When considering drilling costs of $1,000/m and a discount rate of 7%, the generation maximization scenario resulted in the lowest levelized cost of electricity (LCOE) of ~$150/MWh. When considering project return on investment (ROI), defined as lifetime net income divided by upfront capital costs, all flexible operation scenarios performed better than the base case scenario. The highest ROI of 80% was obtained with the revenue maximization scenario. With drilling costs of $200/m and a discount rate of 5%, the generation maximization scenario resulted in LCOE of $49/MWh.

flexible geothermal↗
DOE OSTI2023

Terrestrial carbon dynamics in an era of increasing wildfire

In an increasingly flammable world, wildfire is altering the terrestrial carbon balance. However, the degree to which novel wildfire regimes disrupt biological function remains unclear. Here, we synthesize the current understanding of above and below ground processes that govern carbon loss and recovery across diverse ecosystems. In this study, we find that intensifying wildfire regimes are increasingly exceeding biological thresholds of resilience, causing ecosystems to convert to a lower carbon-carrying capacity. Growing evidence suggests that plants compensate for fire damage by allocating carbon below ground to access nutrients released by fire, while wildfire selects for microbial communities with rapid growth rates and the ability to metabolize pyrolyzed carbon. Determining controls on carbon dynamics following wildfire requires integration of experimental and modeling frameworks across scales and ecosystems. Fire severity is expected to increase as a result of warming. This will potentially amplify climate change due to its impact on the carbon cycle. This Review discusses ecosystem carbon loss and recovery following wildfire, and highlights where further work is needed to inform model predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Virtual Environment for Testing Software-Defined Networking Solutions for Scientific Workflows

Recent developments in software-defined infrastructures promise that scientific workflows utilizing supercomputers, instruments, and storage systems will be dynamically composed and orchestrated using software at unprecedented speed and scale in the near future. Testing of the underlying networking software, particularly during initial exploratory stages, remains a challenge due to potential disruptions, and resource allocation and coordination needed over the multi-domain physical infrastructure. To overcome these challenges, we develop the Virtual Science Network Environment (VSNE) that emulates the multi-site host, storage, and network infrastructure using Virtual Machines (VMs), wherein the production and nascent software can be tested. Within each VM, which represents a site, the hosts and local-area networks are emulated using Mininet, and the Software-Defined Network (SDN) controllers and service daemon codes are natively run to support dynamic provisioning of network connections. Additionally, Lustre filesystem support at the sites and an emulation of the long-haul network using Mininet, are provided using separate VMs. As case studies, we describe Lustre file transfers using XDD, Red5 streaming service demonstration, and an emulated experiment with remote monitoring and steering modules, all supported over dynamically configured connections using SDN controllers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Post-Disturbance Dynamic Distribution System Restoration with DGs and Mobile Resources

Distributed generations (DGs) can act as emergency power supplies when distribution systems suffer from outages. However, the generation capabilities of DGs are generally limited by a number of factors including weather conditions, fuel limitations, etc. In this context, mobile resources that are able to reallocate resources to desired locations are regarded as important complements to conventional fixed DGs in assisting distribution system restoration. In this paper, a distribution system restoration model with DGs and mobile resources is proposed. Firstly, the dispatch and allocation of mobile resources are modeled with respect to the characteristics of the traffic network. Then the developed mobile resource models are integrated into the distribution system restoration model to co-optimize the scheduling of DGs and mobile resources. Uncertainty factors are managed by a model predictive control approach so that system operators can dynamically adjust the restoration strategy with the up-to-date information. The effectiveness of the proposed method is validated through an IEEE 13-bus test system.

distributed generations (DGs)↗
DOE OSTI2017

Modeling Road Vulnerability to Snow Using Mixed Integer Optimization

As the number and severity of snowfall events continue to grow, the need to intelligently direct road maintenance during these snowfall events will also grow. In several locations, local governments lack the resources to completely treat all roadways during snow events. Furthermore, some governments utilize only traffic data to determine which roads should be treated. As a result, many schools, businesses, and government offices must be unnecessarily closed, which directly impacts the social, educational, and economic well-being of citizens and institutions. In this work, we propose a mixed integer programming formulation to optimally allocate resources to manage snowfall on roads using meteorological, geographical, and environmental parameters. Additionally, we evaluate the impacts of an increase in budget for winter road maintenance on snow control resources.

Mixed integer optimization↗
DOE OSTI2021

Forest stand and canopy development unaltered by 12 years of CO2 enrichment*

Abstract Canopy structure—the size and distribution of tree crowns and the spatial and temporal distribution of leaves within them—exerts dominant control over primary productivity, transpiration and energy exchange. Stand structure—the spatial arrangement of trees in the forest (height, basal area and spacing)—has a strong influence on forest growth, allocation and resource use. Forest response to elevated atmospheric CO2 is likely to be dependent on the canopy and stand structure. Here, we investigated elevated CO2 effects on the forest structure of a Liquidambar styraciflua L. stand in a free-air CO2 enrichment experiment, considering leaves, tree crowns, forest canopy and stand structure. During the 12-year experiment, the trees increased in height by 5 m and basal area increased by 37%. Basal area distribution among trees shifted from a relatively narrow distribution to a much broader one, but there was little evidence of a CO2 effect on height growth or basal area distribution. The differentiation into crown classes over time led to an increase in the number of unproductive intermediate and suppressed trees and to a greater concentration of stand basal area in the largest trees. A whole-tree harvest at the end of the experiment permitted detailed analysis of canopy structure. There was little effect of CO2 enrichment on the relative leaf area distribution within tree crowns and there was little change from 1998 to 2009. Leaf characteristics (leaf mass per unit area and nitrogen content) varied with crown depth; any effects of elevated CO2 were much smaller than the variation within the crown and were consistent throughout the crown. In this young, even-aged, monoculture plantation forest, there was little evidence that elevated CO2 accelerated tree and stand development, and there were remarkably small changes in canopy structure. Questions remain as to whether a more diverse, mixed species forest would respond similarly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Enabling DER Participation in Frequency Regulation Markets

Distributed energy resources (DERs) are playing an increasing role in ancillary services for the bulk grid, particularly in frequency regulation. In this article, we propose a framework for collections of DERs, combined to form microgrids and controlled by aggregators, to participate in frequency regulation markets. Our approach covers both the identification of bids for the market clearing stage and the mechanisms for the real-time allocation of the regulation signal. The proposed framework is hierarchical, consisting of a top layer and a bottom layer. The top layer consists of the aggregators communicating in a distributed fashion to optimally disaggregate the regulation signal requested by the system operator. The bottom layer consists of the DERs inside each microgrid whose power levels are adjusted so that the tie line power matches the output of the corresponding aggregator in the top layer. The coordination at the top layer requires the knowledge of cost functions, ramp rates, and capacity bounds of the aggregators. We develop meaningful abstractions for these quantities respecting the power flow constraints and taking into account the load uncertainties and propose a provably correct distributed algorithm for optimal disaggregation of regulation signals among the microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Self-Organizing Map-Based Resilience Quantification and Resilient Control of Distribution Systems Under Extreme Events

Due to climate change, extreme weather events are occurring more frequently and with increasing impact. This trend poses a significant challenge for distribution system operators (DSO) to ensure that there is uninterrupted power supply to critical loads in their networks. To embed resilience into DSO's decision-making, resilience needs to be first quantified and then integrated into the system-level optimization. Therefore, this paper first develops a novel self-organizing map (SOM) based method (called SomRes) to quantify the time-varying resilience index of a system that can leverage the powerful classification property of SOMs and removes some of the disadvantages of subjective weight assignment methods. Using SomRes, a resilient resource allocation and operational dispatch algorithm is further developed to enhance system resilience against extreme events by considering the SomRes resilience index directly as the feedback. Here, the proposed resilience quantification approach is benchmarked with a state-of-the-art approach and the efficacy of the proposed resilient dispatch algorithm is demonstrated through several deterministic and statistical case studies on the IEEE 123-bus distribution system. Simulation studies show that the proposed SomRes quantification method is an appropriate indicator of system resilience, and the resilient resource allocation and dispatch strategy can significantly reduce critical load shedding under varying event propagation scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

VA EDH Advanced Software Pipeline Framework Report: Enhancing Automation and Scalability

The VA Environmental Determinants of Health (EDH) Advanced Software Pipeline Framework is designed to enhance the efficiency, scalability, and security of geospatial data processing workflows. This framework integrates modern data orchestration and containerization technologies, including Prefect for workflow automation, Docker for containerization, and PostgreSQL/PostGIS for geospatial data storage and analysis. It ensures standardized, reproducible, and automated data processing, supporting VA objectives related to substance use risk assessment and recovery research. The pipeline addresses key scalability and performance challenges through horizontal and vertical scaling, high-performance computing (HPC) integration, parallel processing, task caching, and dynamic resource allocation. These optimizations improve throughput and reduce latency, allowing the system to efficiently manage large and complex datasets. Additionally, security and compliance measures—such as data encryption (SSL), Role-Based Access Control (RBAC), and adherence to GDPR and HIPAA standards—safeguard sensitive information throughout data transmission and storage. A key implementation of this framework includes the automation of shelter list geolocation workflows, ensuring that up-to-date data is readily available for VA decision-making. Lessons learned from this project include the transition from in-memory processing to incremental storage writes, improving resource management and reliability. Future enhancements aim to expand automation, integrate AI-driven anomaly detection, and incorporate high-performance computing resources. This framework provides a scalable, secure, and adaptable solution for managing geospatial datasets, reinforcing the VA’s ability to support clinical and strategic initiatives through data-driven decision-making.

97 MATHEMATICS AND COMPUTING↗