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At least 451 records · Page 25

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DOE OSTI2020

Towards Robustness Guarantees for Feedback-Based Optimization

Feedback-based online optimization algorithms have gained traction in recent years because of their simple implementation, their ability to reject disturbances in real time, and their increased robustness to model mismatch. While the robustness properties have been observed both in simulation and experimental results, the theoretical analysis in the literature is mostly limited to nominal conditions. In this work, we propose a framework to systematically assess the robust stability of feedback-based online optimization algorithms. We leverage tools from monotone operator theory, variational inequalities and classical robust control to obtain tractable numerical tests that guarantee robust convergence properties of online algorithms in feedback with a physical system, even in the presence of disturbances and model uncertainty. The results are illustrated via an academic example and a case study of a power distribution system.

approximation algorithms↗

DOE OSTI2023

Creation of Synthetic Electric Grids (SPP/MISO) Supporting PERFORM (Final Report)

Over the course of the project, two “realistic but not real” synthetic transmission-level grid models over the SPP-MISO and ERCOT footprints were created to provide more realistic data and increase the reliability and resiliency of the grids under a variety of scenarios. The synthetic ERCOT transmission grid is compatible with the distribution grid developed in collaboration with NREL. All generators are based on the EIA 860 data and a column with EIA plant code and Gen ID is added to generators of both grids so that they can be easily mapped. The improvements are also made to electric grids including N-1 contingencies with some remedial actions, improving the transmission lines to avoid lines in lakes, including an HVDC line to the SPP-MISO case, providing several generator parameters and their temporal constraints that were not included in EIA 860 form, generators’ cost curves, load offer curves, adding phase shifters and tap changers with impedance correction tables, adding reactive power control and partitioning the grids into active and reactive reserve zones and determine different types of the required reserve for each zone. Hourly load time series at the bus level were generated to create scenarios for solving power flow in different loading conditions. Weather measurement information and the models of renewable generators are used to directly include the impact of weather on the grids. Based on a variety of load and weather conditions the grids are improved to accommodate different conditions. The ERCOT 7k-bus grids were also modeled for the year 2030 with predicted improvements in renewable resources. The renewable generation model was also improved with historic weather data included. The impact of electric vehicles on the ERCOT grid is also modeled.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Quantitative Metrics for Grid Resilience Evaluation and Optimization

Power system resilience has become a critical topic in recent years because of the increasing trend of extreme events and the growing integration of intermittent renewable energy sources. To enhance grid resilience against high-impact, low-frequency events, two questions should be answered: how to quantify the resilience of a given grid and how to incorporate the quantification into power system planning, operation, and restoration. Here this paper develops a new set of quantitative metrics with clear physical interpretation to comprehensively evaluate power system resilience. Using microgrids as an example, an event-based corrective scheduling (ECS) model and an online model predictive control (OMPC) model are developed to integrate the proposed quantitative resilience metrics into power system optimization models for resilience enhancement. The ECS model employs extreme event data to investigate the optimal restoration solution and to help microgrid operators prepare to respond to similar events. The OMPC model provides online decision-making support for operators to handle ongoing outages in the most resilient fashion. The effectiveness and superiority of the proposed quantitative resilience metrics and the resilience enhancement models are demonstrated through simulations and comparative studies on an IEEE test feeder and a real distribution feeder in Southern California.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Operation at Reduced Atmospheric Pressure and Concept of Reliability Redundancy for Optimized Design of Insulation Systems

Electrified transportation is calling for insulation design criteria that is adequate to provide elevated levels of power density, power dynamics and reliability. Increasing voltage levels are expected to cause accelerated intrinsic and extrinsic aging effects which will not be easily predictable at the design stage due to a lack of suitable modeling. Designing reliable insulation systems would require finding solutions able to control accelerated aging due to an unpredictable increase of intrinsic stresses and the onset of extrinsic stresses as partial discharges. This paper proposes the concept of reliability redundancy for the insulation design of aerospace electrical asset components, which is also validated at lower-than-standard atmospheric pressure. The principle is that extrinsic-aging-free design might be achieved upon determining the aging stress or abnormal service stresses distribution and being sure that aging will not generate conditions that can incept extrinsic aging (partial discharges) during operation life. However, such information is never, in practice, fully available to insulation system designers. Hence, especially in critical applications such as electrified aircraft, aerospace, and combat ships a further level of reliability should be added to a partial-discharge-free design, which can consist of the use of corona-resistant materials and/or of life models able to consider the accelerated aging effect of partial discharges (or any other type of extrinsic-accelerated aging factor). Innovative life modeling considering both extrinsic and intrinsic aging stresses, insulating material testing to estimate model parameters, and a metric for quantifying the extent of corona (or partial discharge) resistance can lead to establishing feasibility and limit conditions for optimized or fully reliability-redundant design. It is shown in the paper that if an extrinsic-aging-free design is not feasible, and it is therefore replaced by a redundant design, a further level of reliability redundancy can be provided by effective condition monitoring plans.

Montanari, Gian Carlo↗

NASA NTRS1987

Flight investigation of the effect of tail configuration on stall, spin, and recovery characteristics of a low-wing general aviation research airplane

Flight tests were performed to investigate the stall, spin, and recovery characteristics of a low-wing, single-engine, light airplane with four interchangeable tail configurations. The four tail configurations were evaluated for effects of varying mass distribution, center-of-gravity position, and control inputs. The airplane tended to roll-off at the stall. Variations in tail configuration produced spins ranging from 40 deg to 60 deg angle of attack and turn rates of about 145 to 208 deg/sec. Some unrecoverable flat spins were encountered which required use of the airplane spin chute for recovery. For recoverable spins, antispin rudder followed by forward wheel with ailerons centered provided the quickest spin recovery. The moderate spin modes agreed very well with those predicted from spin-tunnel model tests, however, the flat spin was at a lower angle of attack and a slower rotation rate than indicated by the model tests.

Stough, H. Paul, III↗

NASA NTRS1988

An integrated and modular digital modeling approach for the space station electrical power system development

An electrical power system for the Space Station was designed, developed and built. This system provides for electrical power generation, conditioning, storage, and distribution. The initial configuration uses photovoltaic power generation. The power system control is based on a hierarchical architecture to support the requirements of automation. In the preliminary design and technology development phase of the program, various modeling techniques and software tools were evaluated for the purpose of meeting the Space Station power system modeling requirements. Rocketdyne and LeRC jointly selected the EASY5 simulation software, developed by Boeing Computer Services, as a system level modeling tool. The application of the selected analytical modeling approach to represent the entire power system is described. Typical results of model predictions are also summarized. The equipment modeled includes solar arrays, dc to ac converters, resonant inverters, battery storage system, alternator, transmission line, switch gear, and system level microprocessor controls. During the advanced development phase of this program, several models were developed using this approach.

Gombos, Frank J.↗

NASA NTRS1987

Two experimental supercritical laminar-flow-control swept-wing airfoils

Two supercritical laminar-flow-control airfoils were designed for a large-chord swept-wing experiment in the Langley 8-Foot Transonic Pressure Tunnel where suction was provided through most of the model surface for boundary-layer control. The first airfoil was derived from an existing full-chord laminar airfoil by extending the trailing edge and making changes in the two lower-surface concave regions. The second airfoil differed from the first one in that it was designed for testing without suction in the forward concave region of the lower surface. Differences between the first airfoil and the one from which it was derived as well as between the first and second airfoils are discussed. Airfoil coordinates and predicted pressure distributions for the design normal Mach number of 0.755 and section lift coefficient of 0.55 are given for the three airfoils.

Allison, Dennis O.↗

NASA NTRS1988

An integrated and modular digital modeling approach for the Space Station electrical power system development

Gombos, Frank J.↗

NASA NTRS1990

Predicted and measured in-flight wing deformations of a forward-swept-wing aircraft

An electrooptical flight-deflection measurement system (FDMS) is described in terms of its use in structural testing of the composite forward-swept wing of the X-29 aircraft. The wing deflected shapes measured using the present system are compared to the shapes predicted by NASTRAN and other codes as well as data from ground-test load measurements. The electrooptical FDMS is based on a control unit, two receivers, a target driver, and 12-16 IR LED targets. The FDMS determines the in-flight deflected wing shapes at a variety of altitudes at Mach 0.9, and the results are compared to the analytically predicted wing-twist distributions. The FDMS data describe the predicted increasing streamwise twist with increasing dynamic pressure and suggest that the streamwise twist is more prevalent at the inboard measurement station than at the wing tip. This hook shape is not represented in the predicted data, and suggestions are given for improving the modeling of the X-29 wing.

Lokos, William A.↗

NASA NTRS1994

Multicomponent Gas Diffusion and an Appropriate Momentum Boundary Condition

Multicomponent gas diffusion is reviewed with particular emphasis on gas flows near solid boundaries-the so-called Kramers-Kistemaker effect. The aim is to derive an appropriate momentum boundary condition which governs many gaseous species diffusing together. The many species' generalization of the traditional single gas condition, either as slip or stick (no-slip), is not obvious, particularly for technologically important cases of lower gas pressures and very dissimilar molecular weight gases. No convincing theoretical case exists for why two gases should interact with solid boundaries equally but in opposite flow directions, such that the total gas flow exactly vanishes. ln this way, the multicomponent no-slip boundary requires careful treatment The approaches discussed here generally adopt a microscopic model for gas-solid contact. The method has the advantage that the mathematics remain tractable and hence experimentally testable. Two new proposals are put forward, the first building in some molecular collision physics, the second drawing on a detailed view of surface diffusion which does not unphysically extrapolate bulk gas properties to govern the adsorbed molecules. The outcome is a better accounting of previously anomalous experiments. Models predict novel slip conditions appearing even for the case of equal molecular weight components. These approaches become particularly significant in view of a conceptual contradiction found to arise in previous derivations of the appropriate boundary conditions. The analogous case of three gases, one of which is uniformly distributed and hence non-diffusing, presents a further refinement which gives unexpected flow reversals near solid boundaries. This case is investigated alone and for aggregating gas species near their condensation point. In addition to predicting new physics, this investigation carries practical implications for controlling vapor diffusion in the growth of crystals used in medical diagnosis (e.g. mercuric iodide) and semiconductors.

Noever, David A.↗

DOE OSTI2020

Sequence-to-sequence neural networks for short-term electrical load forecasting in commercial office buildings

The U.S. power grid is transforming to become smarter, cleaner, and more effi- cient. This is leading to the addition of significant distributed variable renew- able generation. Due to the variable nature of renewable generation, the short- and long-term supply-demand imbalances are less predictable, and conventional approaches to mitigating the imbalance will not be efficient or cost-effective. To address this challenge, transactive control technologies have been proposed which balance energy generation and consumption with market activity and in- frastructural limitations. Transactive control requires the ability of individual end-use loads to express flexibility as a function of a transactive signal (e.g., price). Empirical gray- and black-box models have been widely used to express flexibility, and although these approaches are generally easy to construct and simple to use, they do not capture the non-linear behavior that some end-use loads represent . Machine learning approaches have been proposed to address this limitation. Although deep learning approaches for forecasting end-use loads have been explored, certain aspects of the application of deep models to load forecasting are not well understood. These aspects include how much training data is required, and how models should be structured and trained. To that end, this work explores how to approach applying deep recurrent neural networks to short-term electrical load forecasting with a case study of four commercial office buildings. We identify data requirements for training accurate models of whole building electricity use conditioned on outdoor temperature, provide insight into model hyperparameter sensitivity, and demonstrate how readily models can be generalized to unseen buildings.

Skomski, Elliott↗

DOE OSTI2023

Validation of the Fault Ride-Through Response of a Generic EMT Inverter Model by Laboratory Testing

This paper presents the validation of the fault ride-through response of a large-scale inverter model using laboratory testing of a commercial inverter. First, we present the generic inverter model specifications. The generic inverter control is developed based on the fault ride-through response performance requirements of IEEE Std 2800-2022 for inverter-based resources. Next, we present laboratory tests that emulate voltages at the inverter terminal resulting from balanced and unbalanced faults on the transmission system. The tests are performed on a commercia12.2 MVA battery storage inverter at the U.S. National Renewable Energy Laboratory. Comparisons of the model's response to the laboratory measurements show the generic model presented can predict the controlled response of the commercial equipment. The differences between the model's response and the laboratory measurements during the initial transient at fault inception are discussed.

fault ride-through↗

DOE OSTI2020

Modeling Single and Two-Phase Transport in Thin Porous Layers Using a Composite Continuum-Pore Network Formulation

In this work, a composite continuum-pore network formulation is presented to model single and two-phase transport thin porous layers, such as gas diffusion layers in polymer electrolyte fuel cells (PEFCs) and active electrodes in redox flow batteries (RFBs). The formulation can be integrated into CFD codes, thus combining the ease of implementation of continuum-based modeling and the computational power of pore-network modeling. The composite model includes a control volume (CV) mesh at the layer scale, which embeds a cubic pore network [1,2]. The pore-network model is used to determine analytically local anisotropic effective transport properties (local effective diffusivity and permeability), which are mapped onto the CV mesh to simulate transport in the porous transport layer [3,4]. Good agreement is found between the predicted global effective transport properties (global effective diffusivity and permeability) under dry and wet conditions and previous experimental data reported in the literature for Toray TGP-H series carbon paper. Water saturation distributions are also compared with results obtained using X-ray computed tomography [4]. [1] P.A. García-Salaberri, I.V. Zenyuk, J.T. Gostick, A.Z. Weber, Modeling Gas Diffusion Layer in Polymer Electrolyte Fuel Cells Using a Continuum-Based Pore-Network Formulation, ECS Trans. 97 (2020) 615. [2] P.A. García-Salaberri, Modeling diffusion and convection in thin porous transport layers using a composite continuum-network model: Application to gas diffusion layers in polymer electrolyte fuel cells, Int J. Heat Mass Transf. (2020), submitted. [3] P.A. García-Salaberri, J.T. Gostick, G. Hwang, A.Z. Weber, M. Vera, Effective diffusivity in partially-saturated carbon-fiber gas diffusion layers: Effect of local saturation and application to macroscopic continuum models, J. Power Sources 296 (2015) 440–453. [4] P.A. García-Salaberri, G. Hwang, M. Vera, A.Z. Weber, J.T. Gostick, Effective diffusivity in partially-saturated carbon-fiber gas diffusion layers: Effect of through-plane saturation distribution, Int. J. Heat Mass Transf. 86 (2015) 319–333.

Garcia-Salaberri, Pablo↗

NASA NTRS1989

Long-term exposure to zero-g and the gastro-intestinal tract function

The gastrointestinal tract (GIT) function is described with emphasis placed on its important role to smooth, delay, and modify sudden fluid load stress applied to the fluid distribution control system in the body. Two basic components of the GIT are considered: stomach dynamics, which involves storage, mixing, and discharge of food into the intestine after addition of gastric juices; and absorption of water and electrolytes from the small intestine. A dynamic model of these components is described, along with performance characteristics computed consecutively for one g and zero g conditions. The main impact of the zero g condition appears to be through a change in osmotic driven transport across the gut wall. A dramatic change in transport characteristics is predicted with implication for many body systems (the immune system in particular) during long-term exposure to zero g. Experimental measurements in zero g are needed to evaluate these predictions.

Mccormack, Percial D.↗

DOE OSTI2023

The Influence of Carbon Fiber Composite Specimen Design Parameters on Artificial Lightning Strike Current Dissipation and Material Thermal Damage

Previous artificial lightning strike direct effect research has examined a broad range of specimen design parameters. No works have studied how such specimen design parameters and electrical boundary conditions impact the dissipation of electric current flow through individual plies. This article assesses the influence of carbon fiber composite specimen design parameters (design parameters = specimen size, shape, and stacking sequence) and electrical boundary conditions on the dissipation of current and the spread of damage resulting from Joule heating. Thermal-electric finite element (FE) modelling is used and laboratory scale (<1 m long) and aircraft scale (>1 m long) models are generated in which laminated ply current dissipation is predicted, considering a fixed artificial lightning current waveform. The simulation results establish a positive correlation between the current exiting the specimen from a given ply and the amount of thermal damage in that ply. The results also establish that the distance to ground, from the strike location to the zero potential boundary conditions (ground), is the controlling factor which dictates the electric current dissipation in each ply. Significantly, this distance to ground is dependent on each of the specimen shape, dimensions, stacking sequence, and location of ground boundary conditions. Therefore, it is not possible to decouple current dissipation and damage from specimen design and boundary condition setup. However, it is possible to define a specimen size for a given specimen shape, stacking sequence, and waveform which limit the influence of specimen dimensions on the resulting current distribution and damage. For a rectangular specimen design which appears in literature multiple times, as 100 × 150 mm and with a stacking sequence of [45/0/-45/90] 4s , a specimen design of greater than 300 × 200 mm is required to limit the influence of specimen dimensions on current distribution and damage.

36 MATERIALS SCIENCE↗

NASA NTRS1997

Comparison of OARE Accelerometer Data with Dopant Distribution in Se-Doped GaAs Crystals Grown During USML-1

Experiments were conducted in the crystal growth furnace (CGF) during the first United States Microgravity Laboratory (USML-1), the STS-50 flight of the Space Shuttle Columbia, to determine the segregation behavior of selenium in bulk GaAs in a microgravity environment. After the flight, the selenium-doped GaAs crystals were sectioned, polished, and analyzed to determine the free carrier concentration as a function of position, One of the two crystals initially exhibited an axial concentration profile indicative of diffusion controlled growth, but this profile then changed to that predicted for a complete mixing type growth. An analytical model, proposed by Naumann [R.J. Naumann, J. Crystal Growth 142 (1994) 253], was utilized to predict the maximum allowable microgravity disturbances transverse to the growth direction during the two different translation rates used for each of the experiments. The predicted allowable acceleration levels were 4.86 microgram for the 2.5 micrometers/s furnace translation rate and 38.9 microgram for the 5.0 micrometers/s rate. These predicted values were compared to the Orbital Acceleration Research Experiment (OARE) accelerometer data recorded during the crystal growth periods for these experiments. Based on the analysis of the OARE acceleration data and utilizing the predictions from the analytical model, it is concluded that the change in segregation behavior was not caused by any acceleration events in the microgravity environment.

Moskowitz, Milton E.↗

DOE OSTI2025

Hybrid Energy Management with Real-Time Control of a High-Power EV Charging Site

Decarbonization of transportation systems is driving higher capacity energy storage and faster charging power requirements in electric vehicles (EVs). Given the potential advantages - such as increased efficiency, reduced inverter capacity, and less total cable mass - there is a demand in the industry for more DC distribution for high-power charging (HPC) hubs. However, the cost-effective, adaptive, and robust operation of the DC-coupled HPC hub necessitates a robust site energy management system (SEMS). Validating SEMS operation using a digital twin of an HPC hub in a real-time simulator (RTS) platform is crucial before field deployment. In this study, we propose a hybrid energy management site controller designed to achieve high-level, long-term operational objectives while managing low-level power sharing control between hub assets. We develop a centralized model predictive controller (MPC) to optimize hub operating points and use these points to update the droop parameters of the site energy storage system (ESS). This approach ensures the hub follows an optimal operating point while maintaining the flexibility to respond to load surges. We tested and verified our proposed approach both offline and on a Controller Hardware-in-the-loop (C-HIL) simulation platform integrated with a SEMS framework, demonstrating real-time site operation and validating a cost-effective and robust site controller.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Envisioning urban environments resilient to vector-borne diseases: a protocol to study dengue in Vietnam

Transmitted primarily by Aedes aegypti (Ae. aegypti) and Aedes albopictus (Ae. albopictus), arboviral diseases pose a major global public health threat. Dengue, chikungunya, and zika are increasingly prevalent in Southeast Asia. Among other arboviruses, dengue and zika are becoming more common in Central and South America. Given human encroachment into previously uninhabited, often deforested areas, to provide new housing in regions of population expansion, conceptualizing built urban environments in a novel way is urgently needed to safeguard against the growing climate change-driven threat of vector-borne diseases. By understanding the spread from a One Health perspective, enhanced control and prevention can be achieved. This is particularly important considering that climate change is likely to significantly impact the persistence of ponded water where mosquitoes breed due to increasing temperature and shifting rainfall patterns with regard to magnitude, duration, frequency, and season. Models can incorporate aquatic mosquito stages and adult spatial dynamics when habitats are heterogeneously available, thereby including dispersal and susceptible-exposed-infected-recovered (SEIR) epidemiology. Coupled with human population distribution (density, locations), atmospheric conditions (air temperature, precipitation), and hydrological conditions (soil moisture distribution, ponding persistence in topographic depressions), modeling has improved predictive ability for infection rates. However, it has not informed interventional approaches from an urban environment perspective which considers the role of ponds/lakes that support green spaces, the density of population that enables rapid spread of disease, and varying micro-habitats for various mosquito stages under climate change. Here, for an example of dengue in Vietnam, a preventive and predictive approach to design resilient urban environments is proposed, which uses data from rapidly expanding metropolitan communities to learn continually. This protocol deploys computational approaches including simulation and machine learning/artificial intelligence, underpinned by surveillance and medical data for validation and adaptive learning. Its application may best inform urban planning in low-middle income countries in tropical zones where arboviral pathogens are prevalent.

60 APPLIED LIFE SCIENCES↗