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At least 667 records · Page 37

Towards Improved Decision Making for the Smarter Grid: Geomagnetic Disturbance Implicit Modeling Uncertainty Quantification

Geomagnetic disturbances can greatly disrupt the power grid operation. This is caused by low-frequency changes in the earth’s magnetic field, which upon interaction with the deep earth conductivity induces a changing electric field at the earth’s surface. This in turn induces quasi-direct currents which have the potential to cause protective devices to operate, widespread damage to high-voltage transformers, or voltage collapse due to induced reactive power losses. While these impacts have been known since the 1940s, only recently have standards for GMD response been implemented. Because these standards are heavily based on models, it is important to understand when it is appropriate to make certain modeling assumptions. In this work, implicit modeling uncertainty is quantified for the purpose of enhanced decision making for disturbance impact mitigation. Considering electromagnetic models, modeling assumptions of non-uniform grounding, imbalanced operation, transformer saturation, and geomagnetically induced currents, voltage estimation values are analyzed. Statistical characteristics of modeling uncertainty are obtained by analysis of synthetically generated data. Results statistically characterize geomagnetic disturbances modeling uncertainty, providing an important tool for impact mitigation.

grid analysis↗

Network-Cognizant Model Reduction of Grid-Tied Three-Phase Inverters

Power-electronics inverters are expected to satisfy a significant fraction of system load in next-generation power networks with the growing integration of renewable resources and flexible loads. Typical dynamical models for grid-tied inverters are nonlinear and composed of a large number of states; therefore it is impractical to study systems with many inverters when their full dynamics are retained. In our previous work, we have shown that a system of parallel-connected grid-tied three-phase inverters can be modeled as one aggregated inverter unit with the same structure and state-space dimension as any individual inverter in the system. Here, we extend this result to networks with arbitrary topologies by leveraging a classical aggregation method for coherent synchronous generators in transmission networks, and a linear approximation of the AC power-flow equations to ease computational burden. Numerical simulation results for a prototypical distribution feeder demonstrate the accuracy and computational benefits of the approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

(GO) 2 -SIM: a GCM-oriented ground-observation forward-simulator framework for objective evaluation of cloud and precipitation phase

General circulation model (GCM) evaluation using ground-based observations is complicated by inconsistencies in hydrometeor and phase definitions. Here we describe (GO) 2 -SIM, a forward simulator designed for objective hydrometeor-phase evaluation, and assess its performance over the North Slope of Alaska using a 1-year GCM simulation. For uncertainty assessment, 18 empirical relationships are used to convert model grid-average hydrometeor (liquid and ice, cloud, and precipitation) water contents to zenith polarimetric micropulse lidar and Ka-band Doppler radar measurements, producing an ensemble of 576 forward-simulation realizations. Sensor limitations are represented in forward space to objectively remove from consideration model grid cells with undetectable hydrometeor mixing ratios, some of which may correspond to numerical noise. Phase classification in forward space is complicated by the inability of sensors to measure ice and liquid signals distinctly. However, signatures exist in lidar–radar space such that thresholds on observables can be objectively estimated and related to hydrometeor phase. The proposed phase-classification technique leads to misclassification in fewer than 8 % of hydrometeor-containing grid cells. Such misclassifications arise because, while the radar is capable of detecting mixed-phase conditions, it can mistake water- for ice-dominated layers. However, applying the same classification algorithm to forward-simulated and observed fields should generate hydrometeor-phase statistics with similar uncertainty. Alternatively, choosing to disregard how sensors define hydrometeor phase leads to frequency of occurrence discrepancies of up to 40 %. So, while hydrometeor-phase maps determined in forward space are very different from model reality they capture the information sensors can provide and thereby enable objective model evaluation.

54 ENVIRONMENTAL SCIENCES↗

(GO)2-SIM: a GCM-Oriented Ground-Observation Forward-Simulator Framework for Objective Evaluation of Cloud and Precipitation Phase

General circulation model (GCM) evaluation using ground-based observations is complicated by inconsistencies in hydrometeor and phase definitions. Here we describe (GO)2-SIM, a forward simulator designed for objective hydrometeor-phase evaluation, and assess its performance over the North Slope of Alaska using a 1-year GCM simulation. For uncertainty assessment, 18 empirical relationships are used to convert model grid-average hydrometeor (liquid and ice, cloud, and precipitation) water contents to zenith polarimetric micropulse lidar and Ka-band Doppler radar measurements, producing an ensemble of 576 forward-simulation realizations. Sensor limitations are represented in forward space to objectively remove from consideration model grid cells with undetectable hydrometeor mixing ratios, some of which may correspond to numerical noise.Phase classification in forward space is complicated by the inability of sensors to measure ice and liquid signals distinctly. However, signatures exist in lidar–radar space such that thresholds on observables can be objectively estimated and related to hydrometeor phase. The proposed phase-classification technique leads to misclassification in fewer than 8% of hydrometeor-containing grid cells. Such misclassifications arise because, while the radar is capable of detecting mixed-phase conditions, it can mistake water- for ice-dominated layers. However, applying the same classification algorithm to forward-simulated and observed fields should generate hydrometeor-phase statistics with similar uncertainty. Alternatively, choosing to disregard how sensors define hydrometeor phase leads to frequency of occurrence discrepancies of up to 40%. So, while hydrometeor-phase maps determined in forward space are very different from model "reality" they capture the information sensors can provide and thereby enable objective model evaluation.

Lamer, K.↗

Evaluation of grid generation technologies from an applied perspective

An analysis of the grid generation process from the point of view of an applied CFD engineer is given. Issues addressed include geometric modeling, structured grid generation, unstructured grid generation, hybrid grid generation and use of virtual parts libraries in large parametric analysis projects. The analysis is geared towards comparing the effective turn around time for specific grid generation and CFD projects. The conclusion was made that a single grid generation methodology is not universally suited for all CFD applications due to both limitations in grid generation and flow solver technology. A new geometric modeling and grid generation tool, CFD-GEOM, is introduced to effectively integrate the geometric modeling process to the various grid generation methodologies including structured, unstructured, and hybrid procedures. The full integration of the geometric modeling and grid generation allows implementation of extremely efficient updating procedures, a necessary requirement for large parametric analysis projects. The concept of using virtual parts libraries in conjunction with hybrid grids for large parametric analysis projects is also introduced to improve the efficiency of the applied CFD engineer.

Hufford, Gary S.↗

Valuation of Hydrogen Technology on the Electric Grid Using Production Cost Modeling: Cooperative Research and Development Final Report, CRADA Number CRD-18-00736

This research project will estimate the value to the United States electric grid of deploying hydrogen technology (such as electrolyzers and hydrogen-fueled generation) under projected conditions of high renewable penetration. The analysis will advance the state of the art in systems-level cost-benefit analysis of hydrogen technology for the electric grid by incorporating production cost modeling results in the analysis. Large-scale grid simulation tools will be used to evaluate total system production cost and grid operation when hydrogen technology is deployed for applications such as energy storage and demand response. Scenarios will include one or more future grid mixes in the Western Interconnect (WI) with a high proportion of intermittent renewables. Electric Power Research Institute (EPRI) will work with four utility companies to refine scenarios. Results of the analysis will include comparing the net cost of hydrogen to other technologies for long duration storage, and of power-to-gas (P2G) scenarios including merchant hydrogen sale and hydrogen-fueled generation.

08 HYDROGEN↗

Sparse-grid discontinuous Galerkin methods for the Vlasov–Poisson–Lenard–Bernstein model

Sparse-grid methods have recently gained interest in reducing the computational cost of solving high-dimensional kinetic equations. In this paper, we construct adaptive and hybrid sparse-grid methods for the Vlasov–Poisson–Lenard–Bernstein (VPLB) model. This model has applications to plasma physics and is simulated in two reduced geometries: a 0x3v space homogeneous geometry and a 1x3v slab geometry. Here we use the discontinuous Galerkin (DG) method as a base discretization due to its high-order accuracy and ability to preserve important structural properties of partial differential equations. We utilize a multiwavelet basis expansion to determine the sparse-grid basis and the adaptive mesh criteria. We analyze the proposed sparse-grid methods on a suite of three test problems by computing the savings afforded by sparse-grids in comparison to standard solutions of the DG method. The results are obtained using the adaptive sparse-grid discretization library ASGarD.

97 MATHEMATICS AND COMPUTING↗

Achieving sustainable irrigation water withdrawals: global impacts on food security and land use

Unsustainable water use challenges the capacity of water resources to ensure food security and continued growth of the economy. Adaptation policies targeting future water security can easily overlook its interaction with other sustainability metrics and unanticipated local responses to the larger-scale policy interventions. Using a global partial equilibrium grid-resolving model SIMPLE-G, and coupling it with the global Water Balance Model, we simulate the consequences of reducing unsustainable irrigation for food security, land use change, and terrestrial carbon. A variety of future (2050) scenarios are considered that interact irrigation productivity with two policy interventions— inter-basin water transfers and international commodity market integration. We find that pursuing sustainable irrigation may erode other development and environmental goals due to higher food prices and cropland expansion. This results in over 800,000 more undernourished people and 0.87 GtC additional emissions. Faster total factor productivity growth in irrigated sectors will encourage more aggressive irrigation water use in the basins where irrigation vulnerability is expected to be reduced by inter-basin water transfer. By allowing for a systematic comparison of these alternative adaptations to future irrigation vulnerability, the global gridded modeling approach offers unique insights into the multiscale nature of the water scarcity challenge.

54 ENVIRONMENTAL SCIENCES↗

Reynolds-Averaged Navier-Stokes Simulations of Two Partial-Span Flap Wing Experiments

Structured Reynolds Averaged Navier-Stokes simulations of two partial-span flap wing experiments were performed. The high-lift aerodynamic and aeroacoustic wind-tunnel experiments were conducted at both the NASA Ames 7-by 10-Foot Wind Tunnel and at the NASA Langley Quiet Flow Facility. The purpose of these tests was to accurately document the acoustic and aerodynamic characteristics associated with the principle airframe noise sources, including flap side-edge noise. Specific measurements were taken that can be used to validate analytic and computational models of the noise sources and associated aerodynamic for configurations and conditions approximating flight for transport aircraft. The numerical results are used to both calibrate a widely used CFD code, CFL3D, and to obtain details of flap side-edge flow features not discernible from experimental observations. Both experimental set-ups were numerically modeled by using multiple block structured grids. Various turbulence models, grid block-interface interaction methods and grid topologies were implemented. Numerical results of both simulations are in excellent agreement with experimental measurements and flow visualization observations. The flow field in the flap-edge region was adequately resolved to discern some crucial information about the flow physics and to substantiate the merger of the two vortical structures. As a result of these investigations, airframe noise modelers have proposed various simplified models which use the results obtained from the steady-state computations as input.

Takalluk, M. A.↗

Constraints and Potentials of Future Irrigation Water Availability on Agricultural Production Under Climate Change

Freshwater availability is relevant to almost all socioeconomic and environmental impacts of climate and demographic change and their implications for sustainability. We compare ensembles of water supply and demand projections driven by ensemble output from five global climate models. Our results suggest reasons for concern. Direct climate impacts to maize, soybean, wheat, and rice involve losses of 400–2,600 Pcal (8–43% of present-day total). Freshwater limitations in some heavily irrigated regions could necessitate reversion of 20–60 Mha of cropland from irrigated to rainfed management, and a further loss of 600–2,900 Pcal. Freshwater abundance in other regions could help ameliorate these losses, but substantial investment in infrastructure would be required. We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400–1,400 Pcal (8–24% of present-day total) when CO2 fertilization effects are accounted for or 1,400–2,600 Pcal (24–43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20–60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600–2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required.

agriculture↗

1.2.2.404 – Improving the Representation of Hydropower in Production Cost Models

This project's goal is to improve hydropower's representation in power system models by actively coupling river basin (hydrologic) models with grid operations (production cost) models. Near term, this work provides a foundation that allows improved available flexibility and operational constraints representation. Longer term, the work will provide a template that can be used by commercial production cost modeling software vendors to capture the nuances of hydropower operations in their software offerings.

HYDRO ENERGY↗

Power Grid Planning with Higher Renewable Share

Power grid planning with a higher renewable share got worldwide attention since the declining cost of renewable energy technologies and greenhouse gas reduction goals continue to drive a transition to a cleaner power grid. Energy professionals from developing countries working to achieve renewable power goals want to learn about NREL's state-of-the-art research efforts in renewable power and power grid planning. Supporting these efforts, the United States Energy Association, Female Leaders in Energy initiative facilitates mid-career female energy professionals from South East Asia to learn from energy professionals from the USA. This presentation gives an overview of NREL scientific research studies on power grid planning with a high renewable share to mid-career female energy professionals.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗

A Service Oriented Architecture for Exploring High Performance Distributed Power Models

Power grids are increasingly incorporating high quality, high throughput sensor devices inside power distribution networks. These devices are driving an unprecedented increase in the volume and rate of available information. The real-time requirements for handling this data are beyond the capacity of conventional power models running in central utilities. Hence, we are exploring distributed power models deployed at the regional scale. The connection of these models for a larger geographic region is supported by a distributed system architecture. This architecture is built in a service oriented style, whereby distributed power models running on high performance clusters are exposed as services. Each service is semantically annotated and therefore can be discovered through a service catalog and composed into workflows. The overall architecture has been implemented as an integrated workflow environment useful for power researchers to explore newly developed distributed power models.

Service oriented architecture, high performance co↗

A Library of ATMO Forward Model Transmission Spectra for Hot Jupiter Exoplanets

We present a grid of forward model transmission spectra, adopting an isothermal temperature-pressure profile, alongside corresponding equilibrium chemical abundances for 117 observationally significant hot exoplanets (equilibrium temperatures of 547-2710 K). This model grid has been developed using a 1D radiative-convective-chemical equilibrium model termed ATMO, with up-to-date high-temperature opacities. We present an interpretation of observations of 10 exoplanets, including best-fitting parameters and X(exp 2) maps. In agreement with previous works, we find a continuum from clear to hazy/cloudy atmospheres for this sample of hot Jupiters. The data for all the 10 planets are consistent with subsolar to solar C/O ratio, 0.005 to 10 times solar metallicity and water rather than methane-dominated infrared spectra. We then explore the range of simulated atmospheric spectra for different exoplanets, based on characteristics such as temperature, metallicity, C/O ratio, haziness and cloudiness. We find a transition value for the metallicity between 10 and 50 times solar, which leads to substantial changes in the transmission spectra. We also find a transition value of C/O ratio, from water to carbon species dominated infrared spectra, as found by previous works, revealing a temperature dependence of this transition point ranging from approximately 0.56 to approximately 1-1.3 for equilibrium temperatures from approximately 900 to approximately 2600 K. We highlight the potential of the spectral features of HCN and C2H2 to constrain the metallicities and C/O ratios of planets, using James Webb Space Telescope (JWST) observations. Finally, our entire grid (approximately 460 000 simulations) is publicly available and can be used directly with the JWST simulator PandExo for planning observations.

techniques: spectroscopic – planets and satellit↗

Modeling Primary Frequency Response for Grid Studies

For the electric power grid, maintaining nearly constant frequency is important measure of system reliability and stability. Primary frequency response (PFR) is one of the important reserve services used by grid operators to uphold steady frequency. Modeling PFR is historically rare in grid integration and planning studies, but could become more importantly with greater deployment of non-synchronous generators. In this work, we illustrate how a PFR constraint can be implemented into production cost models, which are a key component of grid planning studies. We also discuss the complexities and nuances associated with PFR modeling and provide results of a case study implementing PFR in a section of the western U.S. power grid.

14 SOLAR ENERGY↗

Distribution System Dataset Generator for AI Applications [SWR-24-75]

This software is a simple, light-weight python package to generate pytorch compatible machine learning graph dataset representing electric power distribution system. User is able to use these graph datasets to test their graph generation artificial intelligence (AI) models, link prediction AI models, graph classification AI models and so much more. This package uses grid-data-models (https://github.com/NREL-Distribution-Suites/grid-data-models) as input data format for power distribution system. NREL-Ditto (https://github.com/NREL-Distribution-Suites/ditto) tool can be leveraged to transform popular distribution system file formats such as opendss, cyme and synergi to grid-data-models.

Duwadi, Kapil↗