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DOE OSTI2019

India National Gas Hydrate Program Expedition 02 Summary of Scientific Results: Gas Hydrate Systems Along the Eastern Continental Margin of India

The India National Gas Hydrate Program Expedition 02 (NGHP-02) discovered gas hydrate at high saturation in sand reservoirs at several sites in the deepwater Bay of Bengal. To assess the potential response of those deposits to scientific depressurization experiments, comprehensive geologic models were constructed to enable numerical simulation for two sites. Both sites (NGHP-02-09 and NGHP-02-16) feature thick sequences of thinly-interbedded reservoir and non-reservoir facies at sub-seafloor depths less than 300m and sub-sea depths of 2400m or more. These settings pose significant challenges to current modeling capabilities. First, the thinly-interbedded reservoir architecture complicates the determination of basic reservoir parameters from both log and core data due to measurement resolution issues. Secondly, the fine scale variation in sediment properties imparts great contrasts in key parameters over very short distances, creating high gradients at multiple scales and varying orientations that necessitate careful design of high-definition simulation grids. Thirdly, the deposits include internal sources of water, as well as a range of complex boundary conditions, including variable permeability within the overlying mud-rich “seals,” that complicate reservoir depressurization. Lastly, because of the unique combination of great water depth and relatively shallow sub-seafloor depth: models designed to maximize the dissociation rate impose large pressure drawdowns on relatively low-strength sediments. This condition renders the proper evaluation and integration of the geomechanical response to hydrate dissociation critical. In this report, we review the history of gas hydrate reservoir simulation, discuss methods for creating geologic input models, and summarize the key findings and implications of the collaborative NGHP-02 numerical simulation effort. Together, the studies confirm the viability of the modeled accumulations for scientific testing and identify key challenges related to the selection of specific test sites and the design of test wells.

Collett, Tim↗

DOE OSTI2018

A plasma–vacuum interface tracking algorithm for magnetohydrodynamic simulations of coaxial plasma accelerators

The resistive Magneto-hydrodynamic (MHD) model describes the behavior of a strongly ionized plasma in the presence of external electric and magnetic fields. For problems involving the plasma with an open boundary to very low pressure/vacuum regions, the continuum assumption is no longer valid in the entire domain of interest. For example, this is seen in a plasma accelerator where a dense plasma expands into a vacuum background. A common practice to deal with this issue is to assign small values of density and pressure to the vacuum regions and proceed to solve the continuum based MHD equations throughout the domain. We show that this approach fails to produce solutions consistent with the physics of the problem and can give rise to unacceptable artifacts such as spurious shocks. Here, we develop a plasma–vacuum interface tracking approach to mitigate this problem. The plasma–vacuum interface is tracked in a physically consistent manner and the MHD equations are solved only in the regions that contain the plasma. The interface tracking is achieved using a face-flux formulation derived from the theoretical solution to a 1D free expansion problem. Coupled with a threshold based approach, the interface tracking is implemented for both explicit and implicit time stepping frameworks on generalized unstructured grids. Simulations of magnetized thermal plasma jets expanding into a vacuum background indicate plume profiles devoid of the unphysical shock obtained using the small background density approach. In the context of resistive MHD simulations, the interface tracking approach overcomes the numerical stiffness induced by specifying a large background resistivity in the vacuum regions, resulting in significant wall-clock time gains.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

IM3 GO WEST Parameter Search Dataset

GO WEST is an open-source power grid modeling framework for U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It is developed to address weather and water dynamics, and associated vulnerabilities in this bulk power system. It covers 28 balancing authorities (BA) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of U.S. Western Interconnection created by Texas A&M University. Users can try and select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. Therefore, GO WEST can help researchers to strike a balance between model fidelity (i.e. accuracy) and computational complexity (i.e. runtime). This dataset includes model inputs and outputs from 600 model versions for each 2019, 2020, and 2021. The folder naming convention is as follows: Exp{Number of Nodes}_{Mathematical Formulation}_{Transmission Line Limit Scaling Factor in MW}_{Hurdle Rate Scaling Factor in %}_{Year}. Linear programming is designated with "simple" label whereas mixed-integer linear programming is designated with "coal" label. For example, "Exp100_simple_1000_50_2019" folder contains inputs and outputs from 2019 model version with 100 nodes, linear programming, +1000 MW transmission line limit scaling factor, and +50% hurdle rate scaling factor. GO WEST GitHub repository hosts all raw datasets, processing scripts, and model scripts. Please refer to the README file for a detailed description of the included files.

Economics↗

DOE OSTI2015

Operational Benefits of Meeting California's Energy Storage Targets

In October 2013, the California Public Utilities Commission (CPUC) finalized procurement targets and other requirements to its jurisdictional utilities for a minimum of 1,325 MW of 'viable and cost-effective' energy storage systems by 2020. The goal of this study is to explore several aspects of grid operations in California and the Western Interconnection resulting from meeting the CPUC storage targets. We perform this analysis using a set of databases and grid simulation tools developed and implemented by the CPUC, the California Independent System Operator (CAISO), and the California Energy Commission (CEC) for the CPUC's Long-term Procurement Plan (LTPP). The 2014 version of this database contains information about generators, storage, transmission, and electrical demand, for California in the year 2024 for both 33% and 40% renewable energy portfolios. We examine the value of various services provided by energy storage in these scenarios. Sensitivities were performed relating to the services energy storage can provide, the capacity and duration of storage devices, export limitations, and negative price floor variations. Results show that a storage portfolio, as outlined by the CPUC, can reduce curtailment and system-wide production costs for 33% and 40% renewable scenarios. A storage device that can participate in energy and ancillary service markets provides the grid with the greatest benefit; the mandated storage requirement of 1,325 MW was estimated to reduce the total cost of production by about 78 million per year in the 33% scenario and 144 million per year in the 40% scenario. Much of this value is derived from the avoided start and stop costs of thermal generators and provision of ancillary services. A device on the 2024 California grid and participating in only ancillary service markets can provide the system with over 90% of the value as the energy and ancillary service device. The analysis points to the challenge of new storage providing regulation reserve, as the added storage could provide about 75% of the regulation up requirement for all of California, which would likely greatly reduce regulation prices and potential revenue. The addition of storage in California decreases renewable curtailment, particularly in the 40% RPS case. Following previous analysis, storage has a mixed impact on emissions, generally reducing emissions, but also creating additional incentives for increased emissions from out-of-state coal generations. Overall, storage shows significant system cost savings, but analysis also points to additional challenges associated with full valuation of energy storage, including capturing the operational benefits calculated here, but also recovering additional benefits associated avoided generation, transmission, and distribution capacity, and avoided losses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

A Methodology for Evaluating Operator Usage of Machine Learning Recommendations for Power Grid Contingency Analysis

This work presents the application of a methodology to measure domain expert trust and workload, elicit feedback, and understand the technological usability and impact when a machine learning assistant is introduced into contingency analysis for real-time power grid simulation. The goal of this framework is to rapidly collect and analyze a broad variety of human factors data in order to accelerate the development and evaluation loop for deploying machine learning applications. We describe our methodology and analysis, and we discuss insights gained from a pilot participant about the current usability state of an early technology readiness level (TRL) artificial neural network (ANN) recommender.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

A moment-conserving discontinuous Galerkin representation of the relativistic Maxwellian distribution

Kinetic simulations of relativistic gases and plasmas are critical for understanding diverse astrophysical and terrestrial systems, but the accurate construction of the relativistic Maxwellian, the Maxwell–Jüttner distribution, on a discrete simulation grid is challenging. Difficulties arise from the finite velocity bounds of the domain, which may not capture the entire distribution function, as well as errors introduced by projecting the function onto a discrete grid. Here, we present a novel scheme for iteratively correcting the moments of the projected distribution applicable to all grid-based discretizations of the relativistic kinetic equation. In addition, we describe how to compute the needed nonlinear quantities, such as Lorentz boost factors, in a discontinuous Galerkin scheme through a combination of numerical quadrature and weak operations. The resulting method accurately captures the distribution function and ensures that the moments match the desired values to machine precision.

astrophysical plasmas↗

DOE OSTI2019

Novel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model

Leaf phenology in the humid tropics largely regulates the seasonality of forest carbon and water exchange. However, it is inadequately represented in most global land surface models due to limited understanding of its controls. Based on intensive field studies at four Amazonian evergreen forests, we propose a novel, quantitative representation of tropical forest leaf phenology, which links multiple environmental variables with the seasonality of new leaf production and old leaf litterfall. The new phenology simulates higher rates of leaf turnover (new leaves replacing old leaves) in dry seasons with more sunlight, which is then implemented in ORCHIDEE, together with recent findings of ontogeny-associated photosynthetic capacity, and is evaluated against ground-based measurements of leaf phenology (canopy leaf area index and litterfall), eddy covariance fluxes (photosynthesis and latent heat), and carbon allocations from field observations. Results show the periodical cycles of solar radiation and vapor pressure deficit are the two most important environmental variables that are empirically related to new leaf production and old leaf abscission in tropical evergreen forests. The model with new representation of leaf phenology captures the seasonality of canopy photosynthesis at three out of four sites, as well as the seasonality of litterfall, latent heat, and light use efficiency of photosynthesis at all tested sites, and improves the seasonality of carbon allocations to leaves, roots, and sapwoods. This study advances understanding of the environmental controls on tropical leaf phenology and offers an improved modeling tool for gridded simulations of interannual CO 2 and water fluxes in the tropics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

An Analysis of Concentrating Solar Power with Thermal Energy Storage in a California 33% Renewable Scenario (Report Summary) (Presentation)

This analysis evaluates CSP with TES in a scenario where California derives 33% of its electricity from renewable energy sources. It uses a commercial grid simulation tool to examine the avoided operational and capacity costs associated with CSP and compares this value to PV and a baseload generation with constant output. Overall, the analysis demonstrates several properties of dispatchable CSP, including the flexibility to generate during periods of high value and avoid generation during periods of lower value. Of note in this analysis is the fact that significant amount of operational value is derived from the provision of reserves in the case where CSP is allowed to provide these services. This analysis also indicates that the 'optimal' configuration of CSP could vary as a function of renewable penetration, and each configuration will need to be evaluated in terms of its ability to provide dispatchable energy, reserves, and firm capacity. The model can be used to investigate additional scenarios involving alternative technology options and generation mixes, applying these scenarios within California or in other regions of interest.

14 SOLAR ENERGY↗

DOE OSTI2013

Analysis of Concentrating Solar Power with Thermal Energy Storage in a California 33% Renewable Scenario

14 SOLAR ENERGY↗

NASA NTRS2005

Higher Order Chemistry Models in the CFD Simulation of Laser-Ablated Carbon Plumes

Production of single-walled carbon nanotubes (SWNT) has taken place for a number of years and by a variety of methods such-as laser ablation, chemical vapor deposition, and arc-jet ablation. Yet, little is actually understood about the exact chemical kinetics and processes that occur in SWNT formation. In recent time, NASA Johnson Space Center has devoted a considerable effort to the experimental evaluation of the laser ablation production process for SWNT originally developed at Rice University. To fully understand the nature of the laser ablation process it is necessary to understand the development of the carbon plume dynamics within the laser ablation oven. The present work is a continuation of previous studies into the efforts to model plume dynamics using computational fluid dynamics (CFD). The ultimate goal of the work is to improve understanding of the laser ablation process, and through that improved understanding, refine the laser ablation production of SWNT. Fig. 1 shows a basic schematic of the laser-ablation oven at NASA-JSC. Construction of the facility is simple in concept. Two concentric quartz tubes of 1.5 mm thickness form the inner and outer tubes with inside diameters of 2.2 and 5.08 cm respectively. At one end of the inner tube are located two 60 Hz pulsed lasers operating at 1064 nm and 532 nm wavelength with beam diameters of 5 mm aligned coaxially with the longitudinal axis of the inner quartz tube. For standard nanotube production runs, a 10 ns 532 nm pulse is followed 50 ns later by a 10 ns 1064 nm pulse. Each pulse is of 300 mJ energy. A target of carbon graphite with approximately 1% nickel and cobalt catalysts is located at the other end of the inner quartz tube. In the ordinary processing of SWNT, a base flow of 100 sccm of argon is maintained from the laser location and exits past the carbon target at a pressure of 66.7 kPa. These conditions yield a baseline mass flow through the chamber of 2.723x10(exp -6)kg/s of argon. The whole oven facility is heated to a temperature of 1473 K prior to nanotube production runs. Upon laser irradiation, part of the carbon target ablates immediately and forms a carbon vapor plume that penetrates into the argon base flow towards the laser initially at supersonic velocities. In the previous studies either a single carbon species, C3, was used to model the plume development, or a simplified 11 species carbon model reduced down from the Krestinin and Moravsky model for full fullerene chemistry was used. While both of these options yielded significant results, it was felt that the actual chemistry occ&g in the carbon plume might have a greater affect on the plume than assumed. Indeed, in the earlier attempts at modeling the carbon plume, several thermophysical characteristics could never be matched to experimental observations of plume development - mainly the propagation distance of the plume itself. In the present study, two additional chemistry models will be used to duplicate the previous studies simulations of the carbon plume. The first chemistry model used in this study is again a reduced form of the Krestinin and Moravsky rates. However the highest order carbon species allowed has been increased from C6 to C30 - therefore allowing the simulation of up to a half of the standard C60 fullerene. The second chemistry model investigated is a reduced form of a full carbon nanotube model developed at NASA-JSC. The C30 studies have already been accomplished at the present time, and the reduced SWNT model studies are currently underway. To pursue the current study, one sacrifice had to be made in that the simulation grid spacing had to be increased from 0.5 mm spacing to 1 mm spacing for the sake of computational efficiency since computational effort is proportional to the square of the number of grid points multiplied by the number of species considered. propagation that is far more in line with the experimental results observed by Puretzky et al as shown in Fig. 2. e C6 studies had yielded a far greater propagation in previous studies. In addition, chemical species development with the C30 model indicates that many higher order carbon species are produced outside of the plume proper (indicated by plotting contours of the background argon concentrations in Fig. 3) - this result was not observed in previous studies. In fact, some species primarily occurred outside of the plume itself - as shown for C27 in Fig. 4 when it is compared to Fig. 3. It could be asserted that this has occurred because all of the C27 in the plume had already been consumed in the formation of C30, but this does not seem to be indicated over time. Several other factors that arose in the previous studies have also been made more clear by the use of the higher order chemical models - one being that the use of c6 as an indicator species was mistaken. C6 is the only carbon species in the previous studies that was not injected into the flowfield as a boundary condition; it was therefore hoped that this species would provide insight into the formation of higher order carbon species for comparison to full SWNT production. But, when the plot of total mass in the plume is examined on a species by species basis in Fig. 5, it is seen that Cg was a fairly insignificant contributor to the total carbon mass in the plume and would not provide information on higher order carbon formation. the thermophysical characteristics of the carbon plume as well as simulate the carbon plume using the reduced SWNT model to provide an even better simulation of full chemistry effects upon plume propagation.

Scott, C. D.↗

DOE OSTI2020

Accelerating geostatistical modeling using geostatistics-informed machine Learning

Ordinary Kriging (OK) is a popular geostatistical algorithm for spatial interpolation and estimation. The computational complexity of OK changes quadratically and cubically for memory and speed, respectively, given the number of data. Therefore, it is computationally intensive and also challenging to process a large set of data, especially in three-dimensional (3D) cases. This paper develops a geostatistics-informed machine learning (GIML) model to improve the efficiency of OK by reducing the number of points required to be estimated using OK. Specifically, only a very few of the unknown points are estimated by OK to get the weights and estimations, which are used as the training dataset. Moreover, the governing equations of OK are used to guide our proposed machine learning to better reproduce the spatial distributions. Our results show that the proposed GIML can reduce the computational time of OK by at least one order of magnitude. The effectiveness of the GIML is evaluated and compared using a 2D case. Furthermore, we demonstrate its efficiency and robustness by considering a different number of training samples on various 3D simulation grids.

58 GEOSCIENCES↗

DOE OSTI2019

Modeling Analysis of the Swell and Wind-Sea Climate in the Salish Sea

Accurate model hindcast of wave climate in complex estuarine systems is challenging because high-resolution wave model and wind forcing are required. In this study, a modeling approach using the unstructured-grid Simulating WAves Nearshore and wind product from a high-resolution regional Weather Research and Forecasting hindcast was used to simulate the swell and wind-sea climate in the Salish Sea, a large estuary with many interconnected waterways on the Pacific Northwest coast of North America. The model hindcast was validated with observed data at four wave buoys in the Salish Sea. Spatial distribution and seasonal variations of wave climate in the Salish Sea were analyzed. Of the three major basins in the Salish Sea, the Strait of Juan de Fuca has the largest waves and is dominated by swells propagated from the Pacific Ocean. Significant wave heights in the Strait of Georgia have spatial and seasonal distribution patterns similar to those found in the Strait of Juan de Fuca. Waves in Puget Sound are small and primarily dominated by the wind-sea climate. Strong seasonal variations are observed in the Strait of Juan de Fuca and Strait of Georgia, but there is little seasonality of wave climate in Puget Sound. The high-resolution wave hindcast conducted in this study provides a comprehensive and important data set for better understanding the role of wave climate in coastal processes and natural hazards assessment in the Salish Sea.

wave climate, salish sea, modeling, swell, sea sta↗

DOE OSTI2021

Wave resource characterization at regional and nearshore scales for the U.S. Alaska coast based on a 32-year high-resolution hindcast

A wave resource characterization was performed for the southern coast of Alaska based on a 32-year hindcast covering the period from 1979 to 2010. The characterization closely followed International Electrotechnical Commission (IEC) Technical Specifications. An unstructured-grid Simulating WAves Nearshore (SWAN) model, which had an approximate spatial resolution of 300 m within 30 km from the nearest shoreline, was developed. Additionally, extensive model validation and error characterization was performed. The model was found to perform well with an average absolute percent error of 8.6% in significant wave height, averaged over 18 buoys. Statistics for the six IEC wave resource parameters were calculated and aggregated at 20 km from shore to quantify the incident wave power and its variability at a regional scale. The southern coast of the Aleutian Archipelago was found to have the most available wave energy in the region. A nearshore resource assessment was performed by evaluating resource hotspots located 1 km from shore. More than 900 nearshore stations had an Optimum Hotspot Identifier value of 5 (kW/m) at diverse water depths, thereby positioning Alaska as a promising location for wave energy development.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region

Fine particulate matter (PM 2.5 ) is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM 2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM 2.5 , and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM 2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM 2.5 -attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM 2.5 (>95 µg/m 3 ). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM 2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sources in South Asia.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2020

Selective bond formation triggered by short optical pulses: quantum dynamics of a four-center ring closure

Here we report bond formation induced by an ultrashort UV pulse. The photochemical process is described by quantum dynamics as coherent electronic and nuclear motions during the ultrashort pulse induced ring closure of norbornadiene to quadricyclane. Norbornadiene consists of two ethylene moieties connected by a rigid (CH 2 ) 3 bridge. Upon photoexcitation, two new sigma bonds are formed, resulting in the closure of a four-atom ring. As a medium-sized polyatomic molecule, norbornadiene exhibits a high density of strongly coupled electronic states from about 6 eV above the ground state. We report on inducing the formation of the new bonds using a short femtosecond UV pulse to pump a non-equilibrium electronic density in the open form that evolves towards the closed ring form. As the coherent electronic-nuclear coupled dynamics unfold, the excited states change character through non-adiabatic interactions and become valence states for the two new C–C bonds of quadricyclane. Our three-dimensional fully quantum dynamical grid simulations during the first 200 fs show that short UV pulses of different polarization initiate markedly different initial non-equilibrium electronic densities that follow different dynamical paths to the S 0 /S 1 conical intersection. They lead to different initial relative yields of quadricyclane, thereby opening the way to controlling bond-making with attopulses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

A NEW DENSITY VARIANCE-MACH NUMBER RELATION FOR SUBSONIC AND SUPERSONIC ISOTHERMAL TURBULENCE

The probability density function of the gas density in subsonic and supersonic, isothermal, driven turbulence is analyzed using a systematic set of hydrodynamical grid simulations with resolutions of up to 1024{sup 3} cells. We perform a series of numerical experiments with root-mean-square (rms) Mach number M ranging from the nearly incompressible, subsonic (M=0.1) to the highly compressible, supersonic (M=15) regime. We study the influence of two extreme cases for the driving mechanism by applying a purely solenoidal (divergence-free) and a purely compressive (curl-free) forcing field to drive the turbulence. We find that our measurements fit the linear relation between the rms Mach number and the standard deviation (std. dev.) of the density distribution in a wide range of Mach numbers, where the proportionality constant depends on the type of forcing. In addition, we propose a new linear relation between the std. dev. of the density distribution {sigma}{sub {rho}} and that of the velocity in compressible modes, i.e., the compressible component of the rms Mach number, M{sub comp}. In this relation the influence of the forcing is significantly reduced, suggesting a linear relation between {sigma}{sub {rho}} and M{sub comp}, independent of the forcing, and ranging from the subsonic to the supersonic regime.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Divertor leg filaments in NSTX-U

This study presents the first observation of divertor localized turbulence in the NSTX-Upgrade spherical tokamak. Previous work in NSTX discharges described fluctuations on the divertor target due to blobs generated on the low field side midplane. In the region that shows disconnection from upstream turbulence (private flux region and proximity of the strike point), divertor-localized fluctuations are observed via imaging of C III and D-α emission in diverted L-mode discharges and are characterized in this paper. Field-aligned filaments connected to the divertor target plate are radially localized at the separatrix on the outer divertor leg and in the private flux region on the inner divertor leg. These are limited to the region below the X-point with fluctuation levels up to 10%–20%. The filaments have comparable poloidal and radial correlation lengths (10–100 ion gyroradii ρ i ) and parallel correlation lengths of several meters. Toroidal mode numbers are in the range of 10–30 and 2–10 for outer and inner leg filaments. The poloidal motion of outer leg filaments has the same direction and comparable magnitude to advection due to E x B drift calculated by the multi-fluid edge transport code UEDGE with inclusion of cross field drifts. Disconnection between inner and outer leg filaments as well as the absence of correlation with upstream turbulence support the hypothesis of X-point disconnection for divertor leg filaments. Simulations with the ArbiTER linear eigenvalue solver and a resistive-balooning model were performed with a simulation grid limited to the divertor legs. Instabilities localized to the bad curvature side of the divertor legs were observed, in qualitative agreement with the experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2010

PMU Placement for Enhancing Dynamic Observability of a Power Grid

Power grids are operated in an increasingly complicated environment. However, operators lack effective and accurate tools for real-time monitoring and control of power systems. The U.S. Department of Energy, along with several utilities and system operators, is making a major $108 million investment in the Western Interconnection for phasor measurement unit (PMU) installation and phasor application development. This phasor measurement network opens up many opportunities for the estimation and prediction of power system states in real time, which enable operators to evaluate the system dynamic security in advance and allow them more time to respond to disturbances. Kalman filter based dynamic state estimation offers a solution suitable for this purpose. Our work indicates that the performance of Kalman filters in dynamic state estimation would degrade if PMU measurements cannot adequately capture the system dynamics. This paper develops a framework to identify how to place PMUs to improve dynamic observability of the power grid. Simulation results validate the concept, and the guidelines for PMU placement are derived.

24 POWER TRANSMISSION AND DISTRIBUTION↗