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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8

Western Wind and Solar Integration Study Phase 2

The electric grid is a highly complex, interconnected machine, and changing one part of the grid can have consequences elsewhere. Adding wind and solar affects the operation of the other power plants and adding high penetrations can induce cycling of fossil-fueled generators. Cycling leads to wear-and-tear costs and changes in emissions. Phase 2 of the Western Wind and Solar Integration Study(WWSIS-2) evaluated these costs and emissions and simulated grid operations for a year to investigate the detailed impact of wind and solar on the fossil-fueled fleet. This built on Phase 1, one of the largest wind and solar integration studies ever conducted, which examined operational impacts of high wind and solar penetrations in the West.

14 SOLAR ENERGY↗

The Western Wind and Solar Integration Study Phase 2

The electric grid is a highly complex, interconnected machine, and changing one part of the grid can have consequences elsewhere. Adding wind and solar affects the operation of the other power plants and adding high penetrations can induce cycling of fossil-fueled generators. Cycling leads to wear-and-tear costs and changes in emissions. Phase 2 of the Western Wind and Solar Integration Study (WWSIS-2) evaluated these costs and emissions and simulated grid operations for a year to investigate the detailed impact of wind and solar on the fossil-fueled fleet. This built on Phase 1, one of the largest wind and solar integration studies ever conducted, which examined operational impacts of high wind and solar penetrations in the West(GE Energy 2010).

14 SOLAR ENERGY↗

The Western Wind and Solar Integration Study Phase 2 (Executive Summary)

The electric grid is a highly complex, interconnected machine, and changing one part of the grid can have consequences elsewhere. Adding wind and solar affects the operation of the other power plants and adding high penetrations can induce cycling of fossil-fueled generators. Cycling leads to wear-and-tear costs and changes in emissions. Phase 2 of the Western Wind and Solar Integration Study (WWSIS-2) evaluated these costs and emissions and simulated grid operations for a year to investigate the detailed impact of wind and solar on the fossil-fueled fleet. This built on Phase 1, one of the largest wind and solar integration studies ever conducted, which examined operational impacts of high wind and solar penetrations in the West(GE Energy 2010).

14 SOLAR ENERGY↗

Data-Enhanced Hierarchical Control to Improve Distribution Voltage with Extremely High PV Penetration

Dynamic, scalable, and interoperable control paradigms are required to enable efficient, secure, reliable, and resilient distribution grid operations with widespread grid integration of renewable energy resources. This paper presents our recent research on developing a novel, holistic, data-enhanced hierarchical control architecture that addresses the formidable challenges faced by emerging distribution grids with increasing penetrations of distributed energy resources. The proposed architecture integrates centralized monitoring and control with distributed grid-edge control and thus effectively deals with multi-spatiotemporal dynamics existing in the grid. Simulation results are provided to demonstrate the effectiveness of the proposed control architecture.

14 SOLAR ENERGY↗

Data Enhanced Hierarchical Control to Improve Distribution Voltage with Extremely High PV Penetration: Preprint

Dynamic, scalable and interoperable control paradigm is required to enable efficient, secure, reliable and resilient distribution grid operations with widespread grid integration of renewable energy resources. This paper presents our recent research work on developing a novel, holistic, data enhanced hierarchical control architecture that addresses the formidable challenges faced by emerging distribution grids with increasing penetrations of distributed energy resources. The proposed architecture integrates centralized monitoring and control together with distributed grid edge control, and thus effectively deals with multi-spatiotemporal dynamics existing in the grid. Simulation results are provided to demonstrate the effectiveness of the proposed control architecture.

14 SOLAR ENERGY↗

Electron bunch dynamics and emission in particle-in-cell simulations of relativistic laser–solid interactions: On density artifacts, collisions, and numerical dispersion

Sub-optical-cycle dynamics of dense electron bunches in relativistic-intensity laser–solid interactions lead to the emission of high-order harmonics and attosecond light pulses. The capacity of particle-in-cell simulations to accurately model these dynamics is essential for the prediction of emission properties because the attosecond pulse intensity depends on the electron density distribution at the time of emission and on the temporal distribution of individual electron Lorentz-factors in an emitting electron bunch. Here, we show that in one-dimensional collisionless simulations, the peak density of the emitting electron bunch increases with the increase in the spatial resolution of the simulation grid. When collisions are added to the model, the peak electron density becomes independent of the spatial resolution. Collisions are shown to increase the spread of the peaks of Lorentz-factors of emitting electrons in time, especially in the regimes far from optimum generation conditions, thus leading to lower intensities of attosecond pulses as compared to those obtained in collisionless simulations.

Physics↗

Adaptive Neuro Fuzzy Inference System for Cyber-Intrusion Detection in a Smart Grid

The evolution of the power grid has brought increasing deployment of advance metering infrastructure, penetration of intelligent electronic devices, and integration of physical power system components with information and communications technologies. With the fast-expanding connectivity, cyber vulnerabilities arise due to the use of internet-based communication systems. These systems are targets of cyber-intrusions which attempt to disturb the normal power system functions. Traditional intrusion detection algorithms have been developed without an explicit model of the cyber components. In this paper, an algorithm to detect false data injections in the power system is proposed considering both cyber and physical models of the power system. The algorithm is based on an Adaptive Neuro Fuzzy Inference System (ANFIS) which collects information from state variables of the cyber-physical system to meet the performance requirements of the grid. Simulations of the proposed approach using the IEEE 13-bus test system validate the effectiveness of this artificial intelligence-based algorithm.

Adaptive Neuro Fuzzy Inference System (ANFIS), cyb↗

Electron Pre-acceleration at Nonrelativistic High-Mach-number Perpendicular Shocks

We perform particle-in-cell simulations of perpendicular nonrelativistic collisionless shocks to study electron heating and pre-acceleration for parameters that permit the extrapolation to the conditions at young supernova remnants. Our high-resolution large-scale numerical experiments sample a representative portion of the shock surface and demonstrate that the efficiency of electron injection is strongly modulated with the phase of the shock reformation. For plasmas with low and moderate temperature (plasma beta β{sub p}=5⋅10{sup −4} and β{sub p}=0.5), we explore the nonlinear shock structure and electron pre-acceleration for various orientations of the large-scale magnetic field with respect to the simulation plane, while keeping it at 90° to the shock normal. Ion reflection off of the shock leads to the formation of magnetic filaments in the shock ramp, resulting from Weibel-type instabilities, and electrostatic Buneman modes in the shock foot. In all of the cases under study, the latter provides first-stage electron energization through the shock-surfing acceleration mechanism. The subsequent energization strongly depends on the field orientation and proceeds through adiabatic or second-order Fermi acceleration processes for configurations with the out-of-plane and in-plane field components, respectively. For strictly out-of-plane field, the fraction of suprathermal electrons is much higher than for other configurations, because only in this case are the Buneman modes fully captured by the 2D simulation grid. Shocks in plasma with moderate β{sub p} provide more efficient pre-acceleration. The relevance of our results to the physics of fully 3D systems is discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

Provision of Grid Services by PV Plants with Integrated Battery Energy Storage System: Preprint

Battery energy storage systems (BESS), due to their tremendous range of uses and configurations, may assist PV integration in any number of ways by increasing power system flexibility. In this paper we describe results of a research project conducted by NREL and First Solar for developing controls and demonstrating many use cases for PV-BESS systems including (1) matching generation to loads through time shifting, reducing PV curtailment,; (2) promoting higher levels of PV penetrations by balancing the grid through ancillary services; (3) use of PV-BESS systems to provide wide-area stability services in the form of oscillations damping controls; and (r) use of gird forming BESS for enabling black start and islanded applications for PV-BESS systems. In the paper we will also describe the unique multi-MW test and validation platform developed at NREL for conducting research on fielded utility-scale PV-BESS systems. The platform consists of First Solar 0.43 MW PV power plant, NREL’s 1MW/1MW BESS, 2MW PV power supplies and 7MVA power electronic grid simulator interfaced with industrial plant controllers and power-hardware-in-the-loop (PHIL) capability.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Interconnection Standard Grid-Support Function Evaluations Using an Automated Hardware-in-the-Loop Testbed

Grid operators are increasingly turning to advanced grid-support functions in distributed energy resources (DER) to assist with distribution circuit voltage regulation, bulk system frequency control, and power system protection. The U.S. DER certification standard, Underwriters Laboratories (UL) 1741, was revised in September 2016 to add test procedures for multiple grid-support functions. Sandia National Laboratories, SunSpec Alliance, and growing community of collaborators have undertaken a multiyear effort to create an open-source system validation platform (SVP) that automates DER interconnection and interoperability test procedures by communicating with grid simulators, photovoltaic (PV) simulators, data acquisition systems, and interoperable equipment under test. However, the power hardware required for generating the test conditions may be untenable for many organizations. In this paper, we discuss development of the SVP testing capabilities for UL 1741 tests utilizing a controller hardware-in-the-loop testbed that precludes the need for power hardware using a 34.5 kW Austrian Institute of Technology smart grid controller. Finally, analysis of normal ramp rate, soft start ramp rate, specified power factor, volt-VAr, and frequency-watt advanced grid functions, and the effectiveness of the UL 1741 test protocols are included.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Fast Learning for Immersive Engagement in Energy Simulations

The fast computation which is critical for immersive engagement with and learning from energy simulations would be furthered by developing a general method for creating rapidly computed simplified versions of NREL's computation-intensive energy simulations. Created using machine learning techniques, these 'reduced form' simulations can provide statistically sound estimates of the results of the full simulations at a fraction of the computational cost with response times - typically less than one minute of wall-clock time - suitable for real-time human-in-the-loop design and analysis. Additionally, uncertainty quantification techniques can document the accuracy of the approximate models and their domain of validity. Approximation methods are applicable to a wide range of computational models, including supply-chain models, electric power grid simulations, and building models. These reduced-form representations cannot replace or re-implement existing simulations, but instead supplement them by enabling rapid scenario design and quality assurance for large sets of simulations. We present an overview of the framework and methods we have implemented for developing these reduced-form representations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Frame invariant neural network closures for Kraichnan turbulence

Numerical simulations of geophysical and atmospheric flows have to rely on parameterizations of subgrid scale processes due to their limited spatial resolution. Despite substantial progress in developing parameterization (or closure) models for subgrid scale (SGS) processes using physical insights and mathematical approximations, they remain imperfect and can lead to inaccurate predictions. In recent years, machine learning has been successful in extracting complex patterns from high-resolution spatio-temporal data, leading to improved parameterization models, and ultimately better coarse grid prediction. However, the inability to satisfy known physics and poor generalization hinders the application of these models for real-world problems. In this work, we put forth a frame invariant closure approach to improve the accuracy and generalizability of deep learning-based subgrid scale closure models by embedding physical symmetries directly into the structure of the neural network. Specifically, we utilized specialized layers within the convolutional neural network in such a way that desired constraints are theoretically guaranteed without the need for any regularization terms. We demonstrate our framework for a two-dimensional decaying turbulence test case mostly characterized by the forward enstrophy cascade. We show that our frame invariant SGS model (i) accurately predicts the subgrid scale source term, (ii) respects the physical symmetries such as translation, Galilean, and rotation invariance, and (iii) is numerically stable when implemented in coarse-grid simulation with generalization to different initial conditions and Reynolds number. This work opens up a possibility of connecting physics-based theories and data-driven modeling paradigms, and thus represents a promising step towards the development of physically consistent data-driven turbulence closure models.

42 ENGINEERING↗

Grid Modeling and Hosting Capacity Analysis

An interface with the OpenDSS distribution grid simulator, facilitating users in calibrating and validating models. Additionally, three distinct tools have been developed: PV Hosting Capacity: This tool allows users to determine the additional amount of photovoltaic (PV) generation that can be integrated into the system without breaching operational constraints. EV Hosting Capacity: This tool focuses on identifying the capacity for incorporating extra electric vehicle (EV) load into the system without surpassing operational limitations. Project Impact Analysis Tool: This tool is designed to assess and report all potential grid violations associated with a specific project, providing valuable insights into its impact on the distribution grid.

Poudel, Shiva↗

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↗

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↗

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↗

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↗

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↗