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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. Finally, the methodology developed can be used to extend the analysis to other locations.

14 SOLAR ENERGY↗
DOE OSTI2021

Improved Control Strategy of Grid Interface for EV High-Power Dynamic Wireless Charging

This paper proposes a control strategy for the grid interface converter in high-power dynamic wireless charging system (DWCS) to address two issues on distribution network integration. Due to the unique pulsating load profile of DWCS, load transient response capability is critical for the grid interface to maintain the dc-bus voltage stable. Besides, the inherent unbalanced situation of distribution network would lead to 2nd-order oscillations on the dc-bus voltage, which would further affect the stable operation of the entire system. In this paper, the DWCS model is developed, and the relationship between the dc-bus voltage and the input/output power is analyzed. Based on the developed model, a control strategy based on direct power control is presented. Both simulation results and hardware-in-the-loop (HIL) results demonstrate that the proposed control strategy not only improves load transient response capability, but also eliminates the 2nd-order oscillations on the dc-bus voltage under imbalanced distribution network conditions.

Zeng, Rong↗
DOE OSTI2020

An Application of ASP in Nuclear Engineering: Explaining the Three Mile Island Nuclear Accident Scenario

Abstract The paper describes an ongoing effort in developing a declarative system for supporting operators in the Nuclear Power Plant (NPP) control room. The focus is on two modules: diagnosis and explanation of events that happened in NPPs. We describe an Answer Set Programming (ASP) representation of an NPP, which consists of declarations of state variables, components, their connections, and rules encoding the plant behavior. We then show how the ASP program can be used to explain the series of events that occurred in the Three Mile Island, Unit 2 (TMI-2) NPP accident, the most severe accident in the USA nuclear power plant operating history. We also describe an explanation module aimed at addressing answers to questions such as “why an event occurs?” or “what should be done?” given the collected data.

Computer Science↗
DOE OSTI2022

The Role of Groundwater Withdrawals on River Regulation: Example From the Columbia River Basin

The Columbia River Basin (CRB) is heavily regulated by more than 250 dams on its river system while depending significantly on groundwater withdrawals in certain sub-basins. Neglecting groundwater withdrawals in hydrologic models of the basin could result in inaccurate predictions of its water budget and thus mislead water management decisions in the basin. This work aims to understand the impacts of groundwater pumping on the spatiotemporal patterns of modeling regulated streamflow in the CRB using a modified version of the Variable Infiltration Capacity (VIC) model integrated with a water management component that accounts for groundwater withdrawals, irrigation demands, and reservoir operation (VIC-GIRR). The VIC-GIRR simulations showed that considering additional groundwater withdrawals would alleviate the stress of irrigation water deficit in the Snake River Basin with an average reduction of 10 km 3 /year. Such a reduction in water deficit resulted in slight streamflow increase over the CRB with maximum increase up to 40% during dry period in certain locations. We also note that the implementation of groundwater withdrawal does not, however, improve the overall model performance in long-term averaged streamflow and storage predictions. Our results highlight the efforts needed to examine additional important processes in representing the interactions between water withdrawals and reservoir operations. Such efforts will aid in better simulation of multi-reservoir system and improve effectiveness for agricultural productivity, power generation, flood control, and navigation purposes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Imaging local discharge cascades for correlated electrons in WS 2 /WSe 2 moiré superlattices

Transition metal dichalcogenide moiré heterostructures provide an ideal platform to explore the extended Hubbard model, where long-range Coulomb interactions play a critical role in determining strongly correlated electron states. This has led to experimental observations of Mott insulator states at half filling as well as a variety of extended Wigner crystal states at different fractional fillings. However, a microscopic understanding of these emerging quantum phases is still lacking. Here we describe a scanning tunnelling microscopy (STM) technique for the local sensing and manipulation of correlated electrons in a gated WS 2 /WSe 2 moiré superlattice, which enables the experimental extraction of fundamental extended Hubbard model parameters. We demonstrate that the charge state of the local moiré sites can be imaged by their influence on the STM tunnelling current. In addition to imaging, we are also able to manipulate the charge state of correlated electrons. When we ramp the bias on the STM tip, there is a local discharge cascade of correlated electrons in the moiré superlattice, which allows us to estimate the nearest-neighbour Coulomb interaction. Two-dimensional mapping of the moiré electron charge states also enables us to determine the on-site energy fluctuations at different moiré sites. Furthermore, our technique should be broadly applicable to many semiconductor moiré systems, offering a powerful tool for the microscopic characterization and control of strongly correlated states in moiré superlattices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Tale of Two Simulators—A Comparative Human-in-the-Loop Nuclear Power Plant Operations Study on Thermal Power Dispatch for Hydrogen Production

A study was designed for a reconfigurable, full-scale, full-scope nuclear power plant control room simulator to compare two different thermal power dispatch systems, on separate simulator platforms, demonstrating a TPD concept of operation. A TPD system can provide a desirable alternative revenue source for utilities but requires addressing new and unique operational issues. The selection of representative scenarios and the scenario-based experimental design are presented as key elements to capture evidence for validating the developed TPD concept of operations overcome these operational issues.

Ulrich, Thomas A.↗
DOE OSTI2021

Characteristics of Ultralow Aspect Ratio Toroidal Plasmas and Non-Solenoidal Startup and Edge Stability Studies at Near-Unity Aspect Ratio (Final Report)

This grant supported a long-term research and development program to explore the physics and technology of spherical tokamak (ST) plasma behavior at near-unity aspect ratio ( A ). The PEGASUS Toroidal Experiment is a university-scale ( R ) ~ 0.40 m, α ~ .35 m, I p ≤ 0.3 MA, B T ≤ 0.15 T) experiment that accesses A → 1, to provide large values of the normalized plasma current, I N = I p /α B T , or equivalently the toroidal field utilization factor I p / I TF . The research activities focused on: 1) developing the technique of Local Helicity Injection (LHI) as a viable means of initiating and growing an ST plasma without the use of a central solenoid; 2) exploring the equilibrium and stability properties of spherical tokamak plasmas at extremely low aspect ratio; and 3) obtaining new insights in the properties of the enhanced confinement H-mode regime at A ~ 1. The initial (Phase I) facility employed a unique high-stress central solenoid Ohmic for current drive and heating with simple magnet current waveforms. A subsequent major upgrade (Phase II) offered more flexible control of the plasma evolution along with a powerful LHI system for plasma initiation, heating and sustainment. The LHI technique consists of injection of high-density current streams into vacuum toroidal and vertical magnetic fields. These streams become unstable and support magnetic reconnection to allow the system to relax into a tokamak-like magnetic configuration. This program focused on: 1) development of electron current sources that provide sufficiently high injection currents in the challenging edge plasma region; 2) validation of theoretical limits to achievable I p arising from magnetic helicity and energy conservation plus absolute limits arising from relaxation to a minimal energy states; 3) tests of a power balance model to describe the evolution of the plasma current I p (t); and 4) study of magnetic fluctuations and their role in the I p evolution. This culminated in the production of toroidal currents of I p ≥ 0.2 MA with only ~8 kA of injected current. Operation with Ohmic induction alone in Phase I created plasmas with soft limits on the achievable I p and field utilization ( I p / I TF ~ 1) due to the onset of large low-order (2/1 or 3/2) internal resonant tearing modes. With the expanded capabilities in Phase II operation, methods employed to mitigate those modes and achieve I p / I TF > 1 were: 1) I TF ramp-downs; 2) non-solenoidal startup via LHI; and 3) extremely low I TF Ohmic operations assisted by LHI current injector pre-ionization. Extensive use of LHI-driven startup and drive for non-solenoidal operation produced favorable current profiles to stably operate tokamak plasmas with unprecedentedly high I N = I p / aB T ~ 15 and I p / I TF > 2. With strong reconnection-driven anomalous ion heating, this in turn provided access to tokamak plasmas with B t up to 100%, a world record 2 times higher than that previously achieved in advanced or spherical tokamaks. This high B t regime had a large fraction (~50%) of the plasma volume in a region of an absolute minimum- B configuration. The MHD stability limit in this regime was the ideal external kink mode without a stabilizing wall. These results provided the first demonstration of access to tokamak plasmas with very high B t , high i N , high elongation κ, and low internal inductance ℓ i , and as such served as a proof-ofprinciple for access to this long-sought ST regime. The naturally low B T needed for stability at A ≤ 1.2 reduces the L-H mode power threshold, P LH , so that H-mode plasmas were achieved with Ohmic heating alone. The power threshold for the transition to the H-mode regime was found to be 10× the accepted values from the ITER international scaling, confirming initial trends indicated by experiments on MAST and NSTX, and suggesting that the physics behind this transition is not yet fully understood. The density dependence of the transition and the observed insensitivity to whether the plasma is bounded by a limiter or magnetic divertor are consistent with the recent FM 3 model. Multiple unstable toroidal magnetic modes were measured during ELM (Edge Localized Mode) crashes, with generally lower toroidal mode numbers than seen at higher A , which was attributed to the larger peeling mode instability drive at low A . First-ever edge current profile measurements through an ELM crash showed current-carrying filaments were generated, as seen in ELM simulations and in electromagnetic blob transport theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Automated System-wide Event Detection and Classification Using Machine Learning on Synchrophasor Data

As the number of phasor measurement units (PMUs) deployed in a power system increases, and their data volume streamed to the control canter intensifies, operators are facing challenges related to the analysis of such data, which need to be observed and responded to as the measurements are displayed in the Control Room. Humans are generally unable to process such large amount of data efficiently and rapidly. There is an apparent need for automated ways to analyze the data, extract actionable information about occurrence of specific events, and characterize the events quickly and cost effectively. This paper discusses the use of machine learning (ML) to facilitate such tasks by providing automated, highly computationally efficient, and cost-effective ways of extracting actionable information from synchrophasor big data in real-time. We developed Big Data Smart (BDSmart) ML-based prototype tool for the Control Room use that automatically analyses data properties from synchrophasor system measurements taken across the three grid Interconnections in the USA (Western, Eastern and ERCOT). The data collected from several hundreds of PMUs located across the Interconnections over a period of two years have been made available for our extensive study. As a result, we were able to identify a number of big data properties that influence how ML methodology is applied to select, develop, train and test the data models that can eventually be used for the tool implementation. The resulting set of candidate algorithms spans unsupervised, supervised, semi-supervised and transfer-learning approaches. Many ML techniques, such as decision trees, multinomial logistic regression, feed-forward neural networks, K-nearest neighbor, multiclass support vector machine, and single and multi-channel convolutional neural networks, are implemented, and their performance is examined. We offer the results from testing the data models. The novelty of our study is in the approaches for bad data detection and mitigation, selection of a simplified feature for event detection, and data label improvements. As a result, we came up with a list of recommendations for the utilities on how to improve the PMU recording practices to cater to the future ML applications aimed at automating the analysis of synchrophasor data.

Synchrophasors, Machine Learning, System-wide Even↗
DOE OSTI2020

A Robust Segmented Mixed Effect Regression Model for Baseline Electricity Consumption Forecasting

Renewable energy production has been surging around the world in recent years. To mitigate the increasing uncertainty and intermittency of the renewable generation, proactive demand response algorithms and programs are proposed and developed to further improve the utilization of load flexibility and increase the efficiency of power system operation. One of the biggest challenges to efficient control and operation of demand response resources is how to forecast the baseline electricity consumption and estimate the load impact from demand response resources accurately. In this paper, we propose a mixed effect segmented regression model and a new robust estimate for forecasting the baseline electricity consumption in Southern California, USA, by combining the ideas of random effect regression model, segmented regression model, and the least trimmed squares estimate. Since the log-likelihood of the considered model is not differentiable at breakpoints, we propose a new backfitting algorithm to estimate the unknown parameters. The estimation performance of the new estimation procedure has been demonstrated with both simulation studies and the real data application for the electric load baseline forecasting in Southern California.

42 ENGINEERING↗
DOE OSTI2021

Enhancing Responsiveness and Resilience with Distributed Applications in the Grid

A number of trends are increasing the variability in electric power systems resulting in a need for new approaches in control. The increased variability is originating from distributed energy resources and an increasing demand for personalized energy choice from customers grid-edge. Electricity distribution systems continue to incorporate increasing numbers of intelligent end devices, automated switchgear, and sensing and measurement devices which are providing more visibility and control at the grid-edge. Traditional distribution system planning and operations techniques must evolve to meet the new complexity while continuing to deliver safe, reliable, and cost-effective energy. New technologies are enabling new capabilities at the grid-edge to respond to these needs. Distributed applications can deploy intelligence across the distribution grid with peer-to-peer communications and a shared data context for their local environment. These applications can cooperate with each other to respond quickly to changing grid conditions. This enables a layered coordination framework spanning the centralized Advanced Distribution Management System functions with wide area visibility to these new distributed applications running at intelligent devices and meters throughout the distribution system. This paper describes an open-architecture, open-source system approach for commercial scale integration of devices and intelligence at the grid-edge.

Ogle, James P.↗
DOE OSTI2022

SRF Cavity Emulator for PIP-II LLRF Lab and Field Testing

There are many stages in the LLRF and RF system development process for any new accelerator that can take advantage of hardware emulation of the high-power RF system and RF cavities. LLRF development, bench testing, control system development and testing of installed systems must happen well before SRF cavities are available for test. The PIP-II Linac has three frequencies of SRF cavities, 162.5 MHz, 325 MHz and 650 MHz and a simple analog emulator design has been chosen that can meet the cavity bandwidth requirements, provide tuning errors to emulate Lorentz force detuning and microphonics for all cavity types. This emulator design utilizes a quartz crystal with a bandwidth of 65Hz at an IF of ~ 4 MHz, providing a Q of ~ 1.3 x 10^7 at 650MHz. This paper will discuss the design and test results of this emulator.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Investigation of the Use of Dynamic Probabilistic Risk Assessment Methodologies for Identifying Digital I&C System Common Cause Failures

Digital Instrumentation and Control (I&C) systems have a key role in nuclear power plants in the upgrade of aging analog systems. Digital systems improve plant safety and reliability through features such as increased hardware reliability and stability and improved failure detection capability. There is no consensus on which of the current probabilistic risk assessment methods are most suitable for use in the reliability analysis of digital I&C systems. While the traditional event-tree/fault-tree (ET/FT) approach is still used for their reliability modeling, there are concerns regarding this approach in properly accounting for dynamic interactions among system components since potentially significant dependencies among failure events may not be identified and/or their likelihood may not be properly quantified. Dynamic methodologies are expected to provide a much more accurate representation of probabilistic evolution of the I&C systems in time due to their capability to more properly account for complex interactions than the static approach. The applicability of dynamic PRA methodologies for digital I&C system is investigated using the criteria presented in the NUREG/CR-6901, and the comparisons made in NUREG/CR-6901 are updated in light of the latest studies. The Dynamic Event Tree (DET) approach has been identified as one of the top dynamic methods when evaluated against the requirements for the reliability modeling of digital I&C systems. The DET method is a strong candidate for integration into existing PRA studies, as it bears many similarities to the traditional ET approach. In this study, the DET approach has been applied to the Plant Protection System of the APR1400 design, and the results are compared to results from its available traditional ET/FT analysis. Possible approaches to evaluate and quantify the effects of common cause failures on system safety using dynamic methods are also examined.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Model predictive control for active insulation in building envelopes

Active insulation systems (AISs) refer to building envelopes with insulation materials that can change their thermal conductivity and are coupled with thermal mass to reduce building energy consumption and peak power. In this research, a novel optimal control approach is proposed to evaluate the maximum theoretical energy and cost-saving potential of AISs. A time-varying model predictive control (TV-MPC) controller was used to optimally select the AIS mode and simultaneously determine the operation of the heating, ventilation and air conditioning (HVAC) system so that the maximum saving potential of the entire system can be realized. To comprehensively evaluate the power shifting flexibility of AISs, two optimization objectives—minimizing weekly electric energy consumption and minimizing weekly electricity cost—were considered. The summer season simulation results show that under the first objective, more than 50% electric and thermal energy was saved when the upper boundary of the indoor air temperature was set to 25 °C. Furthermore under the second optimization objective, 38% of the cost was saved. It can be expected that the developed approach can be easily applied to multiple types of AISs with different mechanisms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Renewable Integration in Hybrid ac-dc Systems using Multi-port Autonomous Reconfigurable Solar power plant (MARS)

To increase inertia and improve primary frequency response of future grids, grid-forming inverters connecting PV to grid and energy storage systems (ESSs) are likely to play an important role. Moreover, high-voltage direct current (HVdc) links will also be an enabler to transfer remote PV generation and for improved grid stability. That is, with increased penetration of PV, discrete development of PV and ESS connecting to transmission ac grid and HVdc links is one of the solutions for stable operation of grid. Here, an integrated concept for integration of PV and ESS to transmission ac grid and HVdc links is proposed that is named as multi-port autonomous reconfigurable solar power plant (MARS). The proposed integrated development reduces the cost associated with respect to discrete development of PV-ESS systems connecting to transmission ac grid and HVdc links. The integrated development incorporates advanced control methods to provide inertial and primary frequency response, reactive power support, and transient stability to manage PV and ESS resources. In this paper, high-fidelity switched system model of the integrated system and grids are developed and detailed simulation results are provided to showcase the stable operation of the integrated system and provision of grid support functions.

14 SOLAR ENERGY↗
DOE OSTI2024

Dynamic Shaping of Grid Response of Multi-Machine Multi-Inverter Systems Through Grid-Forming IBRs: Preprint

We consider the problem of controlling the frequency response of weakly-coupled multi-machine multi-inverter low-inertia power systems via grid-forming inverter-based resources (IBRs). In contrast to existing methods, our approach relies on dividing the larger system into multiple strongly-coupled subsystems, without ignoring either the underlying network or approximating the subsystem response as an aggregate harmonic mean model. Rather, through a structured clustering and recursive dynamic shaping approach, the frequency response of the overall system to load perturbations is shaped appropriately. We demonstrate the proposed approach for a three-node triangular configuration and a small-scale radial network. Furthermore, for small-scale radial microgrids, we demonstrate the ability of IBRs to tune the effective transfer functions of synchronous machines. This enables us to relax the uniform turbine time-constant assumptions and widen the scope of existing synchronization results for proportionally heterogeneous machines.

frequency-shaping control↗
DOE OSTI2023

Performance characterization of freeform finished surfaces of potassium dihydrogen phosphate using fluid jet polishing with a nonaqueous slurry

Abstract Potassium dihydrogen phosphate (KDP) and its deuterated analog (DKDP) are unique nonlinear optical materials for high power laser systems. They are used widely for frequency conversion and polarization control by virtue of the ability to grow optical-quality crystals at apertures suitable for fusion-class laser systems. Existing methods for freeform figuring of KDP/DKDP optics do not produce surfaces with sufficient laser-induced–damage thresholds (LIDT’s) for operation in the ultraviolet portion of high-peak-power laser systems. In this work, we investigate fluid jet polishing (FJP) using a nonaqueous slurry as a sub-aperture finishing method for producing freeform KDP surfaces. This method was used to selectively polish surface areas to different depths on the same substrate with removals ranging from 0.16 μm to 5.13 μm. The finished surfaces demonstrated a slight increase in roughness as the removal depth increased along with a small number of fracture pits. Laser damage testing with 351 nm, 1 ns pulses demonstrated excellent surface damage thresholds, with the highest values in areas devoid of fracture pits. This work demonstrates, for the first time, a method that enables fabrication of a waveplate that provides tailored polarization randomization that can be scaled to meter-sized optics. Furthermore, this method is based on FJP technology that incorporates a nonaqueous slurry specially designed for use with KDP. This novel nonaqueous FJP process can be also used for figuring other types of materials that exhibit similar challenging inherent properties such as softness, brittleness, water-solubility, and temperature sensitivity.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Frequency Injection Based HVDC Attack-Defense Control Via Squeeze-Excitation Double CNN

Due to the independent controllability and fast power regulation capability, the High Voltage Direct Current (HVDC) system could be a prospective technology to provide multiple ancillary services to the system besides conventional bulk power transmission. However, with the increase of False Data Injection Attacks (FDIAs) on PMU data, the HVDC system could have the wrong response once the collected data that the HVDC system relied on is attacked, thus threatening the system operating security. How to ensure the security of the PMU-based HVDC ancillary service control become an urgent issue. To mitigate the risk, this paper proposed an HVDC attack-defense control based on the FDIAs detection method. Firstly, the Squeeze-Excitation based Double Convolutional Neural Networks (SE-DCNN) is proposed to realize fast identification of the attacking frequency type based on the time and frequency domain signals. Furthermore, the duration time of FDIAs is detected by the local outlier factor. Then, utilizing the results from SE-DCNN, HVDC ancillary service control framework is reorganized and an HVDC attack defense control is proposed for suppressing the potential influence of various types of FDIAs on the HVDC system ancillary service. Different experiments results demonstrate that the proposed method has the ability to significantly mitigate the frequency deviation and oscillation under the FDIA.

42 ENGINEERING↗