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At least 757 records · Page 42

Model-free control for frequency response support in microgrids utilizing wind turbines

Islanded microgrids integrated with renewable energy resources bring additional challenges to the primary frequency control due to their power-electronic interfaced generations. Developing an efficient control strategy for inertia emulation and frequency response support of microgrids is becoming an important issue. Wind turbine dynamics, however, will degrade the emulated inertial and primary responses with most traditional control strategies. On the other hand, compensation methods often require the knowledge of system models at the design stage and state estimation for feedback once deployed online. To overcome these challenges, this paper explores a model-free control (MFC) strategy to emulate the desired inertia and support the frequency response of a diesel-wind microgrid system. Additionally, the proposed MFC strategy utilizes a model reference concept to obtain guaranteed inertial response and improve the frequency response of microgrids. This work considers different control strategies with different operating points. The proposed controller is implemented and verified using the modified 33-bus full nonlinear model of the three-phase diesel-wind system in Simulink. Simulation results demonstrate the improved frequency response by precisely emulating the desired inertia using the MFC strategy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Stochastic superparameterization in quasigeostrophic turbulence

In this article we expand and develop the authors' recent proposed methodology for efficient stochastic superparameterization algorithms for geophysical turbulence. Geophysical turbulence is characterized by significant intermittent cascades of energy from the unresolved to the resolved scales resulting in complex patterns of waves, jets, and vortices. Conventional superparameterization simulates large scale dynamics on a coarse grid in a physical domain, and couples these dynamics to high-resolution simulations on periodic domains embedded in the coarse grid. Stochastic superparameterization replaces the nonlinear, deterministic eddy equations on periodic embedded domains by quasilinear stochastic approximations on formally infinite embedded domains. The result is a seamless algorithm which never uses a small scale grid and is far cheaper than conventional SP, but with significant success in difficult test problems. Various design choices in the algorithm are investigated in detail here, including decoupling the timescale of evolution on the embedded domains from the length of the time step used on the coarse grid, and sensitivity to certain assumed properties of the eddies (e.g. the shape of the assumed eddy energy spectrum). We present four closures based on stochastic superparameterization which elucidate the properties of the underlying framework: a ‘null hypothesis’ stochastic closure that uncouples the eddies from the mean, a stochastic closure with nonlinearly coupled eddies and mean, a nonlinear deterministic closure, and a stochastic closure based on energy conservation. The different algorithms are compared and contrasted on a stringent test suite for quasigeostrophic turbulence involving two-layer dynamics on a β-plane forced by an imposed background shear. The success of the algorithms developed here suggests that they may be fruitfully applied to more realistic situations. They are expected to be particularly useful in providing accurate and efficient stochastic parameterizations for use in ensemble-based state estimation and prediction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Thermal–mechanical stress analysis of pressurized water reactor pressure vessel with/without a preexisting crack under grid load following conditions

In this paper, we present thermal-mechanical stress analysis of a pressurized water reactor pressure vessel and its hot-leg and cold-leg nozzles. Results are presented from thermal and thermal-mechanical stress analysis under reactor heat-up, cool-down, and grid load-following conditions. Analysis results are given with and without the presence of preexisting crack in the reactor nozzle (axial crack in hot leg nozzle). From the model results it is found that the stress-strain states are significantly higher in case of presence of crack than without crack. In conclusion, the stress-strain state under grid load following condition are more realistic compared to the stress-strain state estimated assuming simplified transients.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Peripheral transverse densities of the baryon octet from chiral effective field theory and dispersion analysis

The baryon electromagnetic form factors are expressed in terms of two-dimensional densities describing the distribution of charge and magnetization in transverse space at fixed light-front time. In this paper, we calculate the transverse densities of the spin-1/2 flavor-octet baryons at peripheral distances b=O(M$-1\atop{π}$) using methods of relativistic chiral effective field theory (χ EFT) and dispersion analysis. The densities are represented as dispersive integrals over the imaginary parts of the form factors in the timelike region (spectral functions). The isovector spectral functions on the two-pion cut t > 4 M$2\atop{π}$ are calculated using relativistic χEFT including octet and decuplet baryons. The χEFT calculations are extended into the ρ meson mass region using an N/D method that incorporates the pion electromagnetic form factor data. The isoscalar spectral functions are modeled by vector meson poles. We compute the peripheral charge and magnetization densities in the octet baryon states, estimate the uncertainties, and determine the quark flavor decomposition. Finally, the approach can be extended to baryon form factors of other operators and the moments of generalized parton distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Distributed output-feedback model predictive control for multi-agent consensus

We introduce a distributed output-feedback model predictive control approach for achieving consensus among multiple agents. Each agent computes a distributed control action based on an output-feedback measurement of a local neighborhood tracking error and communicates information only to its neighbors, according to a communication network modeled as a directed graph. Each agent computes its distributed control action by solving a local min–max optimization problem that simultaneously computes a local state estimate and control input under worst-case assumptions on unmeasured input disturbances and measurement noise. Under easily verified controllability and observability assumptions, this distributed output-feedback model predictive control approach provides an upper bound on the group consensus error, thereby ensuring practical consensus in the presence of unmeasured disturbances and noise. A numerical example with four agents connected in a directed graph is demonstrated to illustrate the results.

42 ENGINEERING↗

Plexcitons: The Role of Oscillator Strengths and Spectral Widths in Determining Strong Coupling

Strong coupling interactions between plasmon and exciton-based excitations have been proposed to be useful in the design of optoelectronic systems. However, the role of various optical parameters dictating the plasmon-exciton (plexciton) interactions is less understood. Herein, we propose an inequality for achieving strong coupling between plasmons and excitons through appropriate variation of their oscillator strengths and spectral widths. These aspects are found to be consistent with experiments on two sets of free-standing plexcitonic systems obtained by (i) linking fluorescein isothiocyanate on Ag nanoparticles of varying sizes through silane coupling and (ii) electrostatic binding of cyanine dyes on polystyrenesulfonate-coated Au nanorods of varying aspect ratios. Being covalently linked on Ag nanoparticles, fluorescein isothiocyanate remains in monomeric state, and its high oscillator strength and narrow spectral width enable us to approach the strong coupling limit. In contrast, in the presence of polystyrenesulfonate, monomeric forms of cyanine dyes exist in equilibrium with their aggregates: Coupling is not observed for monomers and H-aggregates whose optical parameters are unfavorable. The large aggregation number, narrow spectral width, and extremely high oscillator strength of J-aggregates of cyanines permit effective delocalization of excitons along the linear assembly of chromophores, which in turn leads to efficient coupling with the plasmons. Further, the results obtained from experiments and theoretical models are jointly employed to describe the plexcitonic states, estimate the coupling strengths, and rationalize the dispersion curves. The experimental results and the theoretical analysis presented here portray a way forward to the rational design of plexcitonic systems attaining the strong coupling limits.

Thomas, Reshmi↗

Can Biogeochemical Tracer Observations Constrain Southern Ocean Diapycnal Mixing Rates?

Abstract Direct observations of background diapycnal mixing rates in the Southern Ocean (SO) are limited spatially and temporally, making the choice of an appropriate value to parameterize this mixing in Earth system models a challenge. However, the deployment of Argo floats throughout the SO has provided an extensive range of observations of both physical and biogeochemical parameters. We use an ocean state estimate run with various background diapycnal mixing coefficients to assess if biogeochemical tracer observations can be used to better constrain SO diapycnal mixing rates. We find that vertical tracer distributions in the SO are highly sensitive to the rate of background diapycnal mixing and can provide an upper limit on background mixing rates. This demonstrates the importance of biogeochemical tracer observations throughout the full depth of the water column to validate ocean models.

Ellison, Elizabeth [The Australian National Univer↗

Systematic planning of moving target defence for maximising detection effectiveness against false data injection attacks in smart grid

Abstract Moving target defence (MTD) has been gaining traction to thwart false data injection attacks against state estimation (SE) in the power grid. MTD actively perturbs the reactance of transmission lines equipped with distributed flexible AC transmission system (D‐FACTS) devices to falsify the attacker's knowledge about the system configuration. However, the existing literature has not systematically studied what influences the detection effectiveness of MTD and how it can be improved based on the topology analysis. These problems are tackled here from the perspective of an MTD plan in which the D‐FACTS placement is determined. We first exploit the relation between the rank of the composite matrix and the detecting effectiveness. Then, we rigorously derive upper and lower bounds on the attack detecting probability of MTDs with a given rank of the composite matrix. Furthermore, we analyse existing planning methods and highlight the importance of bus coverage by D‐FACTS devices. To improve the detection effectiveness, we propose a novel graph theory–based planning algorithm to retain the maximum rank of the composite matrix while covering all necessary buses. Comparative results on multiple systems show the high detecting effectiveness of the proposed algorithm in both DC‐ and AC‐SE.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Man‐in‐the‐middle attacks and defence in a power system cyber‐physical testbed

Abstract Man‐in‐The‐Middle (MiTM) attacks present numerous threats to a smart grid. In a MiTM attack, an intruder embeds itself within a conversation between two devices to either eavesdrop or impersonate one of the devices, making it appear to be a normal exchange of information. Thus, the intruder can perform false data injection (FDI) and false command injection (FCI) attacks that can compromise power system operations, such as state estimation, economic dispatch, and automatic generation control (AGC). Very few researchers have focused on MiTM methods that are difficult to detect within a smart grid. To address this, we are designing and implementing multi‐stage MiTM intrusions in an emulation‐based cyber‐physical power system testbed against a large‐scale synthetic grid model to demonstrate how such attacks can cause physical contingencies such as misguided operation and false measurements. MiTM intrusions create FCI, FDI, and replay attacks in this synthetic power grid. This work enables stakeholders to defend against these stealthy attacks, and we present detection mechanisms that are developed using multiple alerts from intrusion detection systems and network monitoring tools. Our contribution will enable other smart grid security researchers and industry to develop further detection mechanisms for inconspicuous MiTM attacks.

Wlazlo, Patrick↗

Cross-Layered Distributed Data-Driven Framework for Enhanced Smart Grid Cyber-Physical Security

Smart Grid (SG) research and development has drawn much attention from academia, industry and government due to the great impact it will have on society, economics and the environment. Securing the SG is a considerably significant challenge due the increased dependency on communication networks to assist in physical process control, exposing them to various cyber-threats. In addition to attacks that change measurement values using False Data Injection (FDI) techniques, attacks on the communication network may disrupt the power system's real-time operation by intercepting messages, or by flooding the communication channels with unnecessary data. Addressing these attacks requires a cross-layer approach. In this paper a cross-layered strategy is presented, called Cross-Layer Ensemble CorrDet with Adaptive Statistics(CECD-AS), which integrates the detection of faulty SG measurement data as well as inconsistent network inter-arrival times and transmission delays for more reliable and accurate anomaly detection and attack interpretation. Numerical results show that CECD-AS can detect multiple False Data Injections, Denial of Service (DoS) and Man In The Middle (MITM) attacks with a high F1-score compared to current approaches that only use SG measurement data for detection such as the traditional physics-based State Estimation, Ensemble CorrDet with Adaptive Statistics strategy and other machine learning classification-based detection schemes.

cyber-physical security↗

Nonlinear automatic landing control of unmanned aerial vehicles on moving platforms via a 3D laser radar

This paper presents a motion tracking and control system for automatically landing Unmanned Aerial Vehicles (UAVs) on an oscillating platform using Laser Radar (LADAR) observations. The system itself is assumed to be mounted on a ship deck. A full nonlinear mathematical model is first introduced for the UAV. The ship motion is characterized by a Fourier transform based method which includes a realistic characterization of the sea waves. LADAR observation models are introduced and an algorithm to process those observations for yielding the relative state between the vessel and the UAV is presented, from which the UAV's state relative to an inertial frame can be obtained and used for feedback purposes. A sliding mode control algorithm is derived for tracking a landing trajectory defined by a set of desired waypoints. An extended Kalman filter (EKF) is proposed to account for process and observation noises in the design of a state estimator. The effectiveness of the control algorithm is illustrated through a simulation example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Bayesian filtering for model predictive control of stochastic gene expression in single cells

This study describes a method for controlling the production of protein in individual cells using stochastic models of gene expression. By combining modern microscopy platforms with optogenetic gene expression, experimentalists are able to accurately apply light to individual cells, which can induce protein production. Here we use a finite state projection based stochastic model of gene expression, along with Bayesian state estimation to control protein copy numbers within individual cells. We compare this method to previous methods that use population based approaches. We also demonstrate the ability of this control strategy to ameliorate discrepancies between the predictions of a deterministic model and stochastic switching system.

59 BASIC BIOLOGICAL SCIENCES↗

Cell degradation quantification—a performance metric-based approach

A safe and reliable battery operation needs effective diagnostic tools. A quantitative failure analysis (FA) to enable cell qualification and quantify its effectiveness for reliable and safe operation of rechargeable Li batteries (RLB) is shown here. The method can identify and quantify potential failure based on the state of charge (SOC) under any operating conditions. A precise and accurate electrochemical analytic diagnosis (eCAD) of 14 rechargeable Li || NMC622 cells of the same build are used as an example. The FA by eCAD can quantitatively decipher good, bad and ugly cells in cycle aging. The cell qualification is based on thermodynamic SOC, not experimental conditions. The method provides a quantitative failure mode and effect analysis (FMEA) to reveal diverse “dead Li” formation that affects the reversibility of the Li anode and charge retention in the cell. This cell qualification method highlights the potential to improve cell quality for safe operation, with strong implications for early fault detection, FA, risk mitigation, state estimation and life prediction for reliable and safe RLB operations

25 ENERGY STORAGE↗

Deterministic generation of remote entanglement with active quantum feedback

We develop and study protocols for deterministic remote entanglement generation using quantum feedback, without relying on an entangling Hamiltonian. In order to formulate the most effective experimentally feasible protocol, we introduce the notion of average-sense locally optimal feedback protocols, which do not require real-time quantum state estimation, a difficult component of real-time quantum feedback control. We use this notion of optimality to construct two protocols that can deterministically create maximal entanglement: a semiclassical feedback protocol for low-efficiency measurements and a quantum feedback protocol for high-efficiency measurements. The latter reduces to direct feedback in the continuous-time limit, whose dynamics can be modeled by a Wiseman-Milburn feedback master equation, which yields an analytic solution in the limit of unit measurement efficiency. Our formalism can smoothly interpolate between continuous-time and discrete-time descriptions of feedback dynamics and we exploit this feature to derive a superior hybrid protocol for arbitrary nonunit measurement efficiency that switches between quantum and semiclassical protocols. Lastly, we show using simulations incorporating experimental imperfections that deterministic entanglement of remote superconducting qubits may be achieved with current technology using the continuous-time feedback protocol alone.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Vibrational response and temperature of shock-compressed Pt: In situ extended x-ray absorption fine structure measurements to 325 GPa

Single pulse (~100 ps duration) extended x-ray absorption fine structure (EXAFS) measurements were obtained in laser shocked Pt to examine atomic vibrational properties and to determine temperatures for shock pressures from 72-325 GPa. Pt x-ray absorption spectra were recorded while a planar shock wave was propagating through the Pt sample. The absorption spectrum corresponding to the shocked Pt was obtained by subtracting the ambient Pt contribution from the measured absorption spectrum. Fits to the shocked state EXAFS data provided Pt lattice parameters consistent with the known Pt Hugoniot and the mean squared relative displacements (MSRDs) for nearest neighbor Pt atoms. Pt temperatures in the shocked state, estimated from the MSRDs using the correlated Debye model and correlated Einstein models, were consistent with both the Hugoniot temperatures calculated by integration along the Hugoniot and with the Hugoniot temperatures from published first-principles calculations. However, the agreement between the Hugoniot temperatures from EXAFS measurements and the calculated Hugoniot temperatures is not as good above 200 GPa, likely due to anharmonic effects. Furthermore, the present results demonstrate that single-pulse synchrotron EXAFS measurements in laser-shocked solids are useful for quantitative temperature determination and for examination of vibrational properties, including anharmonicity, at extreme pressure-temperature conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Proactive Stochastic Framework for Cyber-Physical Power Systems Security

This paper presents a framework for cyberphysical power systems security in which defensive action is proactive, striving to mitigate the harm from strategic cyber attacks before they occur. The prospect is formulated in a previously-studied context of state estimation via the Kalman filter under false data injection attacks. Assuming a cognitive attacker who is both advanced and persistent, the proactive defense rests upon stochastically influencing the sensors, Phasor Measurement Units, such that subsequent falsification attacks are countered. Examples are crafted to illustrate both the efficacy of the proactive approach in ideal situations and the practical challenges implied by non-ideal situations.

El Mezyani, Touria↗