Helicon Mode Formation and Radio Frequency Power Deposition in a Helicon Produced Plasma

Time- and space-resolved magnetic (B-dot) probe measurements in combination with measurements of the plasma parameters were carried out to investigate the relationship between the formation and propagation of helicon modes and the radio frequency (rf) power deposition in the core of a helicon plasma. The Poynting flux and the absorbed power density are deduced from the measured rf magnetic field distribution in amplitude and phase. Special attention is devoted to the helicon absorption under linear and nonlinear conditions. The present investigations are attached to recent observations in which the nonlinear nature of the helicon wave absorption has been demonstrated by showing that the strong absorption of helicon waves is correlated with parametric excitation of electrostatic fluctuations.

Measurements of the XUV mass absorption coefficient of an overdense liquid metal

The increase in the XUV mass absorption coefficient of liquid aluminium, produced by high-power-laser shock-compression, is measured using XUV laser radiography. At a photon energy of 63 eV a change in the mass absorption coefficient by up to a factor of similar to2.2 is determined at densities close to twice that of solid and electron temperatures of the order of 1 eV. Comparison with hydrodynamic simulations indicate that the absorption coefficient scales with density as rho (1.3 +/-0.2).

Electron number density measurements in magnesium laser produced plumes

Interferometry has been used to investigate the spatio-temporal evolution of electron number density following 248 nm laser ablation of a magnesium target. Fringe shifts were measured as a function of laser power density for a circular spot obtained using a random phase plate. Line averaged electron number densities were obtained at delay times up to ∼100 ns after the laser pulse. Density profiles normal to the target surface were recorded for power densities on target in the range 125–300 MW cm−2.

A Wavelet-Prony Method for Modeling of Fixed-Speed Wind Farm Low-Frequency Power Pulsations

The increasing penetration of wind generation on the Island of Ireland has been accompanied by close investigation of low-frequency pulsations contained within active power flow. A primary concern is excitation of low-frequency oscillation modes already present on the system, particularly the 0.75 Hz mode as a consequence of interconnection between the Northern and Southern power system networks. In order to determine whether the prevalence of wind generation has a negative effect (excites modes) or positive impact (damping of modes) on the power system, oscillations must be measured and characterised. Using time – frequency methods, this paper presents work that has been conducted to extract features from low-frequency active power pulsations to determine the composition of oscillatory modes which may impact on dynamic stability. The paper proposes a combined wavelet-Prony method to extract modal components and determine damping factors. The method is exemplified using real data obtained from wind farm measurements.

Validation of fixed speed induction generator models for inertial response using wind farm measurements

This paper outlines the use of phasor measurement unit (PMU) records to validate models of fixed speed induction generator (FSIG)-based wind farms during frequency transients. Wind turbine manufacturers usually create their own proprietary models which they can supply to power system utilities for stability studies, subject to confidentiality agreements. However, it is desirable to confirm the accuracy of supplied models with measurements from the particular installation, in order to assess their validity under real field conditions. This is prudent due to possible changes in control algorithms and design retrofits, not accurately reflected or omitted in the supplied model. One important aspect of such models, especially for smaller power systems with limited inertia, is their accuracy during system frequency transients. This paper, therefore, assesses the accuracy of FSIG models with regard to frequency stability, and hence validates a subset of the model dynamics. Such models can then be used with confidence to assess wider system stability implications. The measured and simulated response of a wind farm using doubly fed induction generator (DFIG) technology is also assessed.

Effect of resonance frequency, power input, and saturation gas type on the oxidation efficiency of an ultrasound horn

The sonochemical oxidation efficiency (eta(ox)) of a commercial titanium alloy ultrasound horn has been measured using potassium iodide as a dosimeter at its main resonance frequency (20 kHz) and two higher resonance frequencies (41 and 62 kHz). Narrow power and frequency ranges have been chosen to minimise secondary effects such as changing bubble stability, and time available for radical diffusion from the bubble to the liquid. The oxidation efficiency, eta(ox), is proportional to the frequency and to the power transmitted to the liquid (275 mL) in the applied power range (1-6 W) under argon. Luminol radical visualisation measurements show that the radical generation rate increases and a redistribution of radical producing zones is achieved at increasing frequency. Argon, helium, air, nitrogen, oxygen, and carbon dioxide have been used as saturation gases in potassium iodide oxidation experiments. The highest eta(ox) has been observed at 5 W under air at 62 kHz. The presence of carbon dioxide in air gives enhanced nucleation at 41 and 62 kHz and has a strong influence on eta(ox). This is supported by the luminol images, the measured dependence of eta(ox). on input power, and bubble images recorded under carbon dioxide. The results give insight into the interplay between saturation gas and frequency, nucleation, and their effect on eta(ox). (C) 2010 Elsevier B.V. All rights reserved.

Online Tracking of Thévenin Equivalent Parameters Using PMU Measurements

This paper presents a new method for tracking Thévenin equivalent parameters for a power system at a node using local Phasor Measurement Unit (PMU) measurements. Three consecutive phasor measurements for voltage and current, recorded at one location, are used. The phase drifts caused by the measurement slip frequency are first determined and phase angles of the measured phasors are corrected so that the corrected phasors are synchronized to the same reference. The synchronized phasors are then used to determine the equivalent Thévenin parameters of the system.

Analysis of Two-Speed Wind Farm Operation From Grid-Side Measurements

This paper analyzes data captured by a phasor measurement unit at a wind farm, employing two-speed induction generators, and investigates aspects of the control system's interaction with the power system. Composite superimposed transient events are proposed as a method to improve the quality of the analysis and reduce errors caused by unknowns, such as wind speed variation. A Mathworks SimPowerSystems model validates the inertia contribution of the wind farm, which is an important parameter in power systems with high wind penetration. Transients caused by turbine speed transitions are identified and explained. The analysis also highlights areas where wind farm control should be improved if useful inertia contribution is to be provided.

Analysis of Fixed-Speed Wind Farm Low-Frequency Power Pulsations using a Wavelet-Prony Method

The increasing penetration of wind generation on the Island of Ireland has been accompanied by close investigation of low-frequency periodic pulsations contained within the active power flow from different wind farms. A primary concern is excitation of existing low-frequency oscillation modes already present on the system, particularly the 0.75 Hz mode as a consequence of the interconnected Northern and Southern power system networks. Recently grid code requirements on the Northern Ireland power system have been updated stipulating that wind farms connected after 2005 must be able to control the magnitude of oscillations in the range of 0.25 - 1.75 Hz to within 1% of the wind farm's registered output. In order to determine whether wind farm low-frequency oscillations have a negative effect (excite other modes) or possibly a positive impact (damping of existing modes) on the power system, the oscillations at the point of connection must be measured and characterised. Using time - frequency methods, research presented in this paper has been conducted to extract signal features from measured low-frequency active power pulsations produced by wind farms to determine the effective composition of possible oscillatory modes which may have a detrimental effect on system dynamic stability. The paper proposes a combined wavelet-Prony method to extract modal components and determine damping factors. The method is exemplified using real data obtained from wind farm measurements.

Principal Component Analysis of Wide Area Phasor Measurements for Islanding Detection – A Geometric View

This paper presents a new technique for the detectionof islanding conditions in electrical power systems. This problem isespecially prevalent in systems with significant penetrations of distributedrenewable generation. The proposed technique is based onthe application of principal component analysis (PCA) to data setsof wide-area frequency measurements, recorded by phasor measurementunits. The PCA approach was able to detect islandingaccurately and quickly when compared with conventional RoCoFtechniques, as well as with the frequency difference and change-ofangledifference methods recently proposed in the literature. Thereliability and accuracy of the proposed PCA approach is demonstratedby using a number of test cases, which consider islandingand nonislanding events. The test cases are based on real data,recorded from several phasor measurement units located in theU.K. power system.

Topology of megagauss magnetic fields and of heat-carrying electrons produced in a high-power laser-solid interaction

The intricate spatial and energy distribution of magnetic fields, self-generated during high power laser irradiation (at Iλ2∼1013-1014W.cm-2.μm2) of a solid target, and of the heat-carrying electron currents, is studied in inertial confinement fusion (ICF) relevant conditions. This is done by comparing proton radiography measurements of the fields to an improved magnetohydrodynamic description that fully takes into account the nonlocality of the heat transport. We show that, in these conditions, magnetic fields are rapidly advected radially along the target surface and compressed over long time scales into the dense parts of the target. As a consequence, the electrons are weakly magnetized in most parts of the plasma flow, and we observe a reemergence of nonlocality which is a crucial effect for a correct description of the energetics of ICF experiments.

Real-time temperature estimation for power MOSFETs considering thermal aging effects

This paper presents a novel real-time power-device temperature estimation method that monitors the power MOSFET's junction temperature shift arising from thermal aging effects and incorporates the updated electrothermal models of power modules into digital controllers. Currently, the real-time estimator is emerging as an important tool for active control of device junction temperature as well as online health monitoring for power electronic systems, but its thermal model fails to address the device's ongoing degradation. Because of a mismatch of coefficients of thermal expansion between layers of power devices, repetitive thermal cycling will cause cracks, voids, and even delamination within the device components, particularly in the solder and thermal grease layers. Consequently, the thermal resistance of power devices will increase, making it possible to use thermal resistance (and junction temperature) as key indicators for condition monitoring and control purposes. In this paper, the predicted device temperature via threshold voltage measurements is compared with the real-time estimated ones, and the difference is attributed to the aging of the device. The thermal models in digital controllers are frequently updated to correct the shift caused by thermal aging effects. Experimental results on three power MOSFETs confirm that the proposed methodologies are effective to incorporate the thermal aging effects in the power-device temperature estimator with good accuracy. The developed adaptive technologies can be applied to other power devices such as IGBTs and SiC MOSFETs, and have significant economic implications. 

Characteristics of Offshore Wind Speeds using Buoy Measurements

In the coming decade installed offshore wind capacity is expected to expand rapidly. This will be both technically and economically challenging. Precise wind resource assessment is one of the more imminent challenges. It is more difficult to assess wind power offshore than onshore due to the paucity of representative wind speed data. Offshore site-specific data is less accessible and is far more costly to collect. However, offshore wind speed data collected from sources such as wave buoys, remote sensing from satellites, national weather ships, and coastal meteorological stations and met masts on barges and platforms may be extrapolated to assess offshore wind power. This study attempts to determine the usefulness of pre-existing offshore wind speed measurements in resource assessment, and presents the results of wind resource estimation in the Atlantic Ocean and in the Irish Sea using data from two offshore meteorological buoys

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.