SiGe V Band Wide Tuning-Range VCO and Frequency Divider for Phase Locked Loop

A V-band wide tuning-range VCO and high frequency divide-by-8 frequency divider using Infineon 0.35 µm SiGe HBT process are presented in this paper. An LC impedance peaking technique is introduced in the Miller divider to increase the sensitivity and operation frequency range of the frequency divider. Two static frequency dividers implemented using current mode logic are used to realize dividing by 4 in the circuit. The wide tuning range VCO operates from 51.9 to 64.1 GHz i.e. 20.3% frequency tuning range. The measured phase noise at the frequency divider output stage is around -98.5 dBc at 1 MHz. The circuit consumes 200mW and operates from a 3.5Vdc supply, and occupies 0.6×0.8 mm2 die area.

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.

Measurement-based Method for Wind Farm Power System Oscillation Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly-fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This paper presents a measurement based method for the early detection of power system oscillations, with attention to mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet transform and support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in different frequency bands, while SVDD is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude or that are resonant can be alarmed to the system operator, to reduce the risk of system instability. Method evaluation is exemplified used real data from a chosen wind farm.

Context-Aware Body Area Networks (CABAN) for interactive smart environments:Interference characterization

Body Area Networks are unique in that the large-scale mobility of users allows the network itself to travel across a diverse range of operating domains or even to enter new and unknown environments. This network mobility is unlike node mobility in that sensed changes in inter-network interference level may be used to identify opportunities for intelligent inter-networking, for example, by merging or splitting from other networks, thus providing an extra degree of freedom. This paper introduces the concept of context-aware bodynets for interactive environments using inter-network interference sensing. New ideas are explored at both the physical and link layers with an investigation based on a 'smart' office environment. A series of carefully controlled measurements of the mesh interconnectivity both within and between an ambulatory body area network and a stationary desk-based network were performed using 2.45 GHz nodes. Received signal strength and carrier to interference ratio time series for selected node to node links are presented. The results provide an insight into the potential interference between the mobile and static networks and highlight the possibility for automatic identification of network merging and splitting opportunities. © 2010 ACM.

On sea level change in the North Sea influenced by the North Atlantic Oscillation: local and remote steric effects

In this study, contributions of both local steric and remote baroclinic effects (i.e., steric variations external to the region of interest) to the inter-annual variability of winter sea level in the North Sea, with respect to the North Atlantic Oscillation (NAO), for the period of 1953–2010 are investigated. On inter-annual time scales in this period, the NAO is significantly correlated to sea level variations in the North Sea only in the winter months (December–March), while its correlation to sea temperature over much of the North Sea is only significant in January and February. The discrepancy in sea level between observations and barotropic tide and surge models forced by tides and local atmospheric forcing, i.e., local atmospheric pressure effects and winds, in the present study are found to be consistent with previous studies. In the North Sea, local thermosteric effects caused by thermal expansion play a minor role on winter-mean NAO related sea level variability compared with atmospheric forcing. This is particularly true in the southeastern North Sea where water depths are mostly less than 25 m. Our calculations demonstrate that the discrepancy can be mostly explained by remote baroclinic effects, which appear as water mass exchanges on the continental shelf and are therefore only apparent in ocean bottom pressure. In the North Sea, NAO related sea level variations seem to be a hybrid of barotropic and baroclinic processes. Hence, they can only be adequately modelled with three-dimensional baroclinic ocean models that include contributions of baroclinic effects and large-scale atmospheric forcing external to the region of interest.

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.

Sea-level changes in Iceland and the influence of the North Atlantic Oscillation during the last half millennium

We present a new, diatom-based sea-level reconstruction for Iceland spanning the last -500 years, and investigate the possible mechanisms driving the sea-level changes. A sea-level reconstruction from near the Icelandic low pressure system is important as it can improve understanding of ocean-atmosphere forcing on North Atlantic sea-level variability over multi-decadal to centennial timescales. Our reconstruction is from Viarhólmi salt marsh in Snæfellsnes in western Iceland, a site from where we previously obtained a 2000-yr record based upon less precise sea-level indicators (salt-marsh foraminifera). The 20th century part of our record is corroborated by tide-gauge data from Reykjavik. Overall, the new reconstruction shows ca0.6m rise of relative sea level during the last four centuries, of which ca0.2m occurred during the 20th century. Low-amplitude and high-frequency sea-level variability is super-imposed on the pre-industrial long-term rising trend of 0.65m per 1000 years. Most of the relative sea-level rise occurred in three distinct periods: AD 1620-1650, AD 1780-1850 and AD 1950-2000, with maximum rates of ~3±2mm/yr during the latter two of these periods. Maximum rates were achieved at the end of large shifts (from negative to positive) of the winter North Atlantic Oscillation (NAO) Index as reconstructed from proxy data. Instrumental data demonstrate that a strong and sustained positive NAO (a deep Icelandic Low) generates setup on the west coast of Iceland resulting in rising sea levels. There is no strong evidence that the periods of rapid sea-level rise were caused by ocean mass changes, glacial isostatic adjustment or regional steric change. We suggest that wind forcing plays an important role in causing regional-scale coastal sea-level variability in the North Atlantic, not only on (multi-)annual timescales, but also on multi-decadal to centennial timescales.

Improving RO PUF design using frequency distribution characteristics

A Physical Unclonable Function (PUF) can be used to provide authentication of devices by producing die-unique responses. In PUFs based on ring oscillators (ROs) the responses are derived from the oscillation frequencies of the ROs. However, RO PUFs can be vulnerable to attack due to the frequency distribution characteristics of the RO arrays. In this letter, in order to improve the design of RO PUFs for FPGA devices, the frequencies of RO arrays implemented on a large number of FPGA chips are statistically analyzed. Three RO frequency distribution (ROFD) characteristics, which can be used to improve the design of RO PUFs are observed and discussed.

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.

Synapsin- and actin-dependent frequency enhancement in mouse hippocampal mossy fiber synapses

The synapsin proteins have different roles in excitatory and inhibitory synaptic terminals. We demonstrate a differential role between types of excitatory terminals. Structural and functional aspects of the hippocampal mossy fiber (MF) synapses were studied in wild-type (WT) mice and in synapsin double-knockout mice (DKO). A severe reduction in the number of synaptic vesicles situated more than 100 nm away from the presynaptic membrane active zone was found in the synapsin DKO animals. The ultrastructural level gave concomitant reduction in F-actin immunoreactivity observed at the periactive endocytic zone of the MF terminals. Frequency facilitation was normal in synapsin DKO mice at low firing rates (approximately 0.1 Hz) but was impaired at firing rates within the physiological range (approximately 2 Hz). Synapses made by associational/commissural fibers showed comparatively small frequency facilitation at the same frequencies. Synapsin-dependent facilitation in MF synapses of WT mice was attenuated by blocking F-actin polymerization with cytochalasin B in hippocampal slices. Synapsin III, selectively seen in MF synapses, is enriched specifically in the area adjacent to the synaptic cleft. This may underlie the ability of synapsin III to promote synaptic depression, contributing to the reduced frequency facilitation observed in the absence of synapsins I and II.