Voltage and power quality improvement strategy for a DFIG wind turbine during variable wind conditions

This paper presents a voltage and power quality enhancement scheme for a doubly-fed induction generator (DFIG) wind farm during variable wind conditions. The wind profiles were derived considering the measured data at a DFIG wind farm located in Northern Ireland (NI). The aggregated DFIG wind farm model was validated using measured data at a wind farm during variable generation. The voltage control strategy was developed considering the X/R ratio of the wind farm feeder which connects the wind farm and the grid. The performance of the proposed strategy was evaluated for different X/R ratios, and wind profiles with different characteristics. The impact of flicker propagation along the wind farm feeder and effectiveness of the proposed strategy is also evaluated with consumer loads connected to the wind farm feeder. It is shown that voltage variability and short-term flicker severity is significantly reduced following implementation of the novel strategy described.

Voltage Dip Benchmarking in Power Quality and Disturbance Monitoring

This paper examines power quality benchmarks in the electricity supply industry (ESI) and impact of standards for the reduction of voltage dip incidents. The paper considers adherence to particular standards and is supported by several case studies from incidents where voltage dips have been detected and assessed by the power systems division of Scottish Power and where improvements have been implemented to help militate against subsequent incidents.

Economies of scaling: More evidence that allometry of metabolism is linked to activity, metabolic rate and habitat

Organismal metabolic rates influence many ecological processes, and the mass-specific metabolic rate of organisms decreases with increasing body mass according to a power law. The exponent in this equation is commonly thought to be the three-quarter-power of body mass, determined by fundamental physical laws that extend across taxa. However, recent work has cast doubt as to the universality of this relationship, the value of 0.75 being an interspecies 'average' of scaling exponents that vary naturally between certain boundaries. There is growing evidence that metabolic scaling varies significantly between even closely related species, and that different values can be associated with lifestyle, activity and metabolic rates. Here we show that the value of the metabolic scaling exponent varies within a group of marine ectotherms, chitons (Mollusca: Polyplacophora: Mopaliidae), and that differences in the scaling relationship may be linked to species-specific adaptations to different but overlapping microhabitats. Oxygen consumption rates of six closely related, co-occurring chiton species from the eastern Pacific (Vancouver Island, British Columbia) were examined under controlled experimental conditions. Results show that the scaling exponent varies between species (between 0.64 and 0.91). Different activity levels, metabolic rates and lifestyle may explain this variation. The interspecific scaling exponent in these data is not significantly different from the archetypal 0.75 value, even though five out of six species-specific values are significantly different from that value. Our data suggest that studies using commonly accepted values such as 0.75 derived from theoretical models to extrapolate metabolic data of species to population or community levels should consider the likely variation in exponents that exists in the real world, or seek to encompass such error in their models. This study, as in numerous previous ones, demonstrates that scaling exponents show large, naturally occurring variation, and provides more evidence against the existence of a universal scaling law. © 2012 Elsevier B.V.

A scaling method for modelling the crashworthiness of novel roadside barrier designs

In this paper, a novel method for modelling a scaled vehicle–barrier crash test similar to the 20◦ angled barrier test specified in EN 1317 is reported. The intended application is for proof-of-concept evaluation of novel roadside barrier designs, and as a cost-effective precursor to full-scale testing or detailed computational modelling. The method is based on the combination of the conservation of energy law and the equation of motion of a spring mass system representing the impact, and shows, for the first time, the feasibility of applying classical scaling theories to evaluation of roadside barrier design. The scaling method is used to set the initial velocity of the vehicle in the scaled test and to provide scaling factors to convert the measured vehicle accelerations in the scaled test to predicted full-scale accelerations. These values can then be used to calculate the Acceleration Severity Index score of the barrier for a full-scale test. The theoretical validity of the method is demonstrated by comparison to numerical simulations of scaled and full-scale angled barrier impacts using multibody analysis implemented in the crash simulation software MADYMO. Results show a maximum error of 0.3% ascribable to the scaling method.

Accurate and Efficient Modelling to Calculate the Voltage Dependence of Liquid Crystal Based Reflectarray Cells

Two models that can predict the voltage-dependent scattering from liquid crystal (LC)-based reflectarray cells are presented. The validity of both numerical techniques is demonstrated using measured results in the frequency range 94-110 GHz. The most rigorous approach models, for each voltage, the inhomogeneous and anisotropic permittivity of the LC as a stratified media in the direction of the biasing field. This accounts for the different tilt angles of the LC molecules inside the cell calculated from the solution of the elastic problem. The other model is based on an effective homogeneous permittivity tensor that corresponds to the average tilt angle along the longitudinal direction for each biasing voltage. In this model, convergence problems associated with the longitudinal inhomogeneity are avoided, and the computation efficiency is improved. Both models provide a correspondence between the reflection coefficient (losses and phase-shift) of the LC-based reflectarray cell and the value of biasing voltage, which can be used to design beam scanning reflectarrays. The accuracy and the efficiency of both models are also analyzed and discussed.

Voltage Controlled Intertwined Spiral Arrays for Reconfigurable Metasurfaces

Reconfigurable bistate metasurfaces composed of interwoven spiral arrays with embedded pin diodes are proposed for single and dual polarisation operation. The switching capability is enabled by pin diodes that change the array response between transmission and reflection modes at the specified frequencies. The spiral conductors forming the metasurface also supply the dc bias for controlling pin diodes, thus avoiding the need of additional bias circuitry that can cause parasitic interference and affect the metasurface response. The simulation results show that proposed active metasurfaces exhibit good isolation between transmission and reflection states, while retaining excellent angular and polarisation stability with the large fractional bandwidth (FBW) inherent to the original passive arrays. © 2014 A. Vallecchi et al.

On the potential of significance-driven execution for energy-aware HPC

Dynamic Voltage and Frequency Scaling (DVFS) exhibits fundamental limitations as a method to reduce energy consumption in computing systems. In the HPC domain, where performance is of highest priority and codes are heavily optimized to minimize idle time, DVFS has limited opportunity to achieve substantial energy savings. This paper explores if operating processors Near the transistor Threshold Volt- age (NTV) is a better alternative to DVFS for break- ing the power wall in HPC. NTV presents challenges, since it compromises both performance and reliability to reduce power consumption. We present a first of its kind study of a significance-driven execution paradigm that selectively uses NTV and algorithmic error tolerance to reduce energy consumption in performance- constrained HPC environments. Using an iterative algorithm as a use case, we present an adaptive execution scheme that switches between near-threshold execution on many cores and above-threshold execution on one core, as the computational significance of iterations in the algorithm evolves over time. Using this scheme on state-of-the-art hardware, we demonstrate energy savings ranging between 35% to 67%, while compromising neither correctness nor performance.

TProf: An energy profiler for task-parallel programs

We present TProf, an energy profiling tool for OpenMP-like task-parallel programs. To compute the energy consumed by each task in a parallel application, TProf dynamically traces the parallel execution and uses a novel technique to estimate the per-task energy consumption. To achieve this estimation, TProf apportions the total processor energy among cores and overcomes the limitation of current works which would otherwise make parallel accounting impossible to achieve. We demonstrate the value of TProf by characterizing a set of task parallel programs, where we find that data locality, memory access patterns and task working sets are responsible for significant variance in energy consumption between seemingly homogeneous tasks. In addition, we identify opportunities for fine-grain energy optimization by applying per-task Dynamic Voltage and Frequency Scaling (DVFS).

Power-Capped DVFS and Thread Allocation with ANN Models on Modern NUMA Systems

Abstract—Power capping is an essential function for efficient power budgeting and cost management on modern server systems. Contemporary server processors operate under power caps by using dynamic voltage and frequency scaling (DVFS). However, these processors are often deployed in non-uniform memory
access (NUMA) architectures, where thread allocation between cores may significantly affect performance and power consumption. This paper proposes a method which maximizes performance under power caps on NUMA systems by dynamically optimizing two knobs: DVFS and thread allocation. The method selects the optimal combination of the two knobs with models based on artificial neural network (ANN) that captures the nonlinear effect of thread allocation on performance. We implement
the proposed method as a runtime system and evaluate it with twelve multithreaded benchmarks on a real AMD Opteron based NUMA system. The evaluation results show that our method outperforms a naive technique optimizing only DVFS by up to
67.1%, under a power cap.

Distribution Network Voltage Support Using Sensitivity-based Dispatch of Distributed Generation

This paper is concerned with the voltage and reactive power issues surrounding the connection of Distributed Generation (DG) on the low-voltage (LV) distribution network. The presented system-wide voltage control algorithm consists of three stages. Firstly available reactive power reserves are utilized. Then, if required, DG active power output is curtailed. Finally, curtailment of non-critical site demand is considered. The control methodology is tested on a variant of the 13-bus IEEE Node Radial Distribution Test Feeder. The presented control algorithm demonstrated that the distribution system operator (DSO) can maintain voltage levels within a desired statutory range by dispatching reactive power from DG or network devices. The practical application of the control strategy is discussed.

Power Scaling of Uplink Massive MIMO Systems with Arbitrary-Rank Channel Means

This paper investigates the uplink achievable rates of massive multiple-input multiple-output (MIMO) antenna systems in Ricean fading channels, using maximal-ratio combining (MRC) and zero-forcing (ZF) receivers, assuming perfect and imperfect channel state information (CSI). In contrast to previous relevant works, the fast fading MIMO channel matrix is assumed to have an arbitrary-rank deterministic component as well as a Rayleigh-distributed random component. We derive tractable expressions for the achievable uplink rate in the large-antenna limit, along with approximating results that hold for any finite number of antennas. Based on these analytical results, we obtain the scaling law that the users' transmit power should satisfy, while maintaining a desirable quality of service. In particular, it is found that regardless of the Ricean K-factor, in the case of perfect CSI, the approximations converge to the same constant value as the exact results, as the number of base station antennas, M, grows large, while the transmit power of each user can be scaled down proportionally to 1/M. If CSI is estimated with uncertainty, the same result holds true but only when the Ricean K-factor is non-zero. Otherwise, if the channel experiences Rayleigh fading, we can only cut the transmit power of each user proportionally to 1/√M. In addition, we show that with an increasing Ricean K-factor, the uplink rates will converge to fixed values for both MRC and ZF receivers.

Massive MIMO with Non-Ideal Arbitrary Arrays: Hardware Scaling Laws and Circuit-Aware Design

Massive multiple-input multiple-output (MIMO) systems are cellular networks where the base stations (BSs) are equipped with unconventionally many antennas, deployed on colocated or distributed arrays. Huge spatial degrees-of-freedom are achieved by coherent processing over these massive arrays, which provide strong signal gains, resilience to imperfect channel knowledge, and low interference. This comes at the price of more infrastructure; the hardware cost and circuit power consumption scale linearly/affinely with the number of BS antennas N. Hence, the key to cost-efficient deployment of large arrays is low-cost antenna branches with low circuit power, in contrast to today’s conventional expensive and power-hungry BS antenna branches. Such low-cost transceivers are prone to hardware imperfections, but it has been conjectured that the huge degrees-of-freedom would bring robustness to such imperfections. We prove this claim for a generalized uplink system with multiplicative phasedrifts, additive distortion noise, and noise amplification. Specifically, we derive closed-form expressions for the user rates and a scaling law that shows how fast the hardware imperfections can increase with N while maintaining high rates. The connection between this scaling law and the power consumption of different transceiver circuits is rigorously exemplified. This reveals that one can make the circuit power increase as p N, instead of linearly, by careful circuit-aware system design.

VEDA:Variation-aware energy-efficient discrete Wavelet Transform architecture

In this paper, we present a unified approach to an energy-efficient variation-tolerant design of Discrete Wavelet Transform (DWT) in the context of image processing applications. It is to be noted that it is not necessary to produce exactly correct numerical outputs in most image processing applications. We exploit this important feature and propose a design methodology for DWT which shows energy quality tradeoffs at each level of design hierarchy starting from the algorithm level down to the architecture and circuit levels by taking advantage of the limited perceptual ability of the Human Visual System. A unique feature of this design methodology is that it guarantees robustness under process variability and facilitates aggressive voltage over-scaling. Simulation results show significant energy savings (74% - 83%) with minor degradations in output image quality and avert catastrophic failures under process variations compared to a conventional design. © 2010 IEEE.