981 resultados para Phasor measurement unit (PMUs)


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In the current market system, power systems are operated at higher loads for economic reasons. Power system stability becomes a genuine concern in such operating conditions. In case of failure of any larger component, the system may become stressed. These events may start cascading failures, which may lead to blackouts. One of the main reasons of the major recorded blackout events has been the unavailability of system-wide information. Synchrophasor technology has the capability to provide system-wide real time information. Phasor Measurement Units (PMUs) are the basic building block of this technology, which provide the Global Positioning System (GPS) time-stamped voltage and current phasor values along with the frequency. It is being assumed that synchrophasor data of all the buses is available and thus the whole system is fully observable. This information can be used to initiate islanding or system separation to avoid blackouts. A system separation strategy using synchrophasor data has been developed to answer the three main aspects of system separation: (1) When to separate: One class support machines (OC-SVM) is primarily used for the anomaly detection. Here OC-SVM was used to detect wide area instability. OC-SVM has been tested on different stable and unstable cases and it is found that OC-SVM has the capability to detect the wide area instability and thus is capable to answer the question of “when the system should be separated”. (2) Where to separate: The agglomerative clustering technique was used to find the groups of coherent buses. The lines connecting different groups of coherent buses form the separation surface. The rate of change of the bus voltage phase angles has been used as the input to this technique. This technique has the potential to exactly identify the lines to be tripped for the system separation. (3) What to do after separation: Load shedding was performed approximately equal to the sum of power flows along the candidate system separation lines should be initiated before tripping these lines. Therefore it is recommended that load shedding should be initiated before tripping the lines for system separation.

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Disturbances in power systems may lead to electromagnetic transient oscillations due to mismatch of mechanical input power and electrical output power. Out-of-step conditions in power system are common after the disturbances where the continuous oscillations do not damp out and the system becomes unstable. Existing out-of-step detection methods are system specific as extensive off-line studies are required for setting of relays. Most of the existing algorithms also require network reduction techniques to apply in multi-machine power systems. To overcome these issues, this research applies Phasor Measurement Unit (PMU) data and Zubov’s approximation stability boundary method, which is a modification of Lyapunov’s direct method, to develop a novel out-of-step detection algorithm. The proposed out-of-step detection algorithm is tested in a Single Machine Infinite Bus system, IEEE 3-machine 9-bus, and IEEE 10-machine 39-bus systems. Simulation results show that the proposed algorithm is capable of detecting out-of-step conditions in multi-machine power systems without using network reduction techniques and a comparative study with an existing blinder method demonstrate that the decision times are faster. The simulation case studies also demonstrate that the proposed algorithm does not depend on power system parameters, hence it avoids the need of extensive off-line system studies as needed in other algorithms.

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This study examines the pattern of asset allocation and the performance of unit trust in Malaysia over the post crisis period by using risk-adjusted performance measures and multi-factor model from the year 2000 to 2004. Evidence from the statistics suggests that an active asset allocation strategy had been observed among Malaysian fund managers during the post Asian financial crisis. It is also suggested that investment allocation in equity remained a dominant vehicle for investment and asset allocation. Findings from multifactor model suggest that all funds of different objectives registered positive alphas except for income funds, with growth funds being among the top. While balanced funds registered highest diversification effectively, diversifying away about 70%-80% of unsystematic risk, the momentum factor is not among the important elements to explain unit trust performance in Malaysia.

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This presentation outlines key aspects of public policy in broad terms insofar as they relate to establishment, implementation and compliance with legal measurement standards. It refers in particular to traceability of a legal measurement unit from its source in a single international standard as a compliance issue. It comments on accreditation of legal measurement and liability concerned with errors in measurement.

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The Queensland University of Technology (QUT) allows the presentation of a thesis for the Degree of Doctor of Philosophy in the format of published or submitted papers, where such papers have been published, accepted or submitted during the period of candidature. This thesis is composed of seven published/submitted papers, of which one has been published, three accepted for publication and the other three are under review. This project is financially supported by an Australian Research Council (ARC) Discovery Grant with the aim of proposing strategies for the performance control of Distributed Generation (DG) system with digital estimation of power system signal parameters. Distributed Generation (DG) has been recently introduced as a new concept for the generation of power and the enhancement of conventionally produced electricity. Global warming issue calls for renewable energy resources in electricity production. Distributed generation based on solar energy (photovoltaic and solar thermal), wind, biomass, mini-hydro along with use of fuel cell and micro turbine will gain substantial momentum in the near future. Technically, DG can be a viable solution for the issue of the integration of renewable or non-conventional energy resources. Basically, DG sources can be connected to local power system through power electronic devices, i.e. inverters or ac-ac converters. The interconnection of DG systems to power system as a compensator or a power source with high quality performance is the main aim of this study. Source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, distortion at the point of common coupling in weak source cases, source current power factor, and synchronism of generated currents or voltages are the issues of concern. The interconnection of DG sources shall be carried out by using power electronics switching devices that inject high frequency components rather than the desired current. Also, noise and harmonic distortions can impact the performance of the control strategies. To be able to mitigate the negative effect of high frequency and harmonic as well as noise distortion to achieve satisfactory performance of DG systems, new methods of signal parameter estimation have been proposed in this thesis. These methods are based on processing the digital samples of power system signals. Thus, proposing advanced techniques for the digital estimation of signal parameters and methods for the generation of DG reference currents using the estimates provided is the targeted scope of this thesis. An introduction to this research – including a description of the research problem, the literature review and an account of the research progress linking the research papers – is presented in Chapter 1. One of the main parameters of a power system signal is its frequency. Phasor Measurement (PM) technique is one of the renowned and advanced techniques used for the estimation of power system frequency. Chapter 2 focuses on an in-depth analysis conducted on the PM technique to reveal its strengths and drawbacks. The analysis will be followed by a new technique proposed to enhance the speed of the PM technique while the input signal is free of even-order harmonics. The other techniques proposed in this thesis as the novel ones will be compared with the PM technique comprehensively studied in Chapter 2. An algorithm based on the concept of Kalman filtering is proposed in Chapter 3. The algorithm is intended to estimate signal parameters like amplitude, frequency and phase angle in the online mode. The Kalman filter is modified to operate on the output signal of a Finite Impulse Response (FIR) filter designed by a plain summation. The frequency estimation unit is independent from the Kalman filter and uses the samples refined by the FIR filter. The frequency estimated is given to the Kalman filter to be used in building the transition matrices. The initial settings for the modified Kalman filter are obtained through a trial and error exercise. Another algorithm again based on the concept of Kalman filtering is proposed in Chapter 4 for the estimation of signal parameters. The Kalman filter is also modified to operate on the output signal of the same FIR filter explained above. Nevertheless, the frequency estimation unit, unlike the one proposed in Chapter 3, is not segregated and it interacts with the Kalman filter. The frequency estimated is given to the Kalman filter and other parameters such as the amplitudes and phase angles estimated by the Kalman filter is taken to the frequency estimation unit. Chapter 5 proposes another algorithm based on the concept of Kalman filtering. This time, the state parameters are obtained through matrix arrangements where the noise level is reduced on the sample vector. The purified state vector is used to obtain a new measurement vector for a basic Kalman filter applied. The Kalman filter used has similar structure to a basic Kalman filter except the initial settings are computed through an extensive math-work with regards to the matrix arrangement utilized. Chapter 6 proposes another algorithm based on the concept of Kalman filtering similar to that of Chapter 3. However, this time the initial settings required for the better performance of the modified Kalman filter are calculated instead of being guessed by trial and error exercises. The simulations results for the parameters of signal estimated are enhanced due to the correct settings applied. Moreover, an enhanced Least Error Square (LES) technique is proposed to take on the estimation when a critical transient is detected in the input signal. In fact, some large, sudden changes in the parameters of the signal at these critical transients are not very well tracked by Kalman filtering. However, the proposed LES technique is found to be much faster in tracking these changes. Therefore, an appropriate combination of the LES and modified Kalman filtering is proposed in Chapter 6. Also, this time the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 7 proposes the other algorithm based on the concept of Kalman filtering similar to those of Chapter 3 and 6. However, this time an optimal digital filter is designed instead of the simple summation FIR filter. New initial settings for the modified Kalman filter are calculated based on the coefficients of the digital filter applied. Also, the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 8 uses the estimation algorithm proposed in Chapter 7 for the interconnection scheme of a DG to power network. Robust estimates of the signal amplitudes and phase angles obtained by the estimation approach are used in the reference generation of the compensation scheme. Several simulation tests provided in this chapter show that the proposed scheme can very well handle the source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, and synchronism of generated currents or voltages. The purposed compensation scheme also prevents distortion in voltage at the point of common coupling in weak source cases, balances the source currents, and makes the supply side power factor a desired value.

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A new approach is proposed for obtaining a non-linear area-based equivalent model of power systems to express the inter-area oscillations using synchronised phasor measurements. The generators that remain coherent for inter-area disturbances over a wide range of operating conditions define the areas, and the reduced model is obtained by representing each area by an equivalent machine. The parameters of the reduced system are identified by processing the obtained measurements, and a non-linear Kalman estimator is then designed for the estimation of equivalent area angles and frequencies. The simulation of the approach on a two-area system shows substantial reduction of non-inter-area modes in the estimated angles. The proposed methods are also applied to a ten-machine system to illustrate the feasibility of the approach on larger and meshed networks.

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A neonatal temperature monitoring system operating in subthreshold regime that utilizes time mode signal processing is presented. Resistance deviations in a thermistor due to temperature variations are converted to delay variations that are subsequently quantized by a Delay measurement unit (DMU). The DMU does away with the need for any analog circuitry and is synthesizable entirely from digital logic. An FPGA implementation of the system demonstrates the viability of employing time mode signal processing, and measured results show that temperature resolution better than 0.1 degrees C can be achieved using this approach.

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A robust, compact optical measurement unit for motion measurement in micro-cantilever arrays enables development of portable micro-cantilever sensors. This paper reports on an optical beam deflection-based system to measure the deflection of micro-cantilevers in an array that employs a single laser source, a single detector, and a resonating reflector to scan the measurement laser across the array. A strategy is also proposed to extract the deflection of individual cantilevers from the acquired data. The proposed system and measurement strategy are experimentally evaluated and demonstrated to measure motion of multiple cantilevers in an array. (C) 2015 AIP Publishing LLC.

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A wearable WIMU (Wireless Inertial Measurement Unit) [1] system for sports applications based on Tyndall's 25mm mote technology [2] has been developed to identify tennis performance determining factors, giving coaches & players improved feedback [3, 4]. Multiple WIMUs transmit player motion data to a PC/laptop via a receiver unit. Internally the WIMUs consist of: an IMU layer with MEMS based sensors; a microcontroller/transceiver layer; and an interconnect layer with supplemental 70g accelerometers and a lithium-ion battery. Packaging consists of a robust ABS plastic case with internal padding, a power switch, battery charging port and status LED with Velcro-elastic straps that are used to attach the device to the player. This offers protection from impact, sweat, and movement of sensors which could cause degradation in device performance. In addition, an important requirement for this device is that it needs to be lightweight and comfortable to wear. Calibration ensures that misalignment of the accelerometer and magnetometer axes are accounted for, allowing more accurate measurements to be made.

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Advanced sensory systems address a number of major obstacles towards the provision for cost effective and proactive rehabilitation. Many of these systems employ technologies such as high-speed video or motion capture to generate quantitative measurements. However these solutions are accompanied by some major limitations including extensive set-up and calibration, restriction to indoor use, high cost and time consuming data analysis. Additionally many do not quantify improvement in a rigorous manner for example gait analysis for 5 minutes as opposed to 24 hour ambulatory monitoring. This work addresses these limitations using low cost, wearable wireless inertial measurement as a mobile and minimal infrastructure alternative. In cooperation with healthcare professionals the goal is to design and implement a reconfigurable and intelligent movement capture system. A key component of this work is an extensive benchmark comparison with the 'gold standard' VICON motion capture system.

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Traditional motion capture techniques, for instance, those employing optical technology, have long been used in the area of rehabilitation, sports medicine and performance analysis, where accurately capturing bio-mechanical data is of crucial importance. However their size, cost, complexity and lack of portability mean that their use is often impractical. Low cost MEMS inertial sensors when combined and assembled into a Wireless Inertial Measurement Unit (WIMU) present a possible solution for low cost and highly portable motion capture. However due to the large variability inherent to MEMS sensors, such a system would need extensive characterization to calibrate each sensor and ensure good quality data capture. A completely calibrated WIMU system would allow for motion capture in a wider range of real-world, non-laboratory based applications. Calibration can be a complex task, particularly for newer, multi-sensing range capable inertial sensors. As such we present an automated system for quickly and easily calibrating inertial sensors in a packaged WIMU, demonstrating some of the improvements in accuracy attainable.

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This work employs a custom built body area network of wireless inertial measurement technology to conduct a biomechanical analysis of precision targeted throwing in competitive and recreational darts. The solution is shown to be capable of measuring key biomechanical factors including speed, acceleration and timing. These parameters are subsequently correlated with scoring performance to determine the affect each variable has on outcome. For validation purposes an optical 3D motion capture system provides a complete kinematic model of the subject and enables concurrent benchmarking of the 'gold standard' optical inertial measurement system with the more affordable and proactive wireless inertial measurement solution developed as part of this work.

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This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor technology. The framework comprises distributed agents (synchrophasors) for autonomous local condition monitoring and fault detection, and a central unit for generating global view for situation awareness and decision making. Key technologies that can be integrated into this hierarchical distributed learning scheme are discussed to enable real-time information extraction and knowledge discovery for decision making, without explicitly accumulating and storing all raw data by the central unit. Based on this, the configuration of a wide area monitoring system of power systems using synchrophasor technology, and the functionalities for locally installed open-phasor-measurement-units (OpenPMUs) and a central unit are presented. Initial results on anti-islanding protection using the proposed approach are given to illustrate the effectiveness.

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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.

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In this paper, our previous work on Principal Component Analysis (PCA) based fault detection method is extended to the dynamic monitoring and detection of loss-of-main in power systems using wide-area synchrophasor measurements. In the previous work, a static PCA model was built and verified to be capable of detecting and extracting system faulty events; however the false alarm rate is high. To address this problem, this paper uses a well-known ‘time lag shift’ method to include dynamic behavior of the PCA model based on the synchronized measurements from Phasor Measurement Units (PMU), which is named as the Dynamic Principal Component Analysis (DPCA). Compared with the static PCA approach as well as the traditional passive mechanisms of loss-of-main detection, the proposed DPCA procedure describes how the synchrophasors are linearly
auto- and cross-correlated, based on conducting the singular value decomposition on the augmented time lagged synchrophasor matrix. Similar to the static PCA method, two statistics, namely T2 and Q with confidence limits are calculated to form intuitive charts for engineers or operators to monitor the loss-of-main situation in real time. The effectiveness of the proposed methodology is evaluated on the loss-of-main monitoring of a real system, where the historic data are recorded from PMUs installed in several locations in the UK/Ireland power system.