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Electrical and Computer Engineering, Canadian Journal of

Issue 1 • Date Winter 2013

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Displaying Results 1 - 10 of 10
  • Canadian Journal of Electrical and Computer Engineering - Cover

    Page(s): c1
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  • Canadian Journal of Electrical and Computer Engineering - Masthead

    Page(s): C2
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  • Table of contents

    Page(s): 1
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  • Message from the Editor-in-Chief

    Page(s): 2
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  • Message from the President [of IEEE Canada]

    Page(s): 3
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    Freely Available from IEEE
  • Adaptive noise variance estimation and intrinsic order selection for low SNR hyperspectral signals

    Page(s): 4 - 10
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    In hyperspectral applications, signal vectors belong to a much lower dimensional subspace than the observed data. The true dimensionality of hyperspectral data is difficult to determine in practice. In the presence of powerful noise, estimation of the number of spectrally distinct signal sources that characterize the hyperspectral data is a challenge. Existing methods mostly assume some prior knowledge of the noise and signal structure. In practice, there is no a priori knowledge of the noise or signal statistics. Eigenvalue decomposition based methods, as the most commonly used methods, assume that the contribution of noise to the signal is extractable. In a noisy hyperspectral application this assumption is questionable. In this paper, we propose the Adaptive Noise Variance Estimation and Intrinsic Order Selection method that exploits the concept of residual autocorrelation power to adaptively estimate the noise variance and then simultaneously denoise and estimate the rank of the hyperspectral data. Rank conjecture is obtained by locating an optimum subset that best represents the noiseless signal. The algorithm was applied to both synthetically simulated data and to a real hyperspectral image. Comparing the results with those of existing methods indicates that this method will substantially improve the accuracy of the rank estimation in extremely noisy hyperspectral applications. View full abstract»

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  • Cubic spline-based tag estimation method in RFID multi-tags identification process

    Page(s): 11 - 17
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    Radio Frequency Identification (RFID) system is a communication technology used to identify objects using electromagnetic waves. The key advantage of RFID systems stems from their ability to simultaneously identify multiple tagged objects. However, communication of multiple tags with a reader may result in a collision problem, which is both time and energy inefficient, hindering the effectiveness of tag identification process. Presently, several anti-collision algorithms can be applied in order to reduce the collision probability. The reader¿s a priori knowledge of tag quantity significantly affects the overall performance of the system. Since the exact number of tags is not available for the reader, it is essential to develop an accurate tag estimation method to increase the efficiency of tag identification process. This paper presents a novel tag quantity estimation method, whereby, after simulating the tag distribution process, cubic spline interpolation method is employed to approximate the number of tags. According to the simulation results and the evaluation of the previous estimation methods, the new proposed method estimates the number of tags with a higher accuracy yielding an error rate of less than 1%, on average. Moreover, this low error rate is preserved even when the number of tags increases considerably. View full abstract»

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  • A decentralized self-adjusting control strategy for reactive power management in an islanded multi-bus MV microgrid

    Page(s): 18 - 25
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    This paper presents a decentralized self-adjusting reactive power controller for the autonomous operation of a multi-bus medium voltage (MV) microgrid. The main objective of the proposed control strategy of each distributed generation (DG) unit is to compensate the reactive power of its local loads and to share the reactive power of the nonlocal loads among itself and other DG units. The proposed control strategy includes an improved droop controller whose parameters are adjusted according to the reactive power of the local loads. A virtual inductive impedance loop is augmented to the voltage controller to enhance the steady state and transient responses of the proposed reactive power management scheme. The small signal analysis of the proposed method is presented to ensure stability of the system for different reactive power values. The presented strategy considerably enhances the voltage profiles of the microgrid buses as compared with the conventional droop methods. The proposed method does not require any communication link and minimizes the reactive power flow in the MV lines, thus reducing the losses of the overall microgrid. The performance of the proposed control scheme is verified by using digital time-domain simulation studies in the PSCAD/EMTDC software environment. View full abstract»

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  • A new algorithm to discriminate internal fault current and inrush current utilizing feature of fundamental current

    Page(s): 26 - 31
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    This paper presents a novel method to identify inrush current and internal fault current using the two-instantaneous-value-product algorithm to extract the variation feature of the fundamental current amplitude. First, the two-instantaneous-value-product algorithm is developed, and different variation trends of the fundamental current amplitude for inrush current and internal fault current are analyzed. Then, according to the descending features of the fundamental current amplitude, the inrush current and internal fault current can be distinguished from each other. A total of 216 experimental measurements have been tested on an YNd11 connected transformer. Dynamic testing results indicate that this method is able to clear internal faults, even light ones, within a cycle and is not affected by the current transformer saturation. Moreover, compared with the second harmonic restraint principle and the waveform comparison principle, the proposed algorithm has better performance. The computational simplicity of the proposed scheme enables its implementation in real-time applications with low-cost microprocessors. View full abstract»

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  • A global approach to transient stability constrained optimal power flow using a machine detailed model

    Page(s): 32 - 41
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    Transient stability constrained optimal power flow (TSC-OPF) is originally a nonlinear optimization problem with variables and constraints in time domain, which is not easy to deal with because of its huge dimension, especially for systems with detailed machine models. This paper presents an efficient approach to realize TSC-OPF by introducing an independent dynamics simulation algorithm into the optimization procedure. In the new approach, the simulation algorithm is used to realize the dynamic constraints and to deduce the transient stability constraint, while the optimization algorithm verifies the steady state and the transient stability constraints together. The new TSC-OPF has just one more constraint than that of a conventional OPF and can be solved by a conventional OPF algorithm with small modification. In the new approach, there is no limitation for the machine model and the simulation method. The nonlinearity of the power system is taken fully into account. In the paper, the proposed approach is verified with a small three-machines system. The simulation results show the machine model influences greatly the system transient stability and the TSC-OPF results. The widely used machine classical model in the TSC-OPF over-estimates the system transient stability and under-estimates the TSC-OPF costs. View full abstract»

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Aims & Scope

The role of the Canadian Journal of Electrical and Computer Engineering is to provide scientific and professional activity for its members in Canada, the CJECE complements international journals and will be of particular interest to anyone involved in research and development activities in the field of electrical and computer engineering.

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Meet Our Editors

Editor-in-Chief
Dr. Shahram Yousefi
Dept. of Electrical and Computer
     Engineering
Queen's University