R. Behkam; A. Moradzadeh; H. Karami; M.S. Nadery; B. Mohammadi ivatloo; G.B. Gharehpetian; S. Tenbohlen
Abstract
The Frequency Response Analysis (FRA) technique has advantages in identifying faults related to power transformers, but it suffers from the interpretation of frequency responses. This paper presents an approach based on statistical indices and Artificial Neural Network (ANN) methods to interpret frequency ...
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The Frequency Response Analysis (FRA) technique has advantages in identifying faults related to power transformers, but it suffers from the interpretation of frequency responses. This paper presents an approach based on statistical indices and Artificial Neural Network (ANN) methods to interpret frequency responses. The proposed procedure divides frequency responses into four frequency regions based on frequency resonances and anti-resonances. Then, Lin’s Concordance Coefficient (LCC) index is used as one of the most appropriate numerical indices to extract features of the four frequency regions. Finally, the Multilayer Perceptron (MLP) neural network is trained by the extracted features to identify and differentiate the types of winding faults. Besides, other intelligent algorithms such as Support Vector Machine (SVM), Extreme Learning Machine (ELM), Probabilistic Neural Network (PNN), and Radial Basis Function (RBF) neural network have been employed to compare the classification results. The proposed techniques have been practically implemented. The Axial Displacement (AD) and Disk Space Variation (DSV) faults are applied as two common mechanical faults in different locations and intensities on the 20kV windings of a 1.6MVA distribution power transformer and their corresponding frequency responses are calculated. Frequency responses calculated from the AD and DSV faults constitute the MLP input data set. The network is trained with part of the input data, and the rest of the data is allocated to validate and test the network. The results show that the suggested method has more proper performance than others using the phase component of the frequency responses in interpreting frequency responses and separation and identifying various mechanical fault types of transformer windings.
Micro Grid
M. Zolfaghari; G. B. Gharehpetian; M. Abedi
Abstract
In this paper a repetitive control (RC) approach to improve current sharing between parallel-connected boost converters in DC microgrids is presented. The impact of changes in line impedance on current sharing is investigated. A repetitive controller is designed and connected in series with current controller ...
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In this paper a repetitive control (RC) approach to improve current sharing between parallel-connected boost converters in DC microgrids is presented. The impact of changes in line impedance on current sharing is investigated. A repetitive controller is designed and connected in series with current controller of the boost converters to control the switching signals such that by regulating of the output voltage of each converter, the circulating current is minimized. The performance of the proposed control strategy is validated through simulation.
Micro Grid
Reza Ghanizadeh; Mahmoud Ebadian; Gevork B. Gharehpetian
Volume 4, Issue 1 , June 2016, , Pages 66-82
Abstract
In this paper, a new approach is proposed for voltage and current harmonics compensation in grid-connected microgrids (MGs). If sensitive loads are connected to the point of common coupling (PCC), compensation is carried out in order to reduce PCC voltage harmonics. In absence of sensitive loads at PCC, ...
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In this paper, a new approach is proposed for voltage and current harmonics compensation in grid-connected microgrids (MGs). If sensitive loads are connected to the point of common coupling (PCC), compensation is carried out in order to reduce PCC voltage harmonics. In absence of sensitive loads at PCC, current harmonics compensation scenario is selected in order to avoid excessive injection of harmonics by the main grid. In both scenarios, compensation is performed by the interface converters of distributed generation (DG) units. Also, to decrease the asymmetry among phase impedances of MG, a novel structure is proposed to generate virtual impedance. At fundamental frequency, the proposed structure for the virtual impedance improves the control of the fundamental component of power, and at harmonic frequencies, it acts to adaptively improve nonlinear load sharing among DG units. In the structures of the proposed harmonics compensator and the proposed virtual impedance, a self-tuning filter (STF) is used for separating the fundamental component from the harmonic components. This STF decreases the number of phase locked loops (PLLs). Simulation results in MATLAB/SIMULINK environment show the efficiency of the proposed approach in improving load sharing and decreasing voltage and current harmonics.
