This paper proposes a model-based fault diagnosis scheme for grid-connected photovoltaic systems with distributed maximum power point tracking (MPPT) strategy. Specifically, short-circuit switch faults in optimizers (...
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This paper proposes a model-based fault diagnosis scheme for grid-connected photovoltaic systems with distributed maximum power point tracking (MPPT) strategy. Specifically, short-circuit switch faults in optimizers (boost dc/dc converters in series connection for MPPT purposes) are considered in this study. Depending on the application, SCFs can be more or less detrimental to the stability and integrity of systems. In systems with high penetration, disturbances in voltage or frequency can be generated that can, in the worst case, cause instabilities in the system. Hence, a fast fault detection strategy is mandatory. It is worth noting that, unlike other works reported to date, the control action of the optimizers presents singularities under this fault scenario, making the fault diagnosis task difficult. For this, a decoupled subsystem from i) dc/ac converter dynamics and ii) irradiance changes are obtained for fault and disturbance isolation purposes. Then, a dedicated high-gain observers bank is proposed for a residual generation. In this way, fault time detection is achieved in 8 switching periods. Finally, a numerical evaluation has been carried out to validate the ideas proposed in this paper. For this, three series-connected optimizers interconnected to a three-phase 220V 60 Hz grid through a neutral point clamped (NPC) inverter with a first-order L filter were considered in the simulation.
This paper proposes a model-based fault diagnosis scheme for grid-connected photovoltaic systems with distributed maximum power point tracking (MPPT) strategy. Specifically, short-circuit switch faults in optimizers (...
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This paper proposes a model-based fault diagnosis scheme for grid-connected photovoltaic systems with distributed maximum power point tracking (MPPT) strategy. Specifically, short-circuit switch faults in optimizers (boost dc/dc converters in series connection for MPPT purposes) are considered in this study. Depending on the application, SCFs can be more or less detrimental to the stability and integrity of systems. In systems with high penetration, disturbances in voltage or frequency can be generated that can, in the worst case, cause instabilities in the system. Hence, a fast fault detection strategy is mandatory. It is worth noting that, unlike other works reported to date, the control action of the optimizers presents singularities under this fault scenario, making the fault diagnosis task difficult. For this, a decoupled subsystem from i) dc/ac converter dynamics and ii) irradiance changes are obtained for fault and disturbance isolation purposes. Then, a dedicated high-gain observers bank is proposed for a residual generation. In this way, fault time detection is achieved in 8 switching periods. Finally, a numerical evaluation has been carried out to validate the ideas proposed in this paper. For this, three series-connected optimizers interconnected to a three-phase 220V 60 Hz grid through a neutral point clamped (NPC) inverter with a first-order L filter were considered in the simulation.
This paper develops a consistent estimator for coefficients of probability density functions defined in Multiresolution Analysis Structures (MRD), and an algorithm based on the proposed estimator. This algorithm, name...
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This paper develops a consistent estimator for coefficients of probability density functions defined in Multiresolution Analysis Structures (MRD), and an algorithm based on the proposed estimator. This algorithm, namedfd, behaves similarly to the maximum likelihood estimator for large datasets. The process, by which the coefficients estimated by thefdalgorithm and, then, used to estimate theMRDon a regular point grid, is called Multiresolution Density Estimation (MRDE) and leads to consistentMRDestimations. Simulations trials reveal that thefdalgorithm based on a Frequency Data Count is faster and easier to apply than the Expectation Maximization (EM). The research also shows that using the same data and grid, theMRDEis frequently faster than the Kernel Density Estimation using Fast Fourier Transform algorithm(KDEFFT) These results suggest theMRDEmethod for estimating Multiresolution densities could be applied to estimate probability densities in the big data field.
A processing chain from the transmitter to the receiver dealing with a stepped frequency waveform combined with phase coding (PC) has been proposed in a recent paper. It consists in splitting the spectrum of a PC puls...
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ISBN:
(纸本)9781728189420
A processing chain from the transmitter to the receiver dealing with a stepped frequency waveform combined with phase coding (PC) has been proposed in a recent paper. It consists in splitting the spectrum of a PC pulse into predetermined portions, and then transmitting the corresponding time-domain signals. At the receiver, a modified version of the frequency domain (fd) algorithm is used to process the received echoes. However, this processing chain could be improved. Indeed, alternative modulations could be considered to offer a degree of freedom to the practitioner. In addition, when the number of portions becomes large, the performance of the proposed fd algorithm degrades, the spectrum of the reconstructed waveform being distorted. Therefore, in this paper, the novelty stands in the following items: 1) at the transmitter, the non-linear frequency modulation (NLFM) can be considered as an alternative to PC 2) at the receiver, a novel time-domain waveform reconstruction (TWR) is proposed to process the received echoes in the time domain instead of operating in the frequency domain. Our simulations show that, unlike the modified fd algorithm, for any number of portions, the performance obtained using the TWR algorithm is the same at high signal-to-noise ratio (SNR), whereas at low SNR, the larger the number of portions used, the better the performance.
A great deal of interest has been paid to enhance the radar range resolution for the last decades. One of the techniques is to construct a waveform combining inter-pulse and intra-pulse modulations. In this paper, ste...
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A great deal of interest has been paid to enhance the radar range resolution for the last decades. One of the techniques is to construct a waveform combining inter-pulse and intra-pulse modulations. In this paper, stepped frequency (SF) waveform is used to represent the former, whereas phase coding (PC) is considered for the latter. To obtain the high-resolution range profile (HRRP) of a target induced by an SF waveform at the receiver, one of the approaches is the frequency domain (fd) algorithm. It has been successfully applied with SF linear frequency modulation waveforms. However, based on our investigations, processing the SFPC waveform with the fd algorithm does not lead to the performance, in terms of peak sidelobe ratio (PSLR) and integrated sidelobe ratio (ISLR), of the single-carrier phase coding (SCPC) waveform processed with a matched filter (MF). To overcome these drawbacks, we propose to split the spectrum of a phase coded pulse into a predetermined number of portions, and then to successively transmit the time-domain transformed versions of these various portions. The received echoes are then processed with a modified version of the fd algorithm. Our analysis and simulations show that the proposed waveform can be characterized by a PSLR and an ISLR close to those of the SCPC processed with MF in some scenarios. (C) 2019 Elsevier Inc. All rights reserved.
ECG (Electrocardiogram) signal real-time feature extraction meets the requirements of some smart cardiac home care systems which can automatically extract ECG feature outside the hospital. In this paper, we discuss a ...
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ISBN:
(纸本)9780769536057
ECG (Electrocardiogram) signal real-time feature extraction meets the requirements of some smart cardiac home care systems which can automatically extract ECG feature outside the hospital. In this paper, we discuss a real-time method based on fd (first derivative-based) algorithm and WTMM (wavelet transform modulus maxima) algorithm to detect the QRS complexes. The detection is accomplished by switching the two algorithms with comparing the feature against a threshold. This switching method has advantages of fd algorithm which avoids complicated computation and can realize accurate position of QRS complexes with WTMM algorithm. We use actual ECG signal data gathered from 3-Lead ECG signal gathering system with MATLAB as simulation platform. The result shows that it causes a good effect on the real-time feature extraction.
ECG (Electrocardiogram) signal real-time feature extraction meets the requirements of some smart cardiac home care systems which can automatically extract ECG feature outside the hospital. In this paper, we discuss a ...
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ECG (Electrocardiogram) signal real-time feature extraction meets the requirements of some smart cardiac home care systems which can automatically extract ECG feature outside the hospital. In this paper, we discuss a real-time method based on fd (first derivative-based) algorithm and WTMM (wavelet transform modulus maxima) algorithm to detect the QRS complexes. The detection is accomplished by switching the two algorithms with comparing the feature against a threshold. This switching method has advantages of fd algorithm which avoids complicated computation and can realize accurate position of QRS complexes with WTMM algorithm. We use actual ECG signal data gathered from 3-Lead ECG signal gathering system with MATLAB as simulation platform. The result shows that it causes a good effect on the real-time feature extraction.
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