Wavelet technique based islanding detection and improved repetitive current control for reliable operation of grid-connected PV systems

Pinto, Smitha Joyce; Panda, Gayadhar

doi:10.1016/j.ijepes.2014.11.008

Cited by 35 publications

(13 citation statements)

References 37 publications

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“…Solar energy is a good clean energy and it will never run out. With the development of technology, it has been used effectively gradually . Among them, photovoltaic power generation is the most effective way to use solar energy.…”

Section: Discussionmentioning

confidence: 99%

An active frequency drift method for island problem of grid‐connected photovoltaic power generation system

Zhou

Fang

2019

IEEJ Transactions Elec Engng

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Island problem in grid-connected photovoltaic power generation system has a large influence on the safety and reliability of system, which needs to be timely detected. In this article, the photovoltaic grid-connected generation and island problems were briefly introduced, and then active frequency drift (AFD) method for island detection was studied. It was found that AFD might affect the quality of output current. Therefore, an improved AFD method was proposed, which added a phase shift change to the original reference current. The simulation experiment suggested that the improved AFD method proposed in this article could detect the islanding problem in 0.1 s, and the total harmonic distortion of the output current was 1.62%, much less than that of the AFD method. The experimental results show that the improved AFD method has better performance in island detection, with high security and reliability, and is worth popularizing widely in photovoltaic grid-connected power generation systems.

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Section: Discussionmentioning

confidence: 99%

An active frequency drift method for island problem of grid‐connected photovoltaic power generation system

Zhou

Fang

2019

IEEJ Transactions Elec Engng

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“…Determining the appropriate wavelet type and the number of decompositions to be performed is of great importance in the detection of the disorders. Many studies have discussed the detection of disturbances by the WT-method and used different wavelet types [4][5][6]12,13].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Wavelet Types in DWT-based Power Quality Disturbance Detection Method

Yılmaz¹,

Bayrak²

2019

acperpro

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Power quality parameters are the limit values that allow an electrical device to function as intended without significant loss of performance and life expectancy. It is important to detect power quality disturbances quickly and reliably to ensure reliability and continuity of the power system. Today, unlike conventional methods, signal processing-based disturbance and fault detection methods have gained great importance. Wavelet transform (WT)-based disturbance detection methods are the most prominent among these methods. In this study, the performance of the discrete wavelet transforms (DWT)-based disturbance detection method used in the detection of voltage sag and voltage swell events were evaluated for different wavelet types. Process calculation load, response to event signal and performance values were compared for different wavelet types. The results will be an important source for the selection of appropriate wavelets in the methods using WTs.

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“…In spite of its capabilities in reducing and or even eliminating the NZD, it causes a large degradation of the power quality of the network, high functioning time, and increases the complexity of the system due to the additional controllers/power electronics equipment needed [17,18]. A comprehensive survey on active detection techniques can be found in [17][18][19][20][21][22]. The mainstream methods are passive methods, which are based on measuring certain parameters such as voltage, frequency, current, and harmonic distortion of signals at the point of common coupling (PCC) and comparing them with a given threshold value [17].…”

Section: Introductionmentioning

confidence: 99%

“…The mainstream methods are passive methods, which are based on measuring certain parameters such as voltage, frequency, current, and harmonic distortion of signals at the point of common coupling (PCC) and comparing them with a given threshold value [17]. The passive methods are moderately suitable due to their smooth execution, practical solutions and no effect on power quality [21][22][23][24][25], but they have some disadvantages such as threshold setting, large non-detection zones, high error detection rates, and low consistency in correctly detecting the islanding [22]. Over/under voltage, over/under frequency, overcurrent, voltage phase jump, rate of change of frequency, rate of change of power, and harmonic distortion schemes are the most common passive methods.…”

Section: Introductionmentioning

confidence: 99%

An Anti-Islanding Protection Technique Using a Wavelet Packet Transform and a Probabilistic Neural Network

et al. 2018

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This paper proposes a new islanding detection technique based on the combination of a wavelet packet transform (WPT) and a probabilistic neural network (PNN) for grid-tied photovoltaic systems. The point of common coupling (PCC) voltage is measured and processed by the WPT to find the normalized Shannon entropy (NSE) and the normalized logarithmic energy entropy (NLEE). Subsequently, the yield feature vectors are fed to the PNN classifier to classify the disturbances. The PNN is trained with different spread factors to obtain better classification accuracy. For the best performance of the proposed method, the precise analysis is done for the selection of the type of input data for the PNN, the type of mother wavelet, and the required transform level which is based on the accuracy, simplicity, specificity, speed, and cost parameters. The results show that, by using normalized Shannon entropy and the normalized logarithmic energy entropy, not only it offers simplicity, specificity and reduced costs, it also has better accuracy compared to other smart and passive methods. Based on the results, the proposed islanding detection technique is highly accurate and does not mal-operate during islanding and non-islanding events.

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Wavelet technique based islanding detection and improved repetitive current control for reliable operation of grid-connected PV systems

Cited by 35 publications

References 37 publications

An active frequency drift method for island problem of grid‐connected photovoltaic power generation system

An active frequency drift method for island problem of grid‐connected photovoltaic power generation system

Assessment of Wavelet Types in DWT-based Power Quality Disturbance Detection Method

An Anti-Islanding Protection Technique Using a Wavelet Packet Transform and a Probabilistic Neural Network

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