Fault detection algorithm of the photovoltaic system using wavelet transform

Electrical issues such as old wires and faulty connections are the most common causes of arc faults. Arc faults cause electrical fires by generating high temperatures and discharging molten metal. Every year, such fires cause a considerable deal of destruction and loss. This paper proposes a new method for detecting residential series and parallel arc faults. A simulation model for the arc is employed to simulate the arc faults in series and parallel circuits. The fault features are then retrieved using a signal processing approach called Discrete Wavelet Transform (DWT) designed in MATLAB/Simulink based on the fault detection algorithm. Then db2 and one level were found appropriate mother and level of wavelet transform for extracting arc-fault features. MATLAB Simulink was used to build and simulate the arc-fault model.

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Novel DC Line-to-Ground Fault Detection Algorithm for High Voltage Direct Current System Connected to Floating Photovoltaic System

Science of Advanced Materials ◽

10.1166/sam.2018.2951 ◽

2018 ◽

Vol 10 (1) ◽

pp. 149-153

Author(s):

Hyun Jae Yoo ◽

Myong-Chul Shin ◽

Jae Hyeong Lee ◽

Young Kwan Choi

Keyword(s):

Fault Detection ◽

High Voltage ◽

Direct Current ◽

Current System ◽

Detection Algorithm ◽

Photovoltaic System ◽

High Voltage Direct Current ◽

Ground Fault ◽

Dc Line ◽

Ground Fault Detection

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FAULT DETECTION ALGORITHM USING DCS METHOD COMBINED WITH FILTERS BANK DERIVED FROM THE WAVELET TRANSFORM

Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics ◽

10.5220/0001640802260231 ◽

2007 ◽

Keyword(s):

Wavelet Transform ◽

Fault Detection ◽

Detection Algorithm

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Threshold value of DC array current and DC string voltage for fault detection in grid-connected photovoltaic system

Scientific Research Journal ◽

10.24191/srj.v17i1.6314 ◽

2020 ◽

Vol 17 (1) ◽

pp. 1

Author(s):

Nurmalessa Muhammad ◽

Nor Zaini Ikrom Zakaria ◽

Sulaiman Shaari ◽

Ahmad Maliki Omar

Keyword(s):

Fault Detection ◽

Failure Detection ◽

Threshold Value ◽

Detection Algorithm ◽

Green Energy ◽

Photovoltaic System ◽

Energy Output ◽

Climate Data ◽

Pv System ◽

Loss Analysis

The failure detection in a grid-connected photovoltaic (PV) system has become an important aspect of solving the issue of the reduced energy output in the PV system. One of the methods in detecting failure is by using the threshold-based method to compute the ratio of actual and predicted DC array current and DC string voltage value. This value will be applied in the failure detection algorithm by using power loss analysis and may reduce the time, cost and labour needed to measure the quality of the energy output of the PV system. This study presented the threshold value of DC array current and DC string voltage to be implemented in the algorithm of fault detection in grid-connected photovoltaic (PV) system under the Malaysian climate. Data from the PV system located at Green Energy Research Center (GERC) was recorded in 12 months interval using the monocrystalline PV modules. The actual data was recorded using five minutes interval for 30 consecutive days. The prediction of the data was calculated using the mathematical method. The threshold value was determined from the ratio between actual and predicted data. The results show that the DC array current threshold value, σ is 0.9816. While, DC string voltage threshold value, λ is 0.9261. The proposed value may be beneficial for the determination of threshold value for regions with the tropical climate.

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Fault Detection of the Power System Based on the Chaotic Neural Network and Wavelet Transform

Complexity ◽

10.1155/2020/8884786 ◽

2020 ◽

Vol 2020 ◽

pp. 1-15

Author(s):

Zuoxun Wang ◽

Liqiang Xu

Keyword(s):

Neural Network ◽

Wavelet Transform ◽

Fault Detection ◽

Power System ◽

Fault Location ◽

Detection Algorithm ◽

Travelling Wave ◽

Discrete Wavelet ◽

Chaotic Neural Network ◽

Transition Resistance

The safety and stability of the power supply system are affected by some faults that often occur in power system. To solve this problem, a criterion algorithm based on the chaotic neural network (CNN) and a fault detection algorithm based on discrete wavelet transform (DWT) are proposed in this paper. MATLAB/Simulink is used to establish the system model to output fault signals and travelling wave signals. Db4 wavelet decomposes the travelling wave signals into detail signals and approximate signals, and these signals are combined with the two-terminal travelling wave location method to achieve fault location. And the wavelet detail coefficients are extracted to input to the proposed chaotic neural network. The results show that the criterion algorithm can effectively determine whether there are faults in the power system, the fault detection algorithm has the capabilities of locating the system faults accurately, and both algorithms are not affected by fault type, fault location, fault initial angle, and transition resistance.

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Fault detection technique for modified cascaded half-bridge multi-level inverter with polarity changer in pv grid system

SN Applied Sciences ◽

10.1007/s42452-021-04586-5 ◽

2021 ◽

Vol 3 (5) ◽

Author(s):

Ujjval B Vyas ◽

Varsha A Shah ◽

Srivani S G

Keyword(s):

Fault Detection ◽

Search Algorithm ◽

High Reliability ◽

Gravitational Search Algorithm ◽

Detection Algorithm ◽

Open Circuit ◽

Fault Isolation ◽

Photovoltaic System ◽

Harmonic Elimination ◽

The Cost

AbstractMultilevel Inverters (MLI) are a viable option for a filter-less and transformerless photovoltaic system for direct grid integration, reducing losses, space and cost provided the issues of control and reliability are resolved. A modified cascaded half-bridge MLI with polarity changer is proposed with a reduced number of switches, thereby reducing control complexity. The proposed converter is designed for both seven-level and nine-level topologies. Selective harmonic elimination has been adopted to switch converter and the transcendental equations are solved by the gravitational search algorithm. The THD for nine-level configuration is 7.94% and 5.86% with MPPT and DC source inputs, respectively. The analysis on the open-circuit fault of switches confirms the presence of only five critical switches irrespective of the number of increase in levels, thereby requiring only five redundant switches at the Polarity Changer. The output voltage waveform is subjected to multiresolution analysis for feature extraction of voltages under various irradiance and temperature conditions. A conditions based fault detection algorithm is developed based on the observations of energies of signals to detect the open circuit fault in switches. Based on the comparative analysis, the proposed converter has fewer controlled switches for nine levels or higher configurations than other topologies. Apart from this, the high reliability due to inherent fault isolation capability restricted to half-bridge compared to different MLI topologies shows its superiority. For a nine-level MLI proposed topology reduces the cost considering redundancies for FDI in range of 67–30% depending on the topology for comparision. The system is simulated using MATLAB –Simulink and further validated by experimental results.

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