Prospect of Photovoltaic System Safety Monitoring and Fault Diagnosis Technology Based on PV Cloud Data Platform

2018 ◽  
Author(s):  
Zhongfeng Wang ◽  
Jing Bian ◽  
Peng Ji ◽  
Jun Liu ◽  
Yonghua Zhang ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Safety Monitoring ◽  
Photovoltaic System ◽  
System Safety ◽  
Cloud Data ◽  
Data Platform

scholarly journals Fault Diagnosis and Trace Method of Power System Based on Big Data Platform

2018 ◽  
Vol 394 (4) ◽  
pp. 042116 ◽  
Author(s):  
Lei Wang ◽  
Lingling Shang ◽  
Mengchao Ma ◽  
Zhiguang Ma
Keyword(s):  
Big Data ◽  
Fault Diagnosis ◽  
Power System ◽  
Data Platform

scholarly journals Study of Intelligent Photovoltaic System Fault Diagnostic Scheme Based on Chaotic Signal Synchronization

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Chin-Tsung Hsieh ◽  
Jen Shiu
Keyword(s):  
Fault Diagnosis ◽  
Embedded System ◽  
Dynamic Error ◽  
Chaotic Signal ◽  
Labor Cost ◽  
Photovoltaic System ◽  
Classical Domain ◽  
Voltage Signal ◽  
Signal Synchronization ◽  
Dynamic Errors

As the photovoltaic system consists of many equipment components, manual inspection will be very costly. This study proposes the photovoltaic system fault diagnosis based on chaotic signal synchronization. First, MATLAB was used to simulate the fault conditions of solar system, and the maximum power point tracking (MPPT) was used to ensure the system's stable power and capture and record the system fault feature signals. The dynamic errors of various fault signals were extracted by chaotic signal synchronization, and the dynamic error data of various fault signals were recorded completely. In the photovoltaic system, the captured output voltage signal was used as the characteristic values for fault recognition, and the extension theory was used to create the joint domain and classical domain of various fault conditions according to the collected feature data. The matter-element model of extension engineering was constructed. Finally, the whole fault diagnosis system is only needed to capture the voltage signal of the solar photovoltaic system, so as to know the exact fault condition effectively and rapidly. The proposed fault diagnostor can be implemented by embedded system and be combined with ZigBee wireless network module in the future, thus reducing labor cost and building a complete portable renewable energy system fault diagnostor.

scholarly journals Chaotic Extension Neural Network-Based Fault Diagnosis Method for Solar Photovoltaic Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Kuo-Nan Yu ◽  
Her-Terng Yau ◽  
Jian-Yu Li
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Photovoltaic System ◽  
Photovoltaic Systems ◽  
Solar Photovoltaic ◽  
Error Back Propagation ◽  
Point Tracking ◽  
Diagnosis Method

At present, the solar photovoltaic system is extensively used. However, once a fault occurs, it is inspected manually, which is not economical. In order to remedy the defect of unavailable fault diagnosis at any irradiance and temperature in the literature with chaos synchronization based intelligent fault diagnosis for photovoltaic systems proposed by Hsieh et al., this study proposed a chaotic extension fault diagnosis method combined with error back propagation neural network to overcome this problem. It used the nn toolbox of matlab 2010 for simulation and comparison, measured current irradiance and temperature, and used the maximum power point tracking (MPPT) for chaotic extraction of eigenvalue. The range of extension field was determined by neural network. Finally, the voltage eigenvalue obtained from current temperature and irradiance was used for the fault diagnosis. Comparing the diagnostic rates with the results by Hsieh et al., this scheme can obtain better diagnostic rates when the irradiances or the temperatures are changed.

scholarly journals Fault diagnosis and isolation based on Neuro-Fuzzy models applied to a photovoltaic system

2021 ◽  
Vol 54 (14) ◽  
pp. 358-363
Author(s):  
Raquelita Torres Cabeza ◽  
Alain Segundo Potts
Keyword(s):  
Fault Diagnosis ◽  
Photovoltaic System ◽  
Fuzzy Models ◽  
Neuro Fuzzy

scholarly journals Design and Implementation of Substation Operation Safety Monitoring and Management System Based on Three-Dimensional Reconstruction

2020 ◽  
Author(s):  
Yingyi Yang ◽  
Hao Wu ◽  
Fan Yang ◽  
Xiaoming Mai ◽  
Hui Chen
Keyword(s):  
Management System ◽  
Point Cloud ◽  
Control Level ◽  
Three Dimensional ◽  
Safety Monitoring ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Operational Risks ◽  
Dimensional Reconstruction ◽  
3D Scene

In order to reduce operational risks and to improve the risk management and control level in substation, a substation operation safety monitoring and management system (3D2S2M) has been structured based on three-dimensional (3D) laser modeling technology. In this paper, we introduce how to build such a system and to describe its implementation details. A 3D lidar scanning technology is used to perform a holographic scan of the whole internal area in a substation to obtain color point cloud data of buildings and all equipment. Then, a novel 3D visualization safety monitoring and management system, named 3D2S2M, is developed by performing a 3D reconstruction of the point cloud data. Based on the real 3D scene model of 3D2S2M, the method of 3D distance measurement is used to replace manual on-site investigation for improving operation and maintenance efficiency. In addition, a real-time high-accuracy localization method is proposed, in order to identify and analyze the positioning and the behavior of the personnel, and the movement trajectory of the equipment. By combining positioning information and the electronic fence that used in 3D2S2M, risk levels of the personnel (or equipment) are evaluated and the corresponding alarm is issued to prevent dangerous behavior, thereby the operation risk is reduced in substation.

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