© 2019 IEEE. In this paper, a Modified Multi-Class Support Vector Machines (MMC-SVM) technique is developed to simultaneously detect and classify different types of open-circuit faults in power distribution systems. This technique is capable of detecting and identifying open-circuit faults considering the impact of variations in the voltage of different nodes in power distribution systems. The RMS (Root Mean Square) voltage of the power grid is used as the input signal to diagnose the faults. Simulations are carried out on the IEEE 13-node test system considering temporary open-circuit faults in MATLAB software. The simulation results show the accuracy, effectiveness, and robustness of the proposed method
Bridging the gap between theoretical modeling and practical implementation is essential in fault det...
AbstractIn recent years, power quality has become the main concern in power system engineering. Clas...
International audienceThis paper presents and evaluates a methodology to detect and diagnose single ...
© 2019 IEEE. In this paper, a Modified Multi-Class Support Vector Machines (MMC-SVM) technique is de...
This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing...
Machine learning application have been widely used in various sector as part of reducing work load a...
A new approach for fault diagnosis in power grids is presented in this paper. The approach is capabl...
Fault detection and location are important and front-end tasks in assuring the reliability of power ...
Short circuit is one of the most popular types of permanent fault in power distribution system. Thus...
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and...
Power electronic circuits (PECs) are prone to various failures, whose classification is of paramount...
Power electronic circuits (PECs) are prone to various failures, whose classification is of paramount...
Click on the DOI link to access the article (may not be free).The smart grid initiative requires sel...
After renewable energy distributed generator (DG) is connected to the power grid, traditional divers...
Electrical faults in the distribution network can lead to interruptions in the power supply of the c...
Bridging the gap between theoretical modeling and practical implementation is essential in fault det...
AbstractIn recent years, power quality has become the main concern in power system engineering. Clas...
International audienceThis paper presents and evaluates a methodology to detect and diagnose single ...
© 2019 IEEE. In this paper, a Modified Multi-Class Support Vector Machines (MMC-SVM) technique is de...
This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing...
Machine learning application have been widely used in various sector as part of reducing work load a...
A new approach for fault diagnosis in power grids is presented in this paper. The approach is capabl...
Fault detection and location are important and front-end tasks in assuring the reliability of power ...
Short circuit is one of the most popular types of permanent fault in power distribution system. Thus...
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and...
Power electronic circuits (PECs) are prone to various failures, whose classification is of paramount...
Power electronic circuits (PECs) are prone to various failures, whose classification is of paramount...
Click on the DOI link to access the article (may not be free).The smart grid initiative requires sel...
After renewable energy distributed generator (DG) is connected to the power grid, traditional divers...
Electrical faults in the distribution network can lead to interruptions in the power supply of the c...
Bridging the gap between theoretical modeling and practical implementation is essential in fault det...
AbstractIn recent years, power quality has become the main concern in power system engineering. Clas...
International audienceThis paper presents and evaluates a methodology to detect and diagnose single ...