ABSTRACT
The detection and location of faults on power transmission lines is essential to the protection and maintenance of a power system. Most methods of fault detection and location rely on measurements of electrical quantities provided by current and voltage transformers. In this work, current sensors and voltage sensors were used in the prototyped model of the data collection device. Training data were collected by taking into consideration variables of a simulation situation like fault type, sensor location on the node, short circuit and open circuit faults were also analyzed. The test data were analyzed using three machine learning classifiers namely: K- Nearest Neighbor (KNN), Decision Tree and Support Vector Machines (SVM). Simulation result indicates that the anticipated method for fault classification gives high accuracy (99.5%) and least fault distance estimation error (0.5%) for all discussed cases. In order to verify the accuracy of the proposed method, a comparison is carried out with decision tree (DT), KNN and SVM. Separate investigation was also carried out with testing the system by varying the load at the range of 0%- 100%. It is observed from the test results of the network model that, the fault detection, location and classification gives a high accuracy with machine learning decision tree giving a quick training time response of 0.000999928 seconds.
DZABENG, N (2021). Design And Development of Power Distribution Network Fault Data Collection Device, Fault Detection, Location And Classification Using Machine Learning Algorithms. Afribary. Retrieved from https://afribary.com/works/design-and-development-of-power-distribution-network-fault-data-collection-device-fault-detection-location-and-classification-using-machine-learning-algorithms
DZABENG, NICHOLAS "Design And Development of Power Distribution Network Fault Data Collection Device, Fault Detection, Location And Classification Using Machine Learning Algorithms" Afribary. Afribary, 17 Apr. 2021, https://afribary.com/works/design-and-development-of-power-distribution-network-fault-data-collection-device-fault-detection-location-and-classification-using-machine-learning-algorithms. Accessed 29 Apr. 2024.
DZABENG, NICHOLAS . "Design And Development of Power Distribution Network Fault Data Collection Device, Fault Detection, Location And Classification Using Machine Learning Algorithms". Afribary, Afribary, 17 Apr. 2021. Web. 29 Apr. 2024. < https://afribary.com/works/design-and-development-of-power-distribution-network-fault-data-collection-device-fault-detection-location-and-classification-using-machine-learning-algorithms >.
DZABENG, NICHOLAS . "Design And Development of Power Distribution Network Fault Data Collection Device, Fault Detection, Location And Classification Using Machine Learning Algorithms" Afribary (2021). Accessed April 29, 2024. https://afribary.com/works/design-and-development-of-power-distribution-network-fault-data-collection-device-fault-detection-location-and-classification-using-machine-learning-algorithms