Fault Detection in LV Distribution Networks Based on Augmented Complex Kalman Filter

Abstract

Low voltage distribution networks in the presence of distributed energy resources introduce new challenges in fault detection and protection system. While conventional protection schemes such as over current relays are not reliable in active distribution networks with low-frequency measurement devices, the monitoring and protection of active distribution networks with high tech measurements is currently not cost-effective. Moreover, the unpredictable customer loads behaviour decreases the accuracy of the protection schemes with fixed fault current thresholds. In order to overcome these issues, a new protection scheme based on the corrective error in augmented complex Kalman filter state estimation is proposed to detect shallow faults in low voltage distribution networks. Our empirical investigation shows a normal distribution with zero mean while the standard deviation is fitted on the corrective error in distribution network state estimator, where the calculated standard deviation determines a threshold for fault detection. An unexpected rise in the corrective error over the fault threshold can be considered as a fault in the distribution network. In order to evaluate the performance of the proposed method in this paper, one thousand fault scenarios in a radial distribution network with six-buses is examined, using real measured customer loads data.