Adaptive Leakage Protection for Low-Voltage Distribution Systems Based on SSA-BP Neural Network

Abstract

The fluctuation of normal leakage current has a great influence on the fixed-threshold leakage protector. To address this issue, this paper proposes an adaptive leakage protection method based on the sparrow search algorithm (SSA)-backpropagation (BP) neural network. Based on the analysis of the normal leakage current generation mechanism, this method uses the SSA optimized BP neural network to construct a prediction model of normal leakage current. By dividing the normal leakage range into several intervals and setting the corresponding action threshold, the action threshold of the interval is automatically selected in advance, based on the predicted value of the model, so as to realize the adaptive protection of the leakage current faults. Experiments have proved that the leakage protector can identify the leakage fault more sensitively and increase the ratio of the protector put into operation by predicting the development of normal leakage current and adjusting the protection action threshold in advance.

Keywords

• leakage protection
• adaptive adjustment
• SSA-BP neural network
• normal leakage current prediction
• leakage fault