Abstract
Accurate warning information of potential fault risk in the distribution network is essential to the economic operation as well as the rational allocation of maintenance resources. In this paper, we propose a fault risk warning method for a distribution system based on an improved RelieF-Softmax algorithm. Firstly, four categories including 24 fault features of the distribution system are determined through data investigation and preprocessing. Considering the frequency of distribution system faults, and then their consequences, the risk classification method of the distribution system is presented. Secondly, the K-maxmin clustering algorithm is introduced to improve the random sampling process, and then an improved RelieF feature extraction method is proposed to determine the optimal feature subset with the strongest correlation and minimum redundancy. Finally, the loss function of Softmax is improved to cope with the influence of sample imbalance on the prediction accuracy. The optimal feature subset and Softmax classifier are applied to forewarn the fault risk in the distribution system. The 191-feeder power distribution system in south China is employed to demonstrate the effectiveness of the proposed method.
Highlights
As the last step in the power industry, the distribution system is closely and directly connected to end-users [1, 2].e stable operation of the distribution system is crucial to the reliable power supply for users [3,4,5]
Since the causal relationship is nonlinear, the conventional fault prediction method based on the electrical mechanism is challenging to function. erefore, exploring the potential risks in the distribution system operation process and furtherly taking corresponding measures have become a severe challenge to power supply companies [6, 7]
Literature [29] presented a fault risk warning method of the distribution system based on improved support vector machine algorithm
Summary
As the last step in the power industry, the distribution system is closely and directly connected to end-users [1, 2]. Literature [29] presented a fault risk warning method of the distribution system based on improved support vector machine algorithm. Literature [31, 32] introduces the overall structure of a distribution operation analysis system and expands the application of the massive fault data to the fault risk level prediction and weak spot identification. A fault warning method based on improved RelieF-Softmax algorithm for the distribution system is proposed. Taking 191 feeder lines in south China as examples, the analysis results demonstrate the effectiveness of the fault risk warning method proposed in this paper, which can provide crucial guiding significance to the operation practice.
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