Transmission line condition assessment technology based on multi-source Parameter Fusion

Abstract

Aiming at the shortcomings of current transmission line state evaluation, which refers to the isolation of scalars and the low accuracy of evaluation methods, a transmission line state evaluation technology based on multi-source parameter fusion is proposed. This paper collects and selects characteristic data such as line test inspection information, operation and maintenance records, and power grid operating parameters as indicator quantities. The membership function is used to express the distribution state of the index quantity, and the distribution state is used as the data to establish a comprehensive evaluation model of the line operation state based on the long- and short-term memory network. The data tag is used to train the deep network to establish the mapping relationship between index parameters and operation state. Experiments show that the evaluation accuracy of the proposed method is significantly higher than that of the traditional shallow method, which can provide theoretical guidance for the operation and maintenance of overhead transmission lines.