Predictive Modeling of Transmission Line Parameters for Different Operating Conditions

This paper presents a transmission line parameter prediction model taking into account different operating conditions is proposed. This study combines the feature selection methods of mutual information and elastic networks, and uses deep learning-based time-series forecasting algorithms to propose two different prediction methods. The goal of this study is to improve the prediction accuracy to solve the problem that the accuracy of analyses and calculations of the power system are reduced by line parameters deviation due to the influence of environmental factors, changes in operating conditions, human errors and modeling inaccuracies, etc. and ensure high accuracy and high qualification rate of power system operational analysis in relevant regions.