Research On Differential State Evaluation Of Overhead Transmission Lines Based On Fuzzy Neural Network

With the continuous improvement of China’s requirements for the stability of national production and life,higher requirements have also been imposed on the safe and reliable power supply of power systems.The operation and maintenance of overhead transmission lines and their equipment,as a key link to ensure the reliability of power systems,have also received more attention and requirements from power companies.Based on the accumulation of a large number of historical operating data of the power system,the combination of historical data and data analysis algorithms to obtain an intelligent state evaluation system for overhead transmission lines is a current research hotspot.Aiming at the construction of the overall system for the evaluation of the status of overhead transmission lines,this paper focuses on the operating status of the transmission equipment,and establishes a multi-level status evaluation model.The operating status of the line,and the results of the state evaluation of the transmission equipment are determined by indicators such as the line inspection records obtained by the operation and maintenance personnel and the equipment operating data obtained by the online monitoring equipment.Hierarchical relationship of states.In this progressive relationship,the research focuses on the selection of equipment evaluation indicators,the construction of equipment status evaluation models,and the construction of the overall line status evaluation model based on the equipment operating status.Based on the guidelines for the evaluation of overhead power transmission conditions,this article establishes a basic parameter system for the evaluation indicators of overhead power transmission equipment.It combines historical data and association rules to quantify the relationship between the basic parameters and equipment status evaluation.The system of key indicators for power transmission equipment status evaluation has realized the elimination of redundant indicators and established a highly correlated standardized input system.This paper combines historical defect records,uses association rules and principal component analysis to select key index quantities as inputs to the state assessment model,and establishes an expert system for the state assessment of transmission equipment based on fuzzy mathematics and expert experience.Defect samples in the records verify the feasibility of the fuzzy expert system.In this paper,the fuzzy expert system is used to drive the training of BP neural network,and the Levenberg-Marquardt algorithm is used for network training.An intelligent operation and maintenance platform for transmission lines based on artificial neural network is constructed.Test samples prove that the model can accurately identify defects.Based on the results of equipment evaluation,based on historical defect data and analytic hierarchy process,the basic weight of transmission equipment to the overall operating status of the line is established.And with the help of mathematical model fitting,the optimization of the operating life,the external environment,and the operating section is achieved to obtain the overall operating status of the transmission line.The reliability of the differential state evaluation model in this paper is verified by the 220 k V Shanhui A line as an evaluation case.As a part of line operation and maintenance,the status evaluation of transmission lines is to provide relevant guidance for the formulation of maintenance strategies.In the future,further research on the optimization of maintenance strategies for overhead transmission lines based on the results of condition evaluation and the decision-making of material deployment schemes are required to reduce maintenance Cost,promote economic maintenance of power companies.