Discussion on multi-condition load capacity evaluation algorithm of transmission line based on fusion algorithm

ABSTRACT

High temperature, strong wind, ice cover and other problems may lead to transmission line breakage, tripping, tower toppling and so on. In order to reduce the probability of such problems, it is necessary to predict the load capacity of transmission line in multiple working conditions. In order to improve the accuracy of load capacity prediction of transmission lines under multiple working conditions and reduce the occurrence of bad transmission line problems, Particle Swarm Optimisation-Back Propagation neural network algorithm is used to simulate the prediction of transmission lines under different working conditions with different accuracy. The results show that the error of the optimised fusion algorithm is smaller than that of the pre-optimised algorithm. Combined with the prediction error results of the traditional neural network, it is found that the fusion algorithm can improve the prediction effect of transmission lines, has strong robustness, and can be popularised in practice.

KEYWORDS:

• Transmission line
• PSO-BP neural network
• multiple working conditions
• load capacity assessment

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work is supported by State Grid Shanxi Electric Power Company Science and Technology Project [52051020008A].