Application of neural- network technology to compute the temperature distribution in radial direction of a composite overhead transmission line in steady state is the main object of this work. The accumulation of dust around the line will cause additional temperature rises and will reduce the hypothetical lifetime of the line. The ampacity of the dusty lines should be reduced to suggest an actual ampacity in order that the temperature of the lines doesn’t exceed the maximum permissible temperature and to maintain the hypothetical lifetime of the lines. Artificial neural networks have been designed to obtain the temperature distribution in a line; its equivalent resistance and the power dissipated in it for specified values of the dust-layer thickness and the line current. The percentage reduction coefficients of both lifetime and rating current of the line in addition to the suggested modified line current can also be computed by using the designed network. Input and output patterns have been provided for training the designed networks.

Keywords

Thermal rating of transmission lines, Temperature distribution, Ampacity of lines, Lifetime of transmission lines, Dusty lines, Artificial neural networks, Back propagation algorithm.