Title :
An ice-coating predict system of transmission lines based on the improved neural network
Author :
Zhou, Jing ; Gu, Longfei ; Lai, Zhengtian ; Teng, Jing
Author_Institution :
Sch. of Control & Comput. Eng., North China Electr. Power Univ., Beijing, China
Abstract :
Due to the various weather conditions and the diverse geographical environments, ice disaster is unavoidable in many regions of China. The phenomena of ice-coating lead to quick and massive increment of the weight of transmission lines, resulting in wire breakage, tower toppling, flashover and other accidents. Therefore, it is of great significance to improve the capability of predicting and combating these serious disasters. This paper proposes to predict the thickness of ice-coating using an improved neural network. Based on analysis of the near-term meteorological parameters, including temperature, humidity and wind velocity, etc., problems in electricity transmission are effectively predicted and prevented.
Keywords :
disasters; ice; meteorology; neural nets; power engineering computing; power transmission lines; prediction theory; electricity transmission lines; ice disaster; ice-coating predict system; neural network; tower toppling; wire breakage; Indium tin oxide; Presses; Ice disaster; Ice-coating predict; Neural network; Transmission lines;
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
DOI :
10.1109/ICICISYS.2010.5658332