Abstract. With the purpose of predicting icing of transmission lines, a model updating approach is presented in this study. The changes of structural dynamic response of transmission lines that is caused by icing is studied firstly by using finite element method. Then, model updating method and particle swarm optimization is implemented to indentify the thickness of icing according to the alternation of natural frequencies. The results show that the proposed methodology is meaningful to monitor line icing. IntroductionIcing of transmission lines would cause line galloping, insulator flashover and even tower collapse which is a great threat for the operation of power grid [1-2]. Thus, effective monitoring and condition assessment of line icing is the key issue which needs to be solved, and the establishment of icing forecast plays an important role in the operation of power grid.It's very difficult to evaluate the condition of lines manually considering that transmission lines are located sparsely. Hence, the on-line monitoring technique has attracted increasing attentions in engineering application. The current monitoring strategy are mainly based on measuring the weight, angle of insulator, wind speed, temperature and humidity. The equivalent thickness of line icing can be estimated according to measured data [3][4][5], based on that, related staff will be alerted as long as the thickness evaluated beyond a predefined value. However, the actual icing condition is usually distributed non-uniformly along the length of line, thus, the monitoring technique based on the evaluation of equivalent thickness is unable to get more information of icing distribution in details. In this work, a methodology for icing forecasting based on model updating method is presented. The modal frequencies are introduced to identify the icing condition of transmission lines with the help of artificial intelligence technique, and the results show that the proposed approach is able to identify and predict the distribution of icing.

Abstract. Operation and maintenance management work of overhead transmission lines is related directly to safety and reliability of the power grid. As overhead transmission lines are a significant composition part of smart gird, improvement of the operation and maintenance of management is an important measure to support smart grid. This discussion of operation and maintenance of overhead transmission lines are carried out combined with the demand of the current situation and new information technologies. It is appointed that innovation and advancement of the operation and maintenance mode can be pushed forwarded fully by means of on-line monitoring, live detection technology and information technology according to status and assessment of the transmission lines. It is forwarded that deepening application of the information technology is the key to improve efficiency and quality of operation and maintenance of the line and improve management level of the with the big data technology.

With the development of industrial and information technology, the power users increasingly demand better power quality. Therefore, the power department needs to monitor power quality in real time, and timely take appropriate measures to adjust the power quality. To overcome the shortcomings of wired monitoring networks, based on wireless sensor networks technology, this paper presents a real-time monitoring system scheme. Experimental results show that the system is capable to remotely real-time monitor the grid power quality and conveniently provide reliable basis for optimizing grid operation.