Abstract
Icing forecasting for transmission lines is of great significance for anti-icing strategies in power grids, but existing prediction models have some disadvantages such as application limitations, weak generalization, and lack of global prediction ability. To overcome these shortcomings, this paper suggests a new conception about a segmental icing prediction model for transmission lines in which the classification of icing process plays a crucial role. In order to obtain the classification, a hierarchical K-means clustering method is utilized and 11 characteristic parameters are proposed. Based on this method, 97 icing processes derived from the Icing Monitoring System in China Southern Power Grid are clustered into six categories according to their curve shape and the abstracted icing evolution curves are drawn based on the clustering centroid. Results show that the processes of ice events are probably different and the icing process can be considered as a combination of several segments and nodes, which reinforce the suggested conception of the segmental icing prediction model. Based on monitoring data and clustering, the obtained types of icing evolution are more comprehensive and specific, and the work lays the foundation for the model construction and contributes to other fields.
Highlights
Loads induced by atmospheric icing on transmission lines may lead to ice flashover, conductor galloping, even conductor breakage, tower collapse, etc., seriously threatening the reliability of the power supply and integrity of the power transmission infrastructure [1,2]
The prediction of ice accretion on transmission lines is of great significance for electric power companies at risk to get prepared and take appropriate preventative measures [14]
In order to overcome the problems of existing models, we put forward a new conception of a segmental icing prediction model and focused on the first step of model construction, namely, studying the types of icing evolution
Summary
Loads induced by atmospheric icing on transmission lines may lead to ice flashover, conductor galloping, even conductor breakage, tower collapse, etc., seriously threatening the reliability of the power supply and integrity of the power transmission infrastructure [1,2]. Ice storms have caused great damage to electric power systems and huge economic losses to citizens at home and abroad, such as China [3,4], America [5], Canada [6,7], Germany [8], Japan [9], Iceland [10], Sweden [11], Czech Republic [12], and so on, for over 50 years. As an increasing number of ultra-high voltage transmission lines pass through heavy icing areas in China [13], the online monitoring on transmission lines alone could not satisfy the demands of anti-icing in power grids. The prediction of ice accretion on transmission lines is of great significance for electric power companies at risk to get prepared and take appropriate preventative measures [14]. The purpose of icing forecasting is to predict ice thickness following some certain methods or rules based on existing information for grasping the course of the ice event in advance
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