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| Assessment Method for Outages of Iced Regional Power Grid Lines |
| Wang Zengping, Cao Chen, Wang Tong |
| State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing 102206 China |
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Abstract Relevant statistics show that ice disasters have become a leading cause of prolonged large-scale outages in regional power grids in China during winter, with severe associated damage. Research on assessment method for outages of iced transmission lines can help the power grid operation and maintenance departments to take targeted preventive protection and control measures, ensuring the safe and stable operation of the power grid. However, existing studies often overlook the structural design differences and dynamic response states of lines within regional power grids, and lack in-depth analysis of the impact of regional ice disaster statistical characteristics, which result in poor interpretability and low reliability. To address the above issues, this paper proposes a dual-driven by model and statistics assessment method for outages in iced regional power grid lines. Firstly, models for ice accretion growth as well as wind and ice loads on conductors and towers are developed from the perspective of icing mechanisms, enabling precise characterization of load variations in ice- covered transmission lines. Secondly, fully considering the structural differences and dynamic response states of lines, finite element models are developed for various tower types of 110 kV lines, and the disaster-causing mechanism of tower collapse under ice disaster conditions is analyzed from the perspective of dynamic response. On this basis, probabilistic expressions for conductor breakage and tower collapse failures are derived using fragility theory. Then, leveraging the joint statistical characteristics within the observable frequency range of regional ice disasters, the single-line outage model, which reflects only structural factors, is extended to the regional power grid level from a model-and statistics-driven perspective, enabling a scientific assessment of outages in ice-covered regional power grids. Finally, real meteorological data from the 2008 ice disaster in southern China are utilized to construct a simulation scenario. Spatial interpolation technology based on co-kriging method is applied to simulate meteorological conditions within the regional power grid, and fault analysis is then conducted for the actual power system in southern Hunan Province, China. In the simulation section, multiple comparative schemes are designed to sequentially verify the accuracy, effectiveness, and interpretability of the proposed assessment method. The calculated outage probabilities indicate that the dynamic response states of conductors and towers and the joint statistical characteristics of extreme disasters are key indicators for intuitively reflecting the actual structural damage. Moreover, the failure probability of different tower types can vary by up to 43.8% under the same wind-ice intensity. Compared with traditional methods based on static stress analysis or statistical data analysis, the proposed assessment method can more accurately capture the outage probability trends of ice-covered lines under the coupled impact of wind and ice loads. The following conclusions can be drawn from the study: (1) The proposed structural failure probability calculation method based on vulnerability theory establishes a mapping relationship between the dynamic response of ice-covered conductors and towers and their failures, accurately describing the actual damage to ice-covered line structures. (2) In terms of interpretability, accuracy, and reliability, the proposed dual-driven assessment method surpasses existing models. (3) Structural failure characteristics are significantly influenced by design differences and regional monsoons. Both the internal failure mechanisms of the structures and the statistical characteristics of external disasters should be fully considered.
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Received: 07 October 2024
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