台风环境下考虑地理高程信息的输电通道结构失效故障概率评估方法

Evaluation of the Failure Probability of Power Transimmision Corridors During Typhoons Using Digital Elevation Information

暴露于外部环境的电网输电通道极易受到台风灾害的影响。为提高电网抵御台风的能力,提出一种基于地理高程信息的短时输电通道结构失效概率评估方法。首先,基于我国东南某省1949年以来至今历史所有台风进行预测误差统计分析,证明在短时尺度内台风路径的朴素预测优于气象学常用的路径相似性预测,即朴素预测更适合于电网对即将登陆的台风路径进行短时预测。其次,基于朴素预测的半径与角度的预测误差概率分布采用接受拒绝法进行抽样,解决了台风路径历史样本数过少的问题,进而生成台风预测路径辐射域。同时,将全球地理高程信息与电网输电通道路径地理信息相融合,对输电杆塔的承载风速进行高度修正。最后,提出经分析表明风速与失效率之间的关系不是简单的线性变化而是存在突变的,与线性失效率曲线相比指数型失效率曲线对输电杆塔失效概率评估更切合实际灾损结果。算例以2016年莫兰蒂台风下的东南某省电网输电通道实际灾损情况进行实例分析,验证了方法的实用性与有效性。

Power transmission corridors are exposed to external environment, hence they are susceptible to be affected by typhoons. In order to improve the reliability of power grids during typhoons, this paper proposes a method employs failure probability assessment of short-time power transmission corridors based on digital elevation information. Firstly, by conducting statistical analysis of all historical typhoons that have occurred in a province situated in Southeastern China since 1949, it proves that in a short time, the simple prediction of typhoon tracks is better than the similarity prediction method commonly used in meteorological stations. It is therefore conclusive to say this simple prediction method is more suitable for power grids to forecast typhoon tracks that are coming within a short time. Secondly, as the probability distribution of predictive error of radius and angle based on simple prediction is sampled by accept-rejection method, the problem of inadequate samples regarding historical data of typhoon tracks is resolved and then it creates the predicted area of typhoon tracks. At the same time, the global geographical elevation information is integrated with the geographic information of the transmission towers. With this geographical information, the wind load of the transmission towers is corrected by the altitude information of the tower. Lastly, this paper proves that the relationship between the wind speed and the failure rate does not work in a simple linear way, but change in mutation. Compared with the failure rate from a linear curve, the failure rate of an exponential curve may better depict the actual loss data of transmission towers. In case study, based on the analysis of the actual data loss in power transmission corridors under the influence of Meranti in 2016, it is verified that this method is effective and can be used pragmatically in an actual system operation.