Prediction Model for Power Transmission Line Icing Load Based on Data-driven

被引：4
|
作者：
Li, Peng [1 ]
Li, Ning [1 ]
Li, Qimao [1 ]
Cao, Min [2 ]
Chen, Huoxing [2 ]
机构：
[1] Yunnan Univ, Sch Informat Sci & Engn, Kunming 650091, Peoples R China
[2] South Power Grid Corp, Yunnan Elect Power Res Inst, Kunming, Peoples R China
来源：
SMART MATERIALS AND INTELLIGENT SYSTEMS, PTS 1 AND 2 | 2011年 / 143-144卷
关键词：
prediction model; transmission line icing; data-driven; BP neural networks; FAULT-DETECTION; NEURAL-NETWORK;
D O I：
10.4028/www.scientific.net/AMR.143-144.1295
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
How to monitor and predict icing load of power transmission lines are important problems for the reliability of power grid. A model based on data-driven is presented here to predict the icing load of transmission line, which is available to forecast the icing disaster of it. The fitfulness, which influencing the prediction results of icing load, is analyzed and discussed in this paper. According to the results of simulation, this model has a good accuracy of prediction if the training data and prediction data are in the same icing process. If the icing process is not same but contiguous, it also can predict the degree of icing load qualitatively.
引用
收藏
页码：1295 / +
页数：2
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