摘要
输电线路覆冰会引发导线断股、杆塔折损等事故,严重威胁电网的安全运行,因此能否准确预测输电线路覆冰情况对电力系统的安全稳定运行具有重要意义.针对输电线路覆冰过程模型不易建立的问题提出了一种基于微气象的覆冰过程综合辨识方法.该方法涵盖了多项式回归模型、时间序列模型和机器学习模型,利用Matlab中的系统辨识工具箱和libsvm工具箱较为便捷和全面的对覆冰过程进行辨识与建模.首先对获取的数据进行预处理,然后选择合适的模型结构进行参数辨识得到初始模型,最后对初始模型进行验证得到最终辨识模型.实验表明,综合辨识方法能够实现对不同模型特点的输电线路覆冰过程进行精确预测,并且提高了输电线路覆冰预测模型建立的便捷性和全面性.
Transmission line icing trigger wire off shares, tower breakage and other accidents, a serious threat to the safe operation of the power grid, so accurately predict the transmission line icing conditions is important for the safe and stable operation of the power system. A comprehensive identification method based on the icing process of micro-meteorological transmission lines is proposed.The method includes polynomial regression model, time series analysis model and machine learning model, using Matlab system identification toolbox and libsvm toolbox is more convenient and comprehensive on icing identification and modeling. Firstly, the researchers process the acquired data, and then select the appropriate model structure for parameter identification to obtain the initial model.Finally ,the initial model is verified and the final identification model is obtained.Experiments show that the final identification model can predict the icing process of transmission lines and accurately reflect the actual ice weight of transmission lines, and improve the convenience and comprehensiveness of the model.
出处
《云南大学学报（自然科学版）》
CAS
CSCD
北大核心
2017年第6期937-945,共9页
Journal of Yunnan University(Natural Sciences Edition)
基金
国家自然科学基金(61364024)
云南省应用基础研究(2014FB112)
云南省教育厅基金重点项目(2015Z014)
关键词
输电线路
微气象
便捷性
全面性
覆冰预测
transmission line
micro meteorological
convenience
comprehensiveness
icing prediction
