应用灰色方法预测超高压输电线路的可听噪声

Prediction of Audible Noise for EHV Transmission Line Based on Grey Theory

超高压输电中,输电线下的可听噪声大小是导线选择的主要因素,所以可听噪声的预测十分重要。针对超高压输电线路可听噪声影响因素多的问题,运用灰色关联分析对影响可听噪声的环境因素、地理参数、导线结构参数等13个因素进行简化。通过分析选取影响输电线可听噪声的主要因素,建立基于灰色关联分析的灰色GM(1,9)和GM(0,9)预测模型。通过计算,得出GM(1,9)的预测精度最高,误差很小,其预测精度优于BP神经网络。和其他预测方法相比,灰色预测比较实用、有效,精度较高,可作为预测超高压输电线路可听噪声的一种简单有效的方法。

In EHV power transmission, the value of audible noise under transmission lines is one of the main parameters for selection of conductor, so prediction of this audible noise is rather important in planning and constructing EHV transmission lines. In this paper, thirteen factors influencing the audible noise,such as environmental factor,geographical parameter and conductor＇s structural parameter, are simplified using the grey-correlation analysis. The grey GM（1,9） and GM（0,9） prediction models based on the grey-correlation analysis are established through selecting main factors from the thirteen ones. Calculations indicate that the GM（1,9） model possesses higher prediction accuracy and smaller error, and its prediction accuracy is higher than that of BP neural network. Compared with other methods, the grey model is more effective with a higher degree of precision for audible noise prediction of EHV transmission lines.