典型屋顶太阳能光伏板风压实测研究

Fullscale Measurement and Investigation of Wind Pressure Loadings on Typical Rooftop Photovoltaic Solar Panels

摘要:

对一栋多功能低层建筑平屋顶上的太阳能光伏板进行风压实测，根据风压时程特性选择适当的概率密度函数对各测点的风压系数进行非线性回归分析.运用6种概率密度函数对各测点的均值和极值（正极大值和负极小值）风压系数时程以及面积平均后的极值风压系数时程进行数值拟合，比较不同概率分布的拟合效果.回归分析结果表明：均值风压系数的概率分布近似无偏分布，t分布的拟合效果最好，其次是Logistic分布、正态分布、极值I型分布；负压极小值和正压极大值风压系数的概率分布分别为左偏分布和右偏分布，极值I型分布的拟合效果最好，其次是Lognormal分布和Gamma分布，而正态分布的拟合效果最差；最不利风压系数由极值负风压控制，即光伏板的风力由吸力主导；经面积平均后的最不利风压系数建议取值-2.3.

Abstract:

A fullscale measurement of wind pressure loadings was conducted on photovoltaic (PV) solar panels mounted on the flat roof of a multipurpose lowrise building. According to the characteristics of wind pressure time series, several probability density functions were properly selected for nonlinear regression analysis of wind pressure coefficients of each gauging point. Numerical fittings of mean and peak (positive maxima and negative minima) and areaaveraged peak pressure coefficients were performed and compared by using six probability distributions. The analysis results show that the probability distributions of negative minima and positive maxima of pressure coefficients are leftskewed and rightskewed, respectively. The mean pressure coefficient time series comply with unbiased distribution and the t distribution fits the measured data best, followed by Logistic, Normal, Type I EDV distribution, respectively; Type I EVD has the best fitting effect for peak values, and then the Lognormal distribution, Gamma distribution and Normal distribution in order; The most unfavorable pressure coefficient is dominated by negative peak pressure, that is, suction forces are predominant over wind forces on PV panels; The tributary areaaveraged unfavorable pressure coefficient is recommended to take -2.3.