基于BP神经网络太阳电池板最佳倾角算法  

Optimized algorithm research based on BP neural network for best inclination angle of fixed solar panels

作　　者：胡海燕[1] 乐斌[2] 胡克满[3] 

机构地区：[1]宁波职业技术学院科研处,浙江宁波315800 [2]浙江工商职业技术学院工学院,浙江宁波315012 [3]宁波职业技术学院电子信息工程系,浙江宁波315800

出　　处：《电源技术》2014年第4期683-686,共4页Chinese Journal of Power Sources

基　　金：浙江省教育厅2012年度科研计划项目(Y201226216)

摘　　要：通过对影响太阳辐射量的基本参数进行分析,并根据天空直接辐射和散射建立太阳能辐射总量的数学模型,通过改变太阳电池板安装倾斜角度以求年太阳辐射总的最大值为约束条件,得出太阳电池板固定安装最佳倾角的目标函数。结合BP神经网络数学模型,通过输入太阳辐射强度、赤纬角、时角、日出时刻、日落时刻、太阳直辐射透明度系数、散射透明度系数等参数值,并求得年最大总辐射量,从而获得最佳倾角值。通过计算机仿真计算结果令人满意,同时本算法还可以进行预测某地区太阳辐射量,具有一定的实际应用参考价值。By analyzing the parameters that affect the solar radiation, a mathematical model was built which targeted for the greatest of total amount of direct and scattering radiation. The purpose was to find the best inclination angle of the fixed solar panels. With the parameters of radiation intensity, angle of declination, hour angle, sunrise and sunset time, coefficient of direct and scattering radiation transparency as input and yearly total amount of radiation as a output, with BP neural network algorithm, the best inclination angle was found. The simulation result is satisfying. And this algorithm can also predict the total amount of the district radiation which appears to be valuable.

关 键 词：BP神经网络 最佳倾角 太阳电池板 算法 

分 类 号：TM914[电气工程—电力电子与电力传动]