基于CMAC-BP神经网络的光伏功率短期预测  

Short-term Prediction of Photovoltaic Power based on CMAC-BP

作　　者：廖云涛 向婕 

机构地区：[1]国能日新科技股份有限公司

出　　处：《信息技术与标准化》2020年第9期54-58,共5页Information Technology & Standardization

摘　　要：BP神经网络是目前较为主流的光伏短期功率预测技术之一,针对光伏发电能力受多种因素影响的特性,结合小脑模型关节控制器(CMAC)与BP神经网络,提出了一种CMAC-BP神经网络的光伏短期功率预测技术,并对比了该算法与使用BP神经网络进行预测的结果,证明了该算法的有效性。As the scale of photovoltaic(PV)power connected to the grid growing rapidly,the influence brought by the randomness,time variability,volatility of PV power can not be ignored.An effective method to solve such problem is to schedule system by using the PV power prediction technique,so that the stability of the grid can be guaranteed.Besides,the importance of PV power prediction technique increases as the moving forward of power market.BP neural network(NN)is a widely used method in the field of PV power prediction,in this paper,a CMAC-BP NN is proposed to achieve the forecasting of PV power,and its effectiveness is evaluated by comparing its result with a BP NN based PV power prediction result.

关 键 词：光伏功率预测 BP神经网络 小脑模型关节控制器 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TM615[自动化与计算机技术—控制科学与工程]