基于BP神经网络的光伏太阳能功率预测

most of the researches on PV power generation forecasting methods have problems such as long time for model training and propose an optimization. Using the BP(backpropagation) neural network, this learning algorithm is mainly applicable to multi-input, multi-output networks. It can rely on ready-made data and input and output without knowing the mathematical relationship between the mapping relationship in which input and output. The mapping relationship is learned and stored. In addition, BP neural networks have great advantages in dealing with non-linear problems and have strong generalization ability.