Photovoltaic power generation power short term prediction method based on mind evolution Elman neural network

The invention discloses a photovoltaic power generation power short term prediction method based on a mind evolution Elman neural network. According to the good expandability, the good portability and the extremely strong global optimization capacity of the mind evolution algorithm, and the historical data state sensitivity and the strong self dynamic information processing capacity of the Elman neural network, a photovoltaic power generation power short term prediction algorithm by using the mind evolution algorithm to optimize the Elman neural network is brought forward. Through optimizing an Elman neural network weight and a threshold by the mind evolution algorithm, defects that the Elman neural network is likely to fall into local optimum and the like are overcome. The example result shows that the method is quick in convergence rate, strong in optimization capacity and convenient in dynamic information processing, and an important role is played in photovoltaic power short term prediction.