A distributed wind-solar joint prediction method considering data coupling

High-precision wind-solar joint prediction is an important premise to give full play to the wind-solar complementary characteristics. Based on the coupling relationship between wind and solar, a distributed wind and solar joint prediction method is established in this paper. Firstly, considering the influence of geographical location, meteorological and other factors on the wind and solar power output, the coupling of wind power and solar output was analyzed. Then, the optimal intra-group variance algorithm is established to identify and process the abnormal data. Then, a combined prediction model based on improved attention mechanism and Long ShortTerm Memory (LSTM) is proposed, which can effectively extract the coupling relationship between wind-solar and make accurate prediction. Finally, simulation results show that the proposed method can effectively improve the accuracy of prediction.