Research on Evaluation Method of Renewable Energy Accommodation Capability Based on LSTM

With the rapid growth of installed capacity of renewable energy in “Three North” region of China, the problem of curtailment of wind power and solar power is increasingly prominent year by year. It is urgent to carry out the analysis of renewable energy accommodation. In this paper, a Renewable energy accommodation capacity assessment model based on long short-term memory network under TensorFlow framework is presented. First, the multivariate time series was screened by principal component analysis to reduce the data dimension. Secondly, the LSTM network is used to model the nonlinear relationship between the key factors affecting renewable energy accommodation capacity and the actual output sequence of renewable energy. Based on the actual examples, the effectiveness of the method for assessing the accommodation capacity of the renewable energy is proved.