Adaptive Optimization Algorithm for High Proportion Distributed Photovoltaic Access to Distribution Network Based on RNN

Conventional adaptive optimization algorithm for high proportion distributed photovoltaic access to distribution network mainly uses ARMA (Autoregressive moving average model) to obtain incremental load, which is vulnerable to the impact of centralized absorption fluctuation, resulting in poor algorithm optimization indicators. Therefore, an RNN based adaptive optimization algorithm for high proportion distributed photovoltaic access to distribution network is proposed. That is, RNN is used to build a high proportion distributed photovoltaic access distribution network model, and an adaptive optimization objective function of photovoltaic distribution network is designed to generate an adaptive optimization algorithm for distributed photovoltaic access distribution network. The experimental results show that the optimization performance indicators of the designed adaptive optimization algorithm for distribution networks are good, and the power supply capacity under different scenarios is the best, effective, and has certain economic value. It has made certain contributions to improving the centralized power supply capacity of distribution networks and reducing power supply and distribution losses.