Research on high-dimensional space control of microgrid voltage data based on chaos theory

In traditional power grids, safety considerations are mainly based on constraints, such as unit output constraints and active power supply and demand balance. However, with the development of distributed power technology, energy storage technology, and flexible load technology, Traditional safety constraints are difficult to solve the intermittent and fluctuating safety problems caused by wind energy, photovoltaic and other renewable energy output and flexible loads. Therefore, in the microgrid, special attention should be paid to the safety impact brought by the randomness. Moreover, in the paper, based on the microgrid system, a systematic and comprehensive analysis is conducted on the voltage safety assessment and prediction of microgrids containing intermittent energy, such as wind and photovoltaics. By combining the automatic regression model with the RBF neural network, an improved RBF-AR model is first formed. Then considering the chaotic prediction model of the weighted first-order local method, the effective degree weight combination is applied to carry out the long-time scale prediction research on the voltage sequence of the microgrid. Finally, through the experimental simulation results, the combined model and the single model are judged on the pros and cons, which provides theoretical support for the safety estimation of the microgrid. What is more, it provides a theoretical basis for the safety development of the microgrid, which has important practical significance for its development.