Dynamic partitioning of virtual grids based on stochastic model predictive control
Qiang Wu, He Huang, Song Gao, Zhe Chen · 2024
At present, the control of virtual grid is becoming more and more high-dimensional and difficult. In this, a dynamic partition method of virtual grid system based on stochastic model predictive control is proposed. Considering the influence of system uncertainty, considering the maximum partition independence, the minimum control dimension and the minimum change of partition scheme, based on the stochastic model predictive control, the cluster partition rolling optimization and feedback correction of virtual grid system are carried out to reduce the influence of renewable energy fluctuation and prediction error on the control of virtual grid system. Reasonable dynamic partition of virtual grid system and tracking the actual operation of the system can reduce the difficulty and scale of virtual grid system control, improve the stability and anti-interference ability of virtual grid system cluster partition, and provide support for efficient operation and maintenance of virtual grid. Finally, the effectiveness of the method is verified by a simulation example.