Expandable quantum deep width learning-based distributed voltage control for smart grids with high penetration of distributed energy resources

Abstract

With numerous distributed energy resources accessed to smart grids, the randomness of distributed generators exacerbates the risk of voltage violations in the smart grid. To reduce the risk of voltage violations caused by distributed energy resources, this paper designs a real-time distributed voltage control method for smart grids to replace the centralized voltage control method of smart grids. In the designed real-time distributed voltage control method, the adjacent regional controllers communicate with each other to realize the optimal global control of the voltage of the entire smart grid without the need for a central controller. To study the reactive states of distributed energy resources access to smart grids on the voltage of smart grids, this paper proposes a three-state energy voltage model. To match the expandable distributed voltage control method for smart grids, this paper proposes the expandable quantum deep width learning algorithm. By combining the proposed algorithm with the designed real-time distributed voltage control method, the proposed algorithm has strong expandability and can match the distributed voltage control problem of smart grids. Finally, the effectiveness and expandability of the proposed algorithm and the designed real-time distributed voltage control method are demonstrated under four complex systems. The integral squared time-weighted absolute error index value of the expandable quantum deep width learning is less than or equal to 6.461.