Distributed model predictive control algorithms for emergency voltage stability control of power systems

In this paper, a distributed model predictive control (DMPC) is proposed for the emergency voltage control of large-scale power systems. The main concept of DMPC is that the online rolling optimization of the full system is simplified into a small-scale optimization of multiple sub-areas. It can effectively eliminate or alleviate the dimension disaster, and can reduce the amount of computation. According to the features of DMPC, two kinds of improved DMPC algorithms, namely the communication based distributed model predictive control (C-DMPC-1) and the cooperative distributed model predictive control (C-DMPC-2), are proposed. First, the decomposition principle of DMPC is explained. Then, the rolling optimization model of these two C-DMPC algorithms are built respectively. A case study on New England system is used to validate the proposed algorithms. The results show that the algorithms can effectively enhance the system voltage stability.