Resilient robust model predictive load frequency control for smart grids with air conditioning loads

This paper investigates the robust model predictive load frequency control problem for smart grids with wind power under cyber attacks. To accommodate intermittent power generation, the demand response of the system is considered by involving the air conditioning loads in the frequency regulation. In addition, the system uncertainties produced by the air conditioning load users and wind turbines when replacing traditional generator sets are considered. By using the cone complementary linearization algorithm and the linear matrix inequality technique, a resilience robust model predictive control strategy with mixed H2/H infinity$H_2/H_\infty$ performance indexes is proposed. Furthermore, a rigorous derivation of the recursive feasibility of robust model predictive control is given. Finally, the simulation results of the two-area load frequency control scheme show that the proposed model predictive control strategy is capable of realizing the load frequency control of the multi-area smart grid and is robust to the parameter uncertainties and frequency regulation of the system. The results also show that the proposed model predictive control strategy has some resistance to cyber attacks and external disturbances. This paper investigates the robust model predictive load frequency control problem for smart grids with wind power under cyber attacks. The highlight of this paper is that a resilience robust model predictive control strategy with mixed H2/H infinity performance indexes is proposed considering system uncertainties resulting from air conditioning loads and wind turbines. Moreover, a rigorous derivation of the recursive feasibility of robust model predictive control is put forward, which helps guarantee the performance of load frequency control. image