Resilient Privacy-Preserving Cooperative Control for Constrained RoCoF in Cyber-Physical Microgrids

This paper proposes a resilient distributed control strategy for cyber-physical microgrids (MGs) that jointly ensures constraint-aware frequency regulation and data privacy-preserving. To mitigate the risk of information leakage during communication, a saturation normalization-based mechanism is introduced to protect sensitive frequency and power data. In contrast to conventional privacy-preserving methods that may degrade dynamic performance, the proposed approach explicitly incorporates frequency change rate and deviation constraints into the control design. Based on the derived sufficient conditions, a gain selection algorithm is developed to determine control parameters that ensure both frequency deviation and rate-of-change bounds are satisfied under dynamic load disturbances. Unlike existing privacy-preserving strategies that primarily focus on information masking but often neglect dynamic security, the proposed algorithm follows a principled, constraint-driven design that simultaneously preserves privacy and guarantees secure transient performance. The control framework operates in a cooperative manner with limited and masked information exchange, enabling secure cooperation without compromising stability. Experimental results on multiple IEEE benchmark systems validate the proposed method's effectiveness.