Privacy-preserving distributed state estimation for microgrids based on encrypted measurements under bit-rate constraints
Peifeng Zhao, Yangkai Chen, Derui Ding, Hongjian Liu
Abstract
System measurements and monitoring with information security become vital for microgrids because of the vulnerability of communication networks. The focus of this paper is on privacy-preserving distributed state estimation with measurement data in the face of bit-rate constraints. A new dynamic encryption mechanism designed based on time-varying linear transformations is created to facilitate the encryption of measurements of microgrids. In light of the proposed encryption rule combined with bit-rate constraints, an iterative recursive scheme in a distributed way, receiving the desired estimator gains, is proposed by optimising the upper bound of the estimation error covariance. In addition, the impact of the allocated bit rate is made available to distributed state estimators, and the privacy of encryption strategies adopted is systematically evaluated. Lastly, an engineering-based method is devised to find the linear transformation matrix for a simplified encryption rule. Simulation experiments validate the significant advantages of the established state estimator.