Real-Time Privacy-Preserving Average Consensus and Its Application to Secondary Control for AC Microgrid
Ziqiang Wang, Jie Wang, Massimo La Scala, Linyun Xiong
Abstract
Recent studies of the privacy-preserving consensus guarantee the initial-value privacy but leave real-time running values of consensus states unprotected with respect to external eavesdroppers. In this article, a novel real-time privacy-preserving average consensus algorithm is proposed to fill this gap by utilizing the quasi-resonance (QR) algorithm and the mask function with real-time privacy-preserving property based on the multifrequency (MF) sinusoids. Several kinds of sinusoids are included in the mask function to achieve the privacy preservation of the initial value and real-time values simultaneously, such as nondecaying and exponentially-decaying MF sinusoids. The QR algorithm can achieve the exact consensus because of its high control gain on a specific resonant frequency in MF sinusoids. The designed privacy-preserving average consensus algorithm will not increase the communication pressure since the single signal of the sum of MF sinusoids is transmitted to evade increasing information amount. As an application of the developed consensus algorithm, the privacy-preserving distributed secondary control of the islanded ac microgrid is obtained to achieve active power sharing and frequency restoration.