Resilient decentralized consensus-based state estimation for smart grid in presence of false data

Abstract

State estimation is an essential part of energy management system in smart grid as it is a basis for many of the associated management and control processes. In this paper, we present a decentralized state estimation approach, based on consensus optimization and the alternating direction method of multipliers, that is robust against certain harsh class of false data injection schemes. The proposed scheme provides a reliable estimate of the global system state in a distributed manner even if the system is regionally unobservable to some regional controllers, but globally observable across regions. The scheme also accommodates different communication network topologies for a given power network. We assess the performance of the presented schemes on IEEE 14 and 118 bus test systems.

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