Risk-Averse Transmission Path Selection for Secure State Estimation in Power Systems

Abstract

The secure state estimation (SSE) problem is investigated for a kind of power systems where the smart meters’ measurements are transmitted to a remote estimator. In this paper, we mainly focus on the transmission via wireless networks. Taking consideration of the possible increase in transmission failure rate due to risk events, such as jamming attacks, a so-called risk-averse transmission path selection (RaTPS) method is proposed to improve SSE robustness. Based on the idea of reinforcement learning, the transmission acknowledgments are applied as the reinforcement signals to reward the source node (smart meter) for choosing more reliable paths. The multipath traffic allocation can adaptively performed according to the transmission failure rate of each path. The theoretical analysis about convergence of RaTPS and SSE is given with the technique of Markov chain, and it is illustrated in the simulation that the robustness of SSE can be improved by using RaTPS.