Optimal power flow: Closing the loop over corrupted data

Recently the power system state estimator was shown to be vulnerable to malicious deception attacks on the measurements, resulting in biased estimates. In this work we analyze the behavior of the Optimal Power Flow (OPF) algorithm in the presence of such maliciously biased estimates and the resulting consequences to the system operator. In particular, we characterize the set of attacks that may lead the operator to apply the erroneous OPF recommendation. Such characterization is used to improve a previously proposed security index by also considering the attack impact, which may be used for allocation and prioritization of protective measures. Additionally, we propose an analytical expression for the optimal solution of a simplified OPF problem with corrupted measurements. A small analytical example is discussed to illustrate and motivate our contributions.