Robust estimation for enhancing the cyber security of power state estimation

Cyber security provided by robust power systems state estimation methods is evaluated. Tools and estimators developed in robust statistics theory are exploited. The idea consists in considering redundant robust estimation techniques with different robustness properties to improve the overall detection of attacks and synthesizing a decision making process to determine whether an attack is present or absent. This could offer the advantage of reducing the investment in expensive secure sensors such as safe phasor measurement units (PMUs). Specifically, several robust least trimmed squares estimators are considered with different breakdown points to improve cyber-attacks detection. Attacks on the observation function are assessed. Simulations on the IEEE 14 test bed illustrate the behavior of the proposed approach and the popular detection methods analyzing the weighted least squares normalized residuals when subject to cyber intrusions.