The l1 Optimal State Estimator for Load Frequency Control of Power Systems: A Comparative and Extensive Study

This paper proposes fully decentralized
$l_{1}$
optimal dynamic state estimators (DSEs) for load frequency control (LFC) of interconnected power generating systems and provides its comparative and extensive study with respect to three other types of DSEs. To this end, we present the dynamic model of a single area of the power-generating unit occurring from the interconnected power systems. By noting the fact that each area is affected by the frequency deviations in other areas, and it is quite difficult to obtain any property of the load changes in power systems, we characterize the disturbances in the LFC of power systems as bounded persistent signals. As a candidate for DSEs for LFC of power systems, the unknown input observer (UIO), Kalman filter (KF), and
$H_{\infty} $
optimal DSE are considered, and their limitations are analyzed in depth. In connection with this, the
$l_{1}$
optimal DSE, in which the maximum magnitude of estimation error for the worst bounded persistent disturbances is minimized, is proposed as the most effective state estimator. Finally, the practical validity and effectiveness of the proposed
$l_{1}$
optimal DSE are demonstrated through some comparative simulations for a three-area power generating system.