his article provides a survey on state estimation (SE) in electric power grids and examines the impact on SE of the technological changes being proposed as a part of the smart grid development. Although SE at the transmission level has a long history, further research and development of innovative SE schemes, including those for distribution systems, are needed to meet the new challenges presented by the requirements of the future grid. This article also presents some example topics that signal processing (SP) research can contribute to help meet those challenges.

This paper presents a state estimation method for power systems when not all state variables are observable with phasor measurement units (PMU), namely, incomplete PMU observability. Realizing that PMU measurements are generally more accurate than conventional ones, the proposed approach estimates PMU unobservable states and PMU observable states separately. The latter are estimated from PMU measurements using a linear estimator. Those estimates are then used along with conventional measurements in a reduced-order nonlinear estimator for the PMU unobservable states. The proposed decoupled approach features reduced computational complexity and greater numerical stability, when compared to existing combined approaches. We show analytically that the performance of the proposed method is comparable to that of existing approaches if PMU measurements are sufficiently accurate. In this paper, we also study the impact of time-skew errors in conventional measurements on the performance of hybrid state estimators using both conventional and PMU measurements. We propose a model that incorporates such errors into conventional measurements. We show that our proposed method is more robust than existing approaches in the presence of time-skew errors. Our analytical findings are verified by simulations on standard IEEE test systems.

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