Distributed Moving Horizon Estimation via Operator Splitting for Automated Robust Power System State Estimation

Multirate State Estimation Using Moving Horizon Estimation

In most chemical processes only some measurements are available online while other measurements are available infrequently and often with long delays. Multirate state estimation can optimally combine these different classes of measurements to improve the estimation quality compared to the fast measurements alone. The nature of measurements at different sampling intervals which are subject to de...

Distributed State Estimation Using a Modified Partitioned Moving Horizon Strategy for Power Systems

In this paper, a distributed state estimation method based on moving horizon estimation (MHE) is proposed for the large-scale power system state estimation. The proposed method partitions the power systems into several local areas with non-overlapping states. Unlike the centralized approach where all measurements are sent to a processing center, the proposed method distributes the state estimat...

Robust and Scalable Power System State Estimation via Composite Optimization

In today’s cyber-enabled smart grids, high penetration of uncertain renewables, purposeful manipulation of meter readings, and the need for wide-area situational awareness, call for fast, accurate, and robust power system state estimation. The least-absolute-value (LAV) estimator is known for its robustness relative to the weighted least-squares (WLS) one. However, due to nonconvexity and nonsm...

Extracting Individual Thermostatic Load States from Aggregate Power Consumption Measurements via Moving Horizon State Estimation

We present an optimization-based state estimation method that allows us to estimate the states of individual thermostatically controlled loads (TCLs), such as space heaters, from measurements of the power consumption of small aggregations of TCLs. The state estimator can be used together with a controller to provide services to power systems such as frequency control. The main advantage of this...

Distributed moving horizon estimation for nonlinear constrained systems