Event-Based Joint State and Unknown Input Estimation for Energy Networks: Handling Multi-Machine Power Grids

In this paper, the joint state and unknown input estimation (SUIE) problem is investigated for multi-machine power grids within energy networks under the event-triggered mechanism. The field voltage and the mechanical torque of the synchronous generator (SG), which are generally difficult to be measured in engineering practice, are treated as unknown inputs to be estimated in this investigation through developing easy-to-implement algorithms. For phasor measurement units (PMUs) that are deployed to monitor the dynamic behavior of the SG, the massive PMU-based signal transmissions are orchestrated by using an event-based transmission strategy with the aim to lighten the communication burden. Attention is paid to the design of an event-based joint SUIE algorithm such that, in the presence of nonlinearities and event-triggered measurements, certain upper bounds on the estimation error covariances of both the unknown input and the state are first guaranteed and then minimized at each sampling instant. Finally, based on the IEEE 39-bus system, simulation experiments under three cases are carried out to illustrate the validity of the developed estimation algorithm.

Automated summary

This paper investigates the joint state and unknown input estimation (SUIE) problem for multi-machine power grids within energy networks under the event-triggered mechanism. It develops easy-to-implement algorithms to estimate the field voltage and mechanical torque of the synchronous generator (SG), which are generally difficult to be measured in engineering practice. An event-based transmission strategy is used to coordinate the massive PMU-based signal transmissions, and an event-based joint SUIE algorithm is designed to guarantee and minimize the estimation error covariances of both the unknown input and the state. Simulation experiments on the IEEE 39-bus system validate the developed estimation algorithm.