State Observer for the Fourth-order Model of a Salient Pole Synchronous Generator with Stator Losses: Known and Partially Unknown Input Cases

TL;DR

This paper develops a new state observer for a fourth-order model of a salient pole synchronous generator that works without simplifying assumptions and with limited input measurements, improving robustness and applicability.

Contribution

It introduces a novel observer design that does not rely on idealized assumptions and handles partially known inputs, advancing state estimation in power systems.

Findings

Proposed observer performs well in simulations.

Overcomes lack of persistent excitation using DREM.

Handles realistic scenarios with limited measurements.

Abstract

In this paper we study the question of how to reconstruct the state of a power system using Phasor Measurement Units (PMUs). In our previous research we proved that this question has an affirmative answer imposing some rather strict structural assumptions: namely, neglecting the generator rotors saliency and assuming that the stator resistance of the synchronous generator is zero. It was shown in simulations that the performance of the proposed observer was sensitive to these assumptions, observing a transient quality degradation for realistic simulations not imposing these assumptions. Moreover, it was assumed in our previous work that the mechanical power and the field voltage are available for measurement, a scenario that it is not always realistic. In this paper we accomplish two ambitious objectives. First, we propose a new observer that does not impose the simplifying assumptions on the generator model. Secondly, we consider the more realistic scenario where only mechanical power is available for measurement. That is, we solve a problem of state reconstruction of a nonlinear system with partially known input measurements -- that is well-known to be a very challenging task. The design of the first observer relies on two recent developments proposed by the authors, a parameter estimation based approach to the problem of state estimation and the use of the Dynamic Regressor Extension and Mixing (DREM) technique to estimate these parameters. The use of DREM allows us to overcome the problem of lack of persistent excitation that stymies the application of standard parameter estimation designs. On the other hand, the observer for the partial input measurement scenario relies on the clever exploitation of the systems model. Simulation results illustrates the good performance of the proposed observers.