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access icon free PMU-based decentralised mixed algebraic and dynamic state observation in multi-machine power systems

© The Institution of Engineering and Technology
Received 09/07/2020, Accepted 09/11/2020, Revised 18/09/2020, Published 18/11/2020

The authors propose a novel decentralised mixed algebraic and dynamic state observation method for multi-machine power systems with unknown inputs and equipped with phasor measurement units (PMUs). More specifically, they prove that for the third-order flux-decay model of a synchronous generator, the local PMU measurements provide enough information to reconstruct algebraically the load angle and quadrature-axis internal voltage. Due to the algebraic structure, a high numerical efficiency is achieved, which makes the method applicable to large-scale power systems. Also, they prove that the relative shaft speed can be globally estimated combining a classical immersion and invariance observer with – the recently introduced – dynamic regressor extension and mixing parameter estimator. This adaptive observer ensures global convergence under weak excitation assumptions that are verified in applications. The proposed method neither requires the measurement of exogenous input signals such as the field voltage and the mechanical torque nor the knowledge of mechanical subsystem parameters.

Inspec keywords: nonlinear control systems; shafts; parameter estimation; decentralised control; power system control; observers; power system measurement; synchronous generators; phasor measurement; power system stability; regression analysis

Other keywords: multimachine power systems; local PMU measurements; classical immersion; recently introduced – dynamic regressor; phasor measurement units; adaptive observer; PMU-based; dynamic state observation method; invariance observer; mixed algebraic; third-order flux-decay model; large-scale power systems; algebraic structure; mixing parameter estimator

Subjects: Synchronous machines; Stability in control theory; Power system measurement and metering; Power system control; Control system analysis and synthesis methods; Mechanical components; Control of electric power systems; Multivariable control systems; Simulation, modelling and identification; Nonlinear control systems

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