Polynomial-chaos-expansion-based surrogate models have recently been advocated in the
literature for power system dynamic parameter estimation. Regarding the estimation of the …

This paper develops a new response-surface-based Bayesian inference approach for power
system dynamic parameter estimation of a decentralized generator using phasor …

In this work, we develop a polynomial-chaos-expa-nsion (PCE)-based approach for
decentralized dynamic parameter estimation through Bayesian inference. Using this …

Secure power system operation relies on accurate steady-state and dynamic system
models. It is thus crucial to carefully validate the models in power systems, in particular the …

This letter proposes a Seidel-type recursive Bayesian approach for the power system
parameter estimation. By timely using the latest probabilities calculated in the current …

Quantifying the uncertainty of the renewable energy generation units and loads is critical to
ensure the dynamic security of next-generation power systems. To achieve that goal, the …

In this paper, least square estimation (LSE)-based dynamic generator model parameter
identification is investigated. Electromechanical dynamics related parameters such as inertia …

This paper utilizes data measured by phasor measurement units (PMUs) to extract a low-
order dynamic equivalent model for power system stability studies. The estimated model is a …

We address the problem of estimating the uncertainty in the solution of power grid inverse
problems within the framework of Bayesian inference. We investigate two approaches, an …

This paper proposes a new method to estimate parameters of a synchronous generator
using measurements taken under unbalanced operating conditions. The new method is …