A Gray-Box Approach for Decentralized Grid-Equivalent Model Identification

We propose a decentralized, frequency-domain identification algorithm that estimates the grid-equivalent model from the perspective of local converters. Since local electric signals in a multi-converter setup are affected by voltage inputs from other converters, considered as the grid, estimating a single apparent impedance yields biased and inaccurate results. To overcome this, we design a framework that decouples the effect of the equivalent impedance (passive) from that of the equivalent voltage (active). The parameters and equivalent grid voltages are then estimated using a constrained least squares and a Kalman filter algorithm, respectively, applied across frequency samples. We then demonstrate the accuracy and performance of our algorithm on an interconnected 5-converter system in grid-forming mode, with minimal voltage excitations and non-ideal operating conditions.

Fast and Efficient Estimation of Resonant Modes: A Case Study of Mechanical Drivelines

This work presents the development of an online parameter estimation algorithm for the identification of resonating modes in a linear system of arbitrary order. The method employs a short-time Fourier transform of the input and output signals and uses a recursive least square (RLS) algorithm to detect resonant frequencies and damping factors of the resonant modes.