Adaptive Cubature Kalman Filter Based Dynamic State Estimation for Grid-connected Photovoltaic System

Huang, Shilou; Wang, Tong; Ji, Taipeng; Jin, Mingxin

doi:10.1109/ceepe51765.2021.9475835

Cited by 2 publications

(1 citation statement)

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“…[13], [14] use EKF and EnKF to observe the dynamics of Permanent Magnet Synchronous Generator-based Wind Turbines (PMSG-WTs). An adaptive CKF technique is proposed in [15] for performing DSE of PV generation systems. Ref.…”

Section: Introductionmentioning

confidence: 99%

Dynamic State Estimation for Inverter-Based Resources: A Control-Physics Dual Estimation Framework

Huang,

Lin,

et al. 2024

IEEE Trans. Power Syst.

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Based Resources (IBRs) gradually replace conventional synchronous generators (SGs), Dynamic State Estimation (DSE) techniques must be extended for the monitoring of IBRs. The key difference between IBRs and SGs is that the dynamics of IBRs comprise a heavy mix of physical processes and digital controller computations. This paper develops a generic framework of Control-Physics Dynamic State Estimation (CPDSE) for IBRs. First, a control-physics state-space representation of IBRs is presented. Noting the symmetry of the control and physical state spaces, it is proposed to use two dual estimators to track the states of the physical inverter subsystem and the digital controller subsystem, respectively. The CPDSE framework has the capability of suppressing errors in both measurement signals and control signals flowing between the two subsystems and the potential to distinguish between cyber and physical events. The advantages and versatility of the proposed CPDSE framework are validated on a variety of IBR systems (solar, wind, and storage), control strategies (grid-following and grid-forming), and both transmission and distribution systems.

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Section: Introductionmentioning

confidence: 99%