Estimating Faults in Nonlinear DC Microgrids with Constant Power Loads: A Dual-Extended Kalman Filter Approach

• Type: Article in International Conference Proceedings Book
• Date: 2021

Authors

Vafamand, N (Author) Other; Arefi, MM (Author) Other; Shafie-khah, M (Author) Other; Catalao, JPS (Author) FEUP

Conference proceedings International

Title: 2021 21ST IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2021 5TH IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC/I&CPS EUROPE)

21st IEEE International Conference on Environment and Electrical Engineering / 5th IEEE Industrial and Commercial Power Systems Europe (EEEIC/I and CPS Europe)

Politecnico Bari, Bari, ITALY, SEP 07-10, 2021

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Scopus - 1 Citation

Other information

Authenticus ID: P-00W-BDX

DOI: 10.1109/eeeic/icpseurope51590.2021.9584736

Abstract (EN): This article investigates the problem of detecting and estimating actuator fault in direct current microgrids (DC MGs) with linear and nonlinear constant power loads (CPLs). The actuator fault is modeled by using an additive term in the state-space and highly influences the system response if it is not compensated. An advanced dual-extended Kalman filter (dualEKF) is proposed to estimate the system states and the accruing actuator fault. Though the presented approach offers a systematic procedure to divide the augmented state vector into two parts and these parts can be estimated in parallel. Thereby, the online computational burden is reduced as it can be implemented by two processes in parallel. The proposed approach does not require restrictive assumptions on the system matrices and is robust against stochastic Gaussian noises. The proposed approach is applied on a practical faulty DC MG benchmark connected to a CPL; and, the results are compared with other state-of-the-art methods from the computational burden and estimation accuracy points of view.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6