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Mehrdad Yazdanian

Researcher at Washington State University

Publications -  15
Citations -  921

Mehrdad Yazdanian is an academic researcher from Washington State University. The author has contributed to research in topics: Microgrid & Kalman filter. The author has an hindex of 6, co-authored 14 publications receiving 696 citations. Previous affiliations of Mehrdad Yazdanian include Quanta Technology & Isfahan University of Technology.

Papers
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Distributed Control Techniques in Microgrids

TL;DR: The objective of this paper is to provide a review of distributed control and management strategies for the next generation power system in the context of microgrids and identifies challenges and opportunities ahead.
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Small-Signal Stability Analysis of an Inverter-Based Microgrid With Internal Model-Based Controllers

TL;DR: Small-signal analysis is used to explore the behavior of internal model-based current and voltage controllers by deriving a state-space model and performing eigenvalue and sensitivity analysis on an islanded inverter-based microgrid system and results show that internalmodel-based controllers have superior eigen Value patterns that lead to increased stability and improved transient behavior.
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Internal Model-Based Current Control of the RL Filter-Based Voltage-Sourced Converter

TL;DR: In this article, an internal model control (IMC)-based approach for voltage-sourced converters (VSC) is proposed to improve their dynamic behavior. But, the IMC-based controller has a straightforward design procedure, and can be implemented using simple PI and PID controllers.
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Washout Filter-Based Power Sharing

TL;DR: Using a dynamic feedback incorporating washout filters, this letter proposes a novel approach to perform power sharing without any communication links, and without compromising voltage and frequency regulation.
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Estimation of Electromechanical Oscillation Parameters Using an Extended Kalman Filter

TL;DR: In this article, a new state-space model is proposed for online detection of parameters of a ringdown signal using an extended Kalman filter (EKF), which can estimate both constant and time-varying parameters.