Siavash Oshnoei

Mr. Siavash Oshnoei


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 July 2021 in Energies
Verified
Journal Article
Open access
PDF file
SOSoroush Oshnoei
Soroush Oshnoei
MAMohammadreza Aghamohammadi
Mohammadreza Aghamohammadi
SOSiavash Oshnoei
Siavash Oshnoei
AOArman Oshnoei
Arman Oshnoei
Behnam Mohammadi-IvatlooBehnam Mohammadi-Ivatloo
Behnam Mohammadi-Ivatloo
Nowadays, the renewable energy sources in microgrids (MGs) have high participation to supply the consumer’s demand. In such MGs, the problems such as the system frequency stability, inertia, and damping reduction are threatened. To overcome this challenge, employing the virtual inertia control (VIC) concept in the MG structure could be considered as a viable solution to improve the system frequency response. Hence, this work proposes a novel modeling for VIC in an islanded MG that provides simultaneous emulation of the primary frequency control, virtual inertia, and damping. To show the efficiency of the proposed technique, a comparison is made between the dynamic performance of the proposed VIC and conventional VIC under different scenarios. The results indicate that the proposed VIC presents superior frequency performance in comparison with conventional VIC. In addition to VIC modeling, a new cascade controller based on three-degrees of freedom and fractional-order controllers (FOCs) is proposed as an MG secondary controller. The effectiveness of the proposed controller is compared to tilt-integral-derivative and FO proportional-integral-derivative controllers. The Squirrel search algorithm is utilized to obtain the optimal coefficients of the controllers. The results demonstrate that the proposed controller improves the MG frequency performance over other controllers. Eventually, the sensitivity analysis is performed to investigate the robustness of the proposed controller in the face of the variations of the parameters.