An Online Archimedes Optimization Algorithm Identifier-Controlled Adaptive Modified Virtual Inertia Control for Microgrids

Asmaa Fawzy, Youssef Mobarak, Dina S. Osheba, Mahmoud G. Hemeida (), Tomonobu Senjyu and Mohamed Roshdy
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Asmaa Fawzy: Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt
Youssef Mobarak: Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt
Dina S. Osheba: Department of Electrical Engineering, Faculty of Engineering, Menoufia University, Shebin El Kom 32511, Egypt
Mahmoud G. Hemeida: Minia Higher Institute of Engineering, Minya 61111, Egypt
Tomonobu Senjyu: Department of Electrical and Electronics Engineering, Faculty of Engineering, University of the Ryukyus, Nishihara 903-0213, Japan
Mohamed Roshdy: Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt

Energies, 2022, vol. 15, issue 23, 1-27

Abstract: Single widespread employment of renewable energy sources (RESs) contributes to the shortage in the inertia of the microgrid (MG). After this, frequency stability may regress as a result of power imbalance or minor load fluctuations. This paper proposes an explicit adaptive modified virtual inertia control (VIC) based on an online Archimedes optimization algorithm (AOA) identifier for MG containing thermal, wind, and solar photovoltaic power plants. The Rung Kutta approach is used to construct the proposed online identifier, which acts as a model of the MG. AOA predicts the coefficients of the online identifier based on the input and output of MG to mimic the frequency deviation of the MG online. AOA estimates online the inertia and damping coefficients of the VIC system with an energy storage device based on online AOA identifier coefficients. The frequency deviation of the MG based on the proposed explicit adaptive modified VIC is compared with the conventional VIC based on fixed parameters and the VIC system based on optimal parameters using AOA offline under mutation in loads, weather-dependent input, and MG parameters using MATLAB/Simulink software. Furthermore, the proposed explicit adaptive modified VIC based on an online AOA identifier is evaluated with the adaptive VIC system based on fuzzy logic control, which adjusts only the inertial gain online. The simulation results demonstrate the capabilities of the proposed explicit adaptive modified VIC to improve the frequency stability and enhance low-inertia islanded MGs with RESs.

Keywords: explicit self-tuning adaptive control (ESTC); system identification; islanded microgrid (MG); Archimedes optimization algorithm (AOA); renewable energy sources (RESs); adaptive modified virtual inertia control (VIC) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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