Manta Ray Foraging Optimization for the Virtual Inertia Control of Islanded Microgrids Including Renewable Energy Sources

Amr Saleh, Walid A. Omran, Hany M. Hasanien, Marcos Tostado-Véliz, Abdulaziz Alkuhayli and Francisco Jurado
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Amr Saleh: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
Walid A. Omran: Faculty of Engineering and Materials Science, German University in Cairo, Cairo 12613, Egypt
Hany M. Hasanien: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
Marcos Tostado-Véliz: Department of Electrical Engineering, Superior Polytechnic School of Linares, University of Jaén, 23700 Linares, Spain
Abdulaziz Alkuhayli: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
Francisco Jurado: Department of Electrical Engineering, Superior Polytechnic School of Linares, University of Jaén, 23700 Linares, Spain

Sustainability, 2022, vol. 14, issue 7, 1-19

Abstract: Nowadays, the penetration level of renewable energy sources (RESs) has increased dramatically in electrical networks, especially in microgrids. Due to the replacement of conventional synchronous generators by RESs, the inertia of the microgrid is significantly reduced. This has a negative impact on the dynamics and performance of the microgrid in the face of uncertainties, resulting in a weakening of microgrid stability, especially in an islanded operation. Hence, this paper focuses on enhancing the dynamic security of an islanded microgrid using a frequency control concept based on virtual inertia control. The control in the virtual inertia control loop was based on a proportional-integral (PI) controller optimally designed by the Manta Ray Foraging Optimization (MRFO) algorithm. The performance of the MRFO-based PI controller was investigated considering various operating conditions and compared with that of other evolutionary optimization algorithm-based PI controllers. To achieve realistic simulations conditions, actual wind data and solar power data were used, and random load fluctuations were implemented. The results show that the MRFO-based PI controller has a superior performance in frequency disturbance alleviation and reference frequency tracking compared with the other considered optimization techniques.

Keywords: manta ray foraging optimizer; virtual inertia; microgrid; renewable energy (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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