الفهرس 
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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 work focuses on enhancing the dynamic stability of an islanded microgrid using a frequency control concept based on virtual inertia control.
This thesis introduces two controllers, proportional- integral (PI) controller, and model predictive controller (MPC), that are employed in the virtual inertia control loop to deal with the high integration level of RESs into microgrids. In addition, this study addresses the application of two recent optimization algorithms to optimally design the PI controller and MPC. The optimization problem is defined using the criterion of integral square error (ISE), that is the most commonly utilized within the frequency control loops.
In this thesis, an application of manta ray foraging optimization (MRFO) algorithm is presented to get the optimal design of the PI controller in the virtual inertia control loop of islanded microgrid considering RESs. The second optimization technique is the African vultures optimization algorithm (AVOA) to attain the optimum design of MPC including RESs and energy storage units. Moreover, the microgrid paradigm contains battery energy storage (BES) units for enhancing the islanded microgrid transient stability.
The performance of the proposed controllers and algorithms is investigated considering various operating conditions and compared with other evolutionary optimization algorithms. Real data of RESs are utilized, and random load power pattern is applied to achieve realistic simulations conditions.
The results show that proposed controllers and algorithms have a superior performance in frequency disturbance alleviation and reference frequency tracking compared with other considered optimization techniques. The simulations outcomes are obtained using MATLAB software.