الفهرس 
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Abstract
Recently, interest in DC microgrids has increased due to the growth of dc loads besides the adoption of the renewable energy resources (RESs). In addition to the advantages of DC microgrids in contrast with AC microgrids including the elimination of the conversion stages which increases the DC microgrids’ efficieny, and decreases the power losses which results in a positive impact on the energy savings. Additionally, the current is constantly in phase with the voltage and so, there are no power factor losses. This also elimates the synchronization problems improving the efficieny and power quality of the system. Moreover, the complexity of system design is reduced. Plus, DC microgrids with reduced electromagnetic fields levels is safer for humans. Furthermore, utilizing fewer electronic components led to a lower capital cost, and a simpler control system. However, when subjected to load and RESs uncertainties, bus voltage fluctuations in DC microgrids have a negative impact on the system operation in stable state.
The present dissertation employs the idea of cascaded double-loop control to ensure the system operate in a stable state through voltage management for the DC islanded microgrid’s DC-bus. A new African vulture optimization algorithm (AVOA) and Beluga whale optimization algorithm (BWO) that draw their inspiration from nature are used to adapt the rule in cascaded double-loop control. Cascaded double-loop control is proportional-integral-based (PI-based) for its simple structure, maintainable, easy to implement, cost-effective, and it can enhance both the dynamic stability/transient response and decrease steady-state error through compromise between proportional gain (Kp) and integral gain (KI) parameters. The algorithms are used to tune the parameters of the proportional-integral (PI) controllers to guarantee a desirable performance. The performance of the African Vulture Optimization Algorithm, or Beluga Whale Optimization Algoritm and Particle Swarm Optimization (PSO) are compared in the present work under various operating conditions. The simulation takes into account real-world information on temperature, sun irradiation, and rapid variations in load. The system model is built using MATLAB/Simulink. The indicators used to assess the system performance are maximum percentage overshoot (MPOS), maximum percentage undershoot (MPUS), and settling time (Ts). The outcomes show that both of the AVOA-PI-based control and BWO-PI-based control have given better results in contrast with the PSO-PI-based control in terms of voltage regulation in the mentioned indicators. The proposed control system resilience is evaluated experimentally through the usage of a real-time simulator (RT-LAB) accompanied by OP4510. As a result, contrasting the simulation and experimental results presented similar outcomes, and validated the novel optimal PI-based control superiority.
● Keywords: African vulture optimization algorithm; Beluga whale optimization algorithm; dc microgrid; voltage regulation; renewable energy resources; real-time simulation.