![]() ![]() Fast and efficient integrated analysis can be performed using new instruments, such as shape and size analysis with SEM, crystal structure and purity analysis with XRD, density analysis with a densitometer. The critical parameters of Aluminum quality as propellant fuel are density, purity, particle shape and size, and porosity/surface area. ![]() The results of the analysis of the quality of aluminum for composite propellant raw materials have a very large influence on the quality of the resulting propellant, so an integrated, quick, and efficient quality analysis is needed. Composite propellant made with 87.5% solid content and 18% AL content, then tested the characteristics of the propellant. Two types of aluminum were analyzed for quality, including bulk and true density using the Archimedes principle, particle shape, and size using SEM (Scanning Electron Microscope), and purity using XRD (X-ray Diffraction), particle area with BET (Brunnauer-Emmet-Teller) and BJH (Barret-Joyner-Halenda) adsorption isotherm. Quality analysis of Aluminum powder for solid fuel composite propellant was carried out to determine the critical parameters of the composite propellant characteristics. The simulation results showed the effectiveness of the optimally controlled SMES system, using the AOA in smoothing the output power variations and increasing the stability of the system under various operating conditions. The simulation outcomes of the AOA, the genetic algorithm (GA), and particle swarm optimization (PSO) were compared to ensure the efficacy of the introduced optimization algorithm. In this study, the AOA was employed to determine the optimum conditions of the PI controller that regulates the charging and discharging of the SMES system. The SMES system has a big impact in integrating wind generators with the electrical grid by regulating the output of wind generators and strengthening the power system’s performance. The AOA is a modern population technique based on Archimedes’ law of physics. This article presents a new optimization technique entitled the Archimedes optimization algorithm (AOA) that enhances the wind energy conversion system’s stability, integrated with a superconducting magnetic energy storage (SMES) system that uses a proportional integral (PI) controller. Throughout the past several years, the renewable energy contribution and particularly the contribution of wind energy to electrical grid systems increased significantly, along with the problem of keeping the systems stable. ![]()
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