Power Electronic
Y. Yerkin; A.H.O. Al Mansor; A.A. Ibrahim; A.R.T. Zaboun; J.K. Abbas; S.H. Hlail; D.A. Lafta; K. Al-Majdi
Abstract
DC-DC converters play a crucial role in fuel cell power generation systems, serving as an interface between the fuel cell and the load. Boost converters have gained popularity due to their ability to increase input voltage. However, the performance and efficiency of DC-DC converters in ...
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DC-DC converters play a crucial role in fuel cell power generation systems, serving as an interface between the fuel cell and the load. Boost converters have gained popularity due to their ability to increase input voltage. However, the performance and efficiency of DC-DC converters in fuel cell power systems have posed significant challenges. This study proposes the use of Model Predictive Control (MPC) and the Firefly Optimization Algorithm (FA) for designing and controlling boost DC-DC converters in the most efficient manner. Initially, stability analysis and precise modeling techniques were employed to optimize the characteristics of boost DC-DC converters in fuel cell power generation systems. Subsequently, the predictive control method, utilizing the Firefly optimization algorithm, was applied to enhance converter performance under diverse conditions. The outcomes of the designed control system were compared with conventional methods. Both predictive control and the Firefly optimization algorithm were integrated into the design and control processes of boost DC-DC converters in fuel cell. Based on the simulation results and stability evaluations, the application of the Firefly algorithm and predictive control led to a significant improvement, increasing the system efficiency by approximately 4.7%. These findings highlight the effectiveness of the proposed approach in enhancing the performance of DC-DC boost converters in fuel cell.
Smart Grid
B.A. Usmanovich; T.M.H. Kinanah; A.H.O. Al-Mansor; K. Al-Majdi; S.H. Hlail; D.A. Lafta; A.R.T. Zaboun; J.K. Abbas
Abstract
The optimum location of electric vehicle (EV) parking lots is critical in distribution network design for lowering costs, boosting revenues, and enhancing dependability. However, conventional distribution network schedulers were not designed with these variables in mind. Furthermore, the increased use ...
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The optimum location of electric vehicle (EV) parking lots is critical in distribution network design for lowering costs, boosting revenues, and enhancing dependability. However, conventional distribution network schedulers were not designed with these variables in mind. Furthermore, the increased use of EVs for environmental reasons mandates the planning of EV parking spaces. As a result, distribution network designers must examine network technical difficulties, design approaches, and changing consumer needs. The placement of dispersed manufacturing resources and EV parking without sufficient planning and ideal location leads in economic challenges for investors and technical concerns for the network. As a result, future distribution networks should prioritize the ideal placement of EV parking lots and distributed production resources in order to maximize network capabilities and meet the needs of companies and power applications in the digital society. According to the findings, the rate of EV parking installations is very high. When power consumers remain connected to the grid during peak hours, distribution businesses benefit significantly, and the overall voltage profile improves. Variations in electric vehicle (EV) battery capacity, power cost, EV adoption, and the weighting coefficients required for optimization will all have different outcomes. It is critical to precisely determine the battery capacity of electric vehicles (EVs) as well as the efficiency of inverters in order to produce more accurate results. According to the findings, increasing the number of parking lot for EVs in a network enhances the benefit from minimizing losses, and providing peak load significantly. So that using 2 parking lot for EVs in a network can increase the overall profit to 129%.