Publications by authors named "Anas R Alsoud"
Article Synopsis
- A new method has been developed to accurately determine parameters for proton exchange membrane fuel cells (PEMFCs), crucial for optimal performance and modeling.
- This method employs the GOOSE algorithm, inspired by geese's adaptive behavior, which utilizes an improved orthogonal learning mechanism for better parameter estimation.
- Experimental validation shows the GOOSE algorithm outperforms existing methods, showcasing its effectiveness in simulating complex fuel cell systems and enhancing their applications.
In recent times, photovoltaic (PV) power generation has been growing due to increase in energy demand. In grid-connected mode, achieving maximum power (MP) from the PV array is difficult by using conventional techniques due to various reasons like low tracking efficiency, stability issues, etc. This motivates the design of an appropriate control strategy to obtain the maximum power point tracking (MPPT) to harvest MP from the PV array.
View Article and Find Full Text PDFBat algorithm (BA) is one of the promising metaheuristic algorithms. It proved its efficiency in dealing with various optimization problems in diverse fields, such as power and energy systems, economic load dispatch problems, engineering design, image processing and medical applications. Thus, this review introduces a comprehensive and exhaustive review of the BA, as well as evaluates its main characteristics by comparing it with other optimization algorithms.
View Article and Find Full Text PDFThe Moth flame optimization (MFO) algorithm belongs to the swarm intelligence family and is applied to solve complex real-world optimization problems in numerous domains. MFO and its variants are easy to understand and simple to operate. However, these algorithms have successfully solved optimization problems in different areas such as power and energy systems, engineering design, economic dispatch, image processing, and medical applications.
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