Honey Badger Algorithm Using Partial Shading Condition MPPT Technique
Keywords:
Partial shading condition, MPPT technique, PV system, Honey Badger Algorithm (HBA), Coyote Optimization Algorithm (COA), Efficiency, AccuracyAbstract
The maximum production of electricity is needed to satisfy the consumption from sources of renewable energy, like solar power. The renewable energy source known as solar energy is also environmentally benign, making it an excellent option for power generation. Due to the fact that solar PV panel efficiency is dependent on irradiance, to optimize PV panel output, numerous methods for MPPT, or maximum power point tracking, has been created.. Thus, a new method based on MPPT technique has been provided in this study to enhance the independent photovoltaic system's functionality even in dim lighting and climate change by using the algorithms HBA and COA. The HBA is extracted from the honey badger's method of foraging is employed to maximize the PV panel's power additionally COA optimization is analyzed for making the output power efficiently and accurately by analyzing the placement of PV panel in whole process based on the social behavior of coyotes. From these algorithms the maximum power is obtained in any climate changing situations and also the efficiency and accuracy are maintained using optimization. The novelty of this paper is to produce maximum power and also maintain the efficiency and accuracy of output throughout the process. Multiple simulation results are generated by the suggested algorithm, and the panel power is simulated using MATLAB software to assess its effectiveness. Comparing the suggested technique to the conventional algorithm at various degrees of solar brightness, the findings demonstrate that it can greatly increase regulated output power and provide faster, better dynamic response, hence increasing system efficiency.
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