Abstract
Because of the rapid increase in the depletion rate of conventional energy sources, the energy crisis has become a central problem in the contemporary world. This issue opens the gateway for exploring and developing renewable energy sources to fulfill the exigent energy demand. Solar energy is an abundant source of sustainable energy and hence, nowadays, solar photovoltaic (PV) systems are employed to extract energy from solar irradiation. However, the PV systems need to work at the maximum power point (MPP) to exploit the highest accessible power during varying operating conditions. For this reason, maximum power point tracking (MPPT) algorithms are used to track the optimum power point. Furthermore, the efficient utilization of PV systems is hindered by renowned partial shading conditions (PSC), which generate multiple peaks in the power-voltage characteristic of the PV array. Thus, this article addresses the performance of the newly developed jellyfish search optimization (JSO) strategy in the PV frameworks to follow the global maximum power point (GMPP) under PSC.
Highlights
If the quantity of the food present at the jellyfish (m) position exceeds the food present at the position of jellyfish (k), the latter progresses in the direction of the former, while if the food is less at the mth jellyfish place, the kth jellyfish moves jellyfish move around their own location and subsequently update the position of each jellyfish, per Equation (14)
Where γ stands for the movement coefficient, which relates to the length of movement around the jellyfish’s position, and γ is taken as (0.1), as per the mathematical examination performed by the author in [28]
The run best parameter in the table illustrates the best iterative cycle corresponding to the optimal parameter in the illustrates thethe best iterative cycle corresponding run parameter in table the table illustrates best iterative cycle correspondingtotothe theoptimal optimal power output. These results suggest that the tracking speed of the jellyfish search optimization (JSO) is fast, while there power poweroutput
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. This article gives insight into the validation of the newly developed jellyfish search optimization (JSO) algorithm in the case of the maximum power point tracking of the solar photovoltaic systems as a solution to the partial shading conditions problem in solar PV. The validation process provides the response of the JSO algorithm for the dynamic and static irradiation conditions in the simulation framework These results and problem solutions, i.e., testing of the new algorithm, are the indicators of the originality of this research work. Dynamic and static irradiation conditions in the simulation framework
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