Abstract
This studyaimed at improving the performance and efficiency of conventional static photovoltaic (PV) systems by introducing a metaheuristic algorithm-based approach that involves reconfiguring electrical wiring using switches under different shading profiles. Themetaheuristicalgorithmused wasthe firefly algorithm (FA), which controls the switching patterns under non-homogenous shading profiles and tracks the highest global peak of power produced by the numerous switching patterns. This study aimed to solve the current problems faced by static PV systems, such as unequal dispersion of shading affecting solar panels, multiple peaks, and hot spot phenomena, which can contribute to significant power loss and efficiency reduction. The experimental setup focusedon software development and the system or model developed in the MATLAB Simulink platform. Athorough and comprehensive analysis was done by comparing the proposed method’s overall performance and power generation with thenovel static PVseries–parallel (SP) topology and totalcross-tied (TCT) scheme. The SP configuration is widely used in the PV industry. However, the TCT configuration has superior performance and energy yield generation compared to other static PV configurations, such as the bridge-linked (BL) and honey comb (HC) configurations. The results presented in this paper provide valuable information about the proposed method’s features with regard toenhancing the overall performance and efficiency of PV arrays.
Highlights
Introduction published maps and institutional affilSolar energy is currently a demanding renewable power source forenergy supply.Solar energy hasan infinite supply, a simple installation process in remote areas [1], and is eco-friendly in nature
Based on the experimental analysis performed, the author can conclude that the proposed reconfiguration of electrical array (REA) technique successfully improved the performance of the PV arrays under Partial Shading (PS) profiles compared to the novel static PVseries–parallel (SP)
The power coefficient of PV arrays wassuccessfully increased under all conditions tested
Summary
Mathematical modeling is a vital aspectofthe optimal simulation design of the PV array under PS profiles. Equation (5) establishes an accurate method for the estimation of solar irradiation received by the solar module based on the temperature, voltage, and current measurement; besides this, the other terms are fixed, and these can be obtained from the datasheet. The developed algorithm is based on either the solar panels’ quantity or thearray size of the PV arrays to determine the firefly population’s size. The algorithm developed will go through several iteration processes to track the highest possible GMPP generated by the different switching patterns under each partial shading condition (PSC). Each completed iteration process represents the firefly population, and the highest GMPP found in each population indicates the best value of the population. Equation (11) is deployed to attract the previous lower value of GMPP towards the current best value of GMPP based in the current iteration process.
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