Abstract
This study presents a novel search algorithm of maximum power point tracking for photovoltaic power generation systems. The I-V characteristics and the P-V power output under specific irradiation and temperature conditions are simulated. The performance of the algorithm under fully shaded and sudden partially shaded conditions as well as variable insulations levels is investigated. The developed algorithm performs a wide-range search in order to detect rapidly changing weather conditions, and keeps the simulated stand-alone or grid-connected systems continuously operating close to the maximum power point. The performance of the developed algorithm, under extremely changing environmental conditions, is found to be superior compared to that of other conventional algorithms. The results of this study show that, under uniform radiations conditions, the developed algorithm takes only half of the time required by the Perturbation and Observe algorithms to reach maximum power point MMP. Furthermore, when PV is subjected to sudden partial shading conditions, the algorithm rapidly detects these changes and reaches the new MMP in less than a second.
Highlights
It is widely accepted that the nonrenewable sources in the world are finite and it is only a matter of time before reserves will essentially be consumed [1, 2]
The simulation results are carried out using MATLAB/ Simulink to validate the performance of the proposed maximum power point tracking (MPPT) algorithm
A full Simulink MATLAB model is built to simulate the performance of the proposed algorithm
Summary
It is widely accepted that the nonrenewable sources in the world are finite and it is only a matter of time before reserves will essentially be consumed [1, 2]. The outcomes of MPPT using Neural Network methods are highly related to the accuracy and efficiency of the designed algorithm, the size of the training database, and the network training quality They require gathered data for various conditions and multiple locations to guarantee a better performance. None of the developed search algorithms can successfully deal with all extreme weather conditions, namely, rapidly changing, partial shading, and sudden partial shading conditions. All the developed methods found in the literature still suffer from weak performance under extreme weather conditions It is the objective of this study to develop an efficient novel search algorithm that deals with rapidly changing, partial shading and sudden partial shading conditions to track the MPP of PV cells. Adaptation to different solar panels and different environmental conditions is considered in developing the proposed search algorithm
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