Abstract
Objectives: To improve the reduction of photovoltaic system\'s power output under various resistance load. Additionally, partial shaded conditions (PSCs) lead to several peaks on photovoltaic (PV) curves, which decrease conventional techniques\' efficiency and in these (PSCs), standard equations might not be implemented entirely, therefore, the mathematical model of PV array is compulsory to modify and re-establish as well as it is compulsory to apply some methods based on artificial intelligence to develop the performance of traditional techniques. Methods: This work has modified and re-established the mathematical model of PV array under (PSCs) which are recognized and verified using MATLAB/Simulink environment. Also, heuristic algorithms (Cuckoo Search Algorithm (CSA) and Modified Particle Swarm Optimization (MPSO)) have been suggested and applied with PV system to promote output power under various resistance load, varying weather conditions and (PSCs). Moreover, these suggested algorithms can improve the dynamic response and steady-state PV systems\' performance simultaneously and effectively comparing to the Modified Perturb and Observe (MP&O) and Artificial Neural Network (ANN) methods. Findings: The proposed methods are examined under various resistance load, several scenarios for (PSCs) and non-uniform irradiation levels to investigate its effectiveness. The results ensure that proposed tracker based on Cuckoo Search Algorithm (CSA) can distinguish between the global and local maximum peaks of PV system effectively with efficiency of 99% comparing to other MPPT approaches. So, all approaches mentioned above are implemented to improve the output power of PV system in Yemen. Novelty: Modified and re-established the mathematical model of PV array under (PSCs) and also, proposed a heuristic algorithms (CSA) and (MPSO)) to apply with PV system to promote maximum output power under various resistance load, varying weather conditions and (PSCs) as well as to improve the performance of (MP&O) and (ANN) methods. Keywords PV Systems, Maximum Power Point Tracking (MPPT), Uniform Irradiation, Partial Shading, Cuckoo Search Algorithm (CSA), MPSO, ANN, and MP&O
Highlights
The applications for PV solar systems are increasing, which need to develop the ingredients and methods used to harness this power source
The previous sections show that the global maximum power point’s location depends on two factors; the first factor is how shadow shading is distributed on PV arrays, and the second one is how PV panels expose solar irradiation
This section will show all the simulations for the Photovoltaic array, the boost converter, the proposed artificial cuckoo search algorithm comparing to Modified Particle Swarm Optimization (MPSO), MP&O, and artificial neural network (ANN) methods
Summary
The applications for PV solar systems are increasing, which need to develop the ingredients and methods used to harness this power source. PV system efficiency, the intensity of source irradiation, and storage methods are the main aspects that disturb the effectiveness of the collection process. The most available method to improve the solar power system’s performance is the rise of irradiation intensity [1]. Over time the use of Solar panels is spreading throughout too many of the rural areas but what remains as a back flaw is these panels’ ability to harness that sunlight with proper efficiency and use it properly. The central aspect of concern remains in terms of its efficiency and another big question about its operation during uniform and non-uniform radiation conditions and conditions of partial shading [2,3]
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