Abdulbari Talib Naser , Karam Khairullah Mohammed , Nur Fadilah Ab Aziz , Ahmed Elsanabary , Karmila Binti Kamil , Saad Mekhilef
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引用次数: 0
Abstract
The presence of weather variations poses a significant challenge for photovoltaic (PV) systems in achieving maximum power during maximum power point tracking (MPPT), especially under partial shading conditions (PSCs). To prevent the hotspot phenomenon, bypass diodes are fitted across series-connected PV modules. As a result, the power curve has multiple local peaks (LPs) and one global peak (GP). Conventional MPPTs tend to become entrapped in one of these LPs, resulting in a substantial reduction in both the generated power and overall efficiency of the PV system. Metaheuristic optimization algorithms (MOAs) have effectively tackled this issue, although they have incurred a lengthier convergence time, representing one of these methods’ principal drawbacks. Reducing convergence speed is the most important aim in the field of MPPT methods, even if it entails a compromise in terms of tracking efficiency and accuracy. This paper proposes a modified coot optimization algorithm (MCOA) to address these issues to track the global maximum power point (GMPP) under various weather conditions. Additionally, by using only one tuning parameter, the proposed method reduces the complexity of the method in comparison to other MPPT methods. Moreover, the proposed method employs a search space skipping method to improve convergence speed by skipping unnecessary search spaces during MPPT tracking. An experimental validation has been conducted to test the efficacy of the proposed approach under variable shading conditions, utilizing a SEPIC converter and a sampling time of 0.1 s. Based on the experimental results obtained, the proposed MCOA has achieved the best performance with an average tracking time of 1.3 s across all weather conditions and an efficiency of 99.87 %. Furthermore, this paper has also conducted a comparative analysis with five different metaheuristic algorithms, and experimental results demonstrate that MCOA has outperformed others in terms of accuracy and fast tracking time for MPPT, primarily due to its simplicity.
期刊介绍:
in Shams Engineering Journal is an international journal devoted to publication of peer reviewed original high-quality research papers and review papers in both traditional topics and those of emerging science and technology. Areas of both theoretical and fundamental interest as well as those concerning industrial applications, emerging instrumental techniques and those which have some practical application to an aspect of human endeavor, such as the preservation of the environment, health, waste disposal are welcome. The overall focus is on original and rigorous scientific research results which have generic significance.
Ain Shams Engineering Journal focuses upon aspects of mechanical engineering, electrical engineering, civil engineering, chemical engineering, petroleum engineering, environmental engineering, architectural and urban planning engineering. Papers in which knowledge from other disciplines is integrated with engineering are especially welcome like nanotechnology, material sciences, and computational methods as well as applied basic sciences: engineering mathematics, physics and chemistry.