基于 MPPT 的快速跟踪修正 COOT 优化算法,适用于部分遮阳条件下的光伏系统

IF 6 2区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
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

摘要

天气变化对光伏(PV)系统在最大功率点跟踪(MPPT)过程中实现最大功率,尤其是在部分遮阳条件(PSCs)下实现最大功率提出了巨大挑战。为防止出现热点现象,在串联光伏组件上安装了旁路二极管。因此,功率曲线具有多个局部峰值(LP)和一个全局峰值(GP)。传统的 MPPT 容易陷入其中一个 LP,导致光伏系统的发电量和整体效率大幅降低。元启发式优化算法 (MOA) 有效地解决了这一问题,但收敛时间较长,这是这些方法的主要缺点之一。降低收敛速度是 MPPT 方法领域最重要的目标,即使这需要在跟踪效率和精度方面做出妥协。本文针对这些问题提出了一种改进的 COOT 优化算法 (MCOA),以跟踪各种天气条件下的全局最大功率点 (GMPP)。此外,与其他 MPPT 方法相比,所提出的方法只使用一个调整参数,从而降低了方法的复杂性。此外,该方法还采用了搜索空间跳过方法,在 MPPT 跟踪过程中跳过不必要的搜索空间,从而提高收敛速度。根据所获得的实验结果,所提出的 MCOA 在所有天气条件下的平均跟踪时间为 1.3 秒,效率为 99.87%,取得了最佳性能。此外,本文还与五种不同的元启发式算法进行了对比分析,实验结果表明,MCOA 在 MPPT 的准确性和快速跟踪时间方面优于其他算法,这主要归功于它的简单性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A fast-tracking MPPT-based modified coot optimization algorithm for PV systems under partial shading conditions

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.

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来源期刊
Ain Shams Engineering Journal
Ain Shams Engineering Journal Engineering-General Engineering
CiteScore
10.80
自引率
13.30%
发文量
441
审稿时长
49 weeks
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.
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