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Performance optimization of photovoltaic and solar cells via a hybrid and efficient chimp algorithm
Solar Energy ( IF 6.0 ) Pub Date : 2023-03-03 , DOI: 10.1016/j.solener.2023.02.036
Chao Yang , Chang Su , Haiting Hu , Mostafa Habibi , Hamed Safarpour , Mohamed Amine Khadimallah

The global shift toward solar energy has resulted in the advancement of research into the manufacture of high-performance solar cells. It is critical to accurately model and identify the parameters of solar cells. Numerous models of solar cells have been presented thus far, including the single-diode, the double-diode, and the three-diode models. Every model contains a number of unidentified parameters, and numerous approaches for determining their optimal values have been published in the literature. The purpose of this article is to propose an efficient optimization technique, dubbed the Chimp Optimization Algorithm (ChOA), for estimating the model parameters of solar networks. The proposed ChOA outperforms state-of-the-art algorithms in terms of convergence rate, global search capacity, and durability. To demonstrate the proposed ChOA algorithm's efficiency, it is used to determine the parameters of several photovoltaic modules and solar cells. The result of ChOA is evaluated and compared with ten well-known optimization algorithms in the literature. Additionally, the performance of the ChOA algorithm has been evaluated in a practical application for parameter evaluation of three widely-utilized commercial modules, i.e., multi-crystalline (KC200GT), polycrystalline (SW255), and monocrystalline (SM55), under a variety of temperature and irradiance circumstances that result in alterations in the photovoltaic model's parameters. The results confirm the proposed algorithm's robustness and high performance.



中文翻译:

通过混合高效的黑猩猩算法优化光伏和太阳能电池的性能

全球向太阳能的转变促进了对高性能太阳能电池制造的研究。准确建模和识别太阳能电池的参数至关重要。迄今为止,已经提出了许多太阳能电池模型,包括单二极管、双二极管和三二极管模型。每个模型都包含许多未识别的参数,并且文献中已经发表了许多确定其最佳值的方法。本文的目的是提出一种有效的优化技术,称为 Chimp 优化算法 (ChOA),用于估计太阳能网络的模型参数。所提出的 ChOA 在收敛速度、全局搜索能力和耐久性方面优于最先进的算法。为了证明所提出的 ChOA 算法的效率,它被用来确定几个光伏模块和太阳能电池的参数。对 ChOA 的结果进行了评估,并与文献中十种著名的优化算法进行了比较。此外,ChOA 算法的性能已经在三种广泛使用的商业组件参数评估的实际应用中进行了评估,即多晶 (KC200GT)、多晶 (SW255) 和单晶 (SM55),在各种条件下导致光伏模型参数改变的温度和辐照度环境。结果证实了所提算法的鲁棒性和高性能。对 ChOA 的结果进行了评估,并与文献中十种著名的优化算法进行了比较。此外,ChOA 算法的性能已经在三种广泛使用的商业组件参数评估的实际应用中进行了评估,即多晶 (KC200GT)、多晶 (SW255) 和单晶 (SM55),在各种条件下导致光伏模型参数改变的温度和辐照度环境。结果证实了所提算法的鲁棒性和高性能。对 ChOA 的结果进行了评估,并与文献中十种著名的优化算法进行了比较。此外,ChOA 算法的性能已经在三种广泛使用的商业组件参数评估的实际应用中进行了评估,即多晶 (KC200GT)、多晶 (SW255) 和单晶 (SM55),在各种条件下导致光伏模型参数改变的温度和辐照度环境。结果证实了所提算法的鲁棒性和高性能。多晶硅 (SW255) 和单晶硅 (SM55),在导致光伏模型参数发生变化的各种温度和辐照度环境下。结果证实了所提算法的鲁棒性和高性能。多晶硅 (SW255) 和单晶硅 (SM55),在导致光伏模型参数发生变化的各种温度和辐照度环境下。结果证实了所提算法的鲁棒性和高性能。

更新日期:2023-03-04
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