Optimum Parameters Extraction of Flexible Photovoltaic Cell Using Earthworm Optimization Algorithm

Fatima Wardi, Mohamed Louzazni, Mohamed Hanine
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Abstract

The research presents an original approach to estimate and extract the electrical intrinsic characteristics of flexible hydrogenated amorphous silicon (a-Si:H) solar cells using Earthworm Optimization Algorithm (EOA) The EOA metaheuristic algorithm has gained popularity for optimizing non-linear and complicated systems in various fields. Additionally, the current-voltage curve is used to calculate the offered restricted objective function. In addition, the obtained results using EOA are compared with two algorithms named; quasi-Newton technique (Q-N) and self-organizing migration algorithm (SOMA). Finally, to validate the performance of the used algorithm statistical evaluations are calculated to determine the correctness of the calculated parameters. The compared results show that the theoretical results exhibit great agreement with experimental data, demonstrating higher accuracy when compared to Q-N and SOMA.
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利用蚯蚓优化算法提取柔性光伏电池的最佳参数
该研究提出了一种利用蚯蚓优化算法(EOA)估算和提取柔性氢化非晶硅(a-Si:H)太阳能电池电气固有特性的独创方法。 EOA 元启发式算法在优化各领域的非线性复杂系统方面广受欢迎。此外,电流-电压曲线用于计算所提供的受限目标函数。此外,还将使用 EOA 算法获得的结果与两种算法(准牛顿技术(Q-N)和自组织迁移算法(SOMA))进行了比较。最后,为了验证所使用算法的性能,还计算了统计评估,以确定计算参数的正确性。比较结果表明,理论结果与实验数据非常吻合,与 Q-N 和 SOMA 相比具有更高的准确性。
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