Mathematical model parameter estimation of solar photovoltaic (PV) cell, module and array represent a prodigious challenge in recent researches, where analytical, metaheuristic and hybrid techniques play a vital role for parameter extraction by using manufacturer's datasheet and experimental data, although the precise and highly reliable solution identification is still a complex problem to be solved. In this paper, a new Emperor Penguin Optimisation- (EPO) based parameter estimation approach for a single-diode R_p solar PV model is presented that is cohesively analysed under different sets of temperature and irradiance (G). Validation of the proposed technique is perceived on the analysis of performance characteristics, that is, current-voltage (I-V) and power-voltage (P-V) of KC200GT, PWP201, and STP6 120-36 PV modules under various simulation conditions. Moreover, estimated results are compared with the experimental data and several established estimation techniques in the literature for validation and demonstrate the proposed technique with highly precise outcomes having reduced computational cost for the PV model parameter extraction problem.

中文翻译：

---

一种新的基于帝企鹅优化的太阳能光伏参数估计方法

太阳能光伏 (PV) 电池、模块和阵列的数学模型参数估计在最近的研究中是一个巨大的挑战，其中分析、元启发式和混合技术通过使用制造商的数据表和实验数据在参数提取方面发挥着至关重要的作用，尽管精确和高度可靠的解决方案识别仍然是一个需要解决的复杂问题。在本文中，提出了一种新的基于帝企鹅优化 (EPO) 的参数估计方法，用于单二极管R _p太阳能光伏模型，该方法在不同的温度和辐照度 ( G )组下进行了内聚分析。所提出的技术的验证在性能特征的分析中被感知，即电流 - 电压（IV) 和KC200GT、PWP201 和 STP6 120-36 光伏组件在各种模拟条件下的功率电压 ( PV )。此外，将估计结果与实验数据和文献中的几种既定估计技术进行比较以进行验证，并证明所提出的技术具有高度精确的结果，降低了 PV 模型参数提取问题的计算成本。