Towards Renewable Energy in Iraq: Accurate Photovoltaic Parameter Estimation Using Metaheuristic Algorithms

Engineering notes

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Chinese explanation / 中文解读

中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。

Original abstract

Nowadays there is a global transition to renewable energy because of the urgent need to combat climate change and enhance energy sustainability. For Iraq, which has been facing frequent power shortages and the negative consequences of climate change, such as water shortages and desertification, the investment in renewable energy is no longer optional. Iraq has a high potential for using solar energy due to its high solar radiation levels and long days of sunlight. Solar photovoltaic (PV) systems offer a clean and reliable alternative to diesel generators, but their effectiveness relies largely on exact approximation of nonlinear internal parameters. In this work, three recent metaheuristic algorithms (MAs): FATA (an efficient optimization approach based on geophysics), Moss Growth Optimization (MGO), and Polar Lights Optimizer (PLO), are applied for parameter estimation of single-diode, double-diode, and modified PV models. Results showed that the FATA consistently outperformed MGO and PLO, obtaining the lowest average fitness over 30 independent runs, which means improved accuracy in PV parameter extraction. The achieved results demonstrate how MAs can be a significant tool for enhancing the performance of PV systems.

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