Emerging Parameters Extraction Method of PV Modules Based on the Survival Strategies of Flying Foxes Optimization (FFO)

Nowadays, the world is encountering multiple challenges of energy security, economic recovery, and effect global warming. Investing in new fossil fuels only locks uneconomic practices, sustains existing risks increases threats climate change. In contrast, renewable energies, such as photovoltaic energy, constitute one most promising technologies combating increase temperatures. Given its simplicity low maintenance costs, effective alternative to address issues above. However, standard test conditions (STCs) PV modules are, cases, different from real working a solar module. For instance, high levels incident irradiation an arid may cause temperature module rise by many degrees above STC 25 °C, lowering module’s performance. To effectively simulate control systems for given location, it has become paramount develop robust accurate model that considers how behave. This study seeks introduce emerging metaheuristic optimization algorithm estimate unknown parameters modules. The strategies deployed flying foxes event temperatures have birth development called FFO. Contrary previous methods, this modeling procedure makes possible calculate all parameters, regardless or irradiance. Four modules, having technologies, were tested evaluate accuracy question. effectiveness FFO then contrasted with other well-known metaheuristics where single double diode models are deployed. results show optimizer represents substantial compelling substitute extraction methods.