Fractional Order Differential Evolution to Solve Parameter Estimation Problem of Solar Photovoltaic Models

Parameter estimation problem (PEP) in photovoltaic (PV) systems is crucial for maximizing the utilization of solar energy in PV power systems. In this study, we employ fractional order differential evolution (FODE) to address PEP of various solar PV models. FODE operates on a bi-strategy co-deployment framework and is enhanced with fractional-order difference vectors, allowing for comprehensive utilization of historical population information. To assess the efficacy of FODE, we conduct six sets of experiments encompassing single, dual, and triple diode models, as well as PV module models. FODE is benchmarked against ten other representative algorithms. The experimental findings demonstrate that FODE outperforms all other algorithms in addressing PV system PEP.