The power-voltage characteristic curve of photovoltaic systems under partially shaded conditions exhibits multiple peaks and renders conventional maximum power point tracking techniques ineffective. This study proposes a hybrid optimisation algorithm incorporating genetic algorithm (GA) in the initial stages of tracking followed by traditional perturb and observe (P&O) algorithm. Although GA and P&O methods do not guarantee convergence to global maximum power point when employed separately, the fusion of the two methods leads to confirmed global convergences with least time. The excellent performance of the combined method is illustrated through extensive simulation and experimental results. Nomenclature I c output current of PV cell (A) V c output voltage of PV cell (V) I c L photocurrent of PV cell (A) I c O diode saturation current (A) I c On diode saturation current at nominal condition (A) V c t thermal voltage of PV cell (V) k Boltzman constant (Joules/Kelvin) q charge of an electron (coulomb) T actual temperature of PV cell (Kelvin) a diode ideality constant R c s series resistance of PV cell (Ω) R c p parallel resistance of PV cell (Ω) I m L photocurrent of PV module (A) I m Ln photocurrent PV module at the nominal condition (A) T n nominal temperature (Kelvin) G actual irradiation (kW/m 2 ) G n nominal irradiation (kW/m 2 ) I m scn nominal short circuit current of PV module (A) I c scn nominal short circuit current of PV cell (A) V m ocn nominal open circuit voltage of PV module (V) V c ocn nominal open circuit voltage of PV cell (V) K i current temperature co-efficient (A/Kelvin) E g bandgap energy of the PV cell (eV) N s Number of series connected cells N p Number of parallel connected cells
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