With the escalating demand for energy and the concomitant depletion of fossil fuel reserves, solar energy has emerged as a sustainable alternative, offering both energy conservation and power-saving benefits. The optimization of photovoltaic (PV) system performance through vigilant monitoring is essential for maximizing energy production. This study aims to devise a novel algorithm that derives from photocurrent measurements at the string level, alongside the aggregate current output of the PV array. Simulations of a PV string/array were executed using MATLAB/Simulink to discern the effects of solar irradiance and temperature fluctuations on current parameters. A representative model comprising two commercial PV modules arranged in series was employed to construct a four-string PV array for analysis. Findings indicate that photocurrent and overall current output are significantly influenced by solar irradiance, whereas increases in saturation and reverse saturation currents with temperature correspond to diminished current output. A rudimentary fault detection algorithm emerged from the simulation data, facilitating the identification of faults by juxtaposing the current from a PV string against a benchmark PV cell. Prompt detection and amelioration of faults-particularly those within groups two and three, which are characterized by 10 - 40 and greater than 40 reductions in current, respectively, and commonly associated with shading, soiling, and hotspots-are imperative for averting substantial energy yield losses and prolonging system longevity. It is crucial to acknowledge that daily variations in weather conditions may affect the algorithm's efficacy, underscoring the need for ongoing refinement. © 2023 IIETA.