article · Sustainability
Accurate extraction of parameters in solar photovoltaic systems is challenging due to the complex, non-linear relationships between current, voltage, and power. To address this, an implementation of the Gorilla Troops Optimizer (GTO) was developed for parameter extraction across single-diode and double-diode photovoltaic models. Inspired by natural gorilla group behaviours, the algorithm incorporates several operational strategies including migration, following group leaders, and competitive interactions. The method was validated using numerical analyses on two commercial photovoltaic modules, the Kyocera KC200GT and STM6-40/36. Performance comparisons against multiple recent optimisation algorithms showed high consistency, with standard deviations of fitness values falling below 1E-16 for single-diode models and below 1E-6 for double-diode models. The approach demonstrated close agreement between simulated and experimental current-voltage and power-voltage curves under various temperatures and solar irradiation levels.
Solar panels must be modelled accurately to predict energy output, design efficient power networks, and detect system degradation. However, environmental factors such as shifting temperatures and sunlight intensity make solar cell behaviour difficult to calculate. Using advanced mathematical optimisation improves the precision of these digital models, helping engineers simulate solar panel performance more reliably under changing real-world conditions.
This research provides an algorithmic tool for solar module characterisation, primarily applicable to solar system designers, simulation software developers, and photovoltaic engineers. Because the algorithm was validated against experimental data from commercial solar modules, the technique appears to be applied research, though the abstract does not indicate whether it is packaged into commercial software or deployed in field operations.
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The extraction of parameters of solar photovoltaic generating systems is a difficult problem because of the complex nonlinear variables of current-voltage and power-voltage. In this article, a new implementation of the Gorilla Troops Optimization (GTO) technique for parameter extraction of several PV models is created. GTO is inspired by gorilla group activities in which numerous strategies are imitated, including migration to an unknown area, moving to other gorillas, migration in the direction of a defined site, following the silverback, and competition for adult females. With numerical analyses of the Kyocera KC200GT PV and STM6-40/36 PV modules for the Single Diode (SD) and Double-Diode (DD), the validity of GTO is illustrated. Furthermore, the developed GTO is compared with the outcomes of recent algorithms in 2020, which are Forensic-Based Investigation Optimizer, Equilibrium Optimizer, Jellyfish Search Optimizer, HEAP Optimizer, Marine Predator Algorithm, and an upgraded MPA. GTO’s efficacy and superiority are expressed by calculating the standard deviations of the fitness values, which indicates that the SD and DD models are smaller than 1E−16, and 1E−6, respectively. In addition, validation of GTO for the KC200GT module is demonstrated with diverse irradiations and temperatures where great closeness between the emulated and experimental P-V and I-V curves is achieved under various operating conditions (temperatures and irradiations).
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DOI: 10.3390/su13169459
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