Abstract
Extraction of accurate Photo Voltaic (PV) model parameters is a challenging task for PV simulator developers. To mitigate this challenging task a novel approach using Gravitational Search Algorithm (GSA) for accurate extraction of PV model parameters is proposed in this paper. GSA is a population based heuristic optimization method which depends on the law of gravity and mass interactions. In this optimization method, the searcher agents are collection of masses which interact with each other using laws of gravity and motion of Newton. The developed PV model utilizes mathematical equations and is described through an equivalent circuit model comprising of a current source, a diode, a series resistor and a shunt resistor including the effect of changes in solar irradiation and ambient temperature. The optimal values of photo-current, diode ideality factor, series resistance and shunt resistance of the developed PV model are obtained by using GSA. The simulations of the characteristic curves of PV modules (SM55, ST36 and ST40) are carried out using MATLAB/Simulink environment. Results obtained using GSA are compared with Differential Evolution (DE), which shows that GSA based parameters are better optimal when compared to DE.
Highlights
World’s primary energy consumption is increasing by about 2.5% in every year
The Photo Voltaic (PV) modelling method accuracy is validated by measured parameters of selected PV modules
Three PV modules (SM55, ST36 and ST40) of different technologies are utilized for verification; these include the mono-crystalline and thin-film types
Summary
World’s primary energy consumption is increasing by about 2.5% in every year. Though most of the energy demand is shared by conventional energy sources, the en-. GSA proved that it gives better convergence than GA and PSO under various conditions This algorithm is mainly based on the Newton’s law of gravity, “The gravitational force between two particles is directly proportional to the product of their masses and inversely proportional to the square of the distance between them”. This algorithm gives the better optimal results which are obtained by various applications in an effective manner [13] [14]. This mass will present an optimal solution in the search space
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