Fraction order particle swarm optimization for parameter extraction of triple-diode photovoltaic models

Abstract

Abstract This work proposes an application of Fractional Order Particle Swarm Optimization (FO-PSO), a meta-heuristic method for parameters estimation of photo-voltaic (PV) module as a non-linear, transcendental, multi-modal and implicit optimization problem. The uses single diode model (SDM), double diode model (DDM) and three-diode model (TDM) of PV modules with the constraint that only data-sheet information may be utilized. A fitness function based on the error amongst the computed values of current and voltage and the ones given in characteristic I-V curves of data-sheet, is minimized using the FO-PSO to get the required parameters. The comparative study between the estimated and data-sheet values provided by PV module manufacturers will determine the effectiveness of this research. The effectiveness of the FO-PSO is demonstrated by comparing the fitness values with that of other techniques. The FO-PSO technique makes a novel contribution to the PV power systems industry by making it possible to obtain a nearly realistic model of any commercial PV module. The effectiveness of the FO-PSO is determined by comparing the results for all the three models with the state of the art optimization techniques. The Root Mean Square error values calculated for the TDM is less than 10e–16, producing very consistent FO-PSO results. Therefore, FO-PSO is anticipated to be a competitive method for obtaining PV module specifications.