Comparison of two PV array models for the simulation of PV systems using five different algorithms for the parameters identification


Comparison of PV array models to simulate the dynamic behavior of PV systems.

Three grid-connected PV systems located in two sites in Northern and Southern Spain are analysed.

Three different technologies of PV modules are included in the study.

Five optimization algorithms (LMA, GA, PSO, DE and ABC) are used for the parameters extraction.

The SAPM model demonstrated best potential for the simulation of PV systems in real operating conditions.


Simulation is of primal importance in the prediction of the produced power and automatic fault detection in PV grid-connected systems (PVGCS). The accuracy of simulation results depends on the models used for main components of the PV system, especially for the PV module. The present paper compares two PV array models, the five-parameter model (5PM) and the Sandia Array Performance Model (SAPM). Five different algorithms are used for estimating the unknown parameters of both PV models in order to see how they affect the accuracy of simulations in reproducing the outdoor behavior of three PVGCS. The arrays of the PVGCS are of three different PV module technologies: Crystalline silicon (c-Si), amorphous silicon (a-Si:H) and micromorph silicon (a-Si:H/μc-Si:H).

The accuracy of PV module models based on the five algorithms is evaluated by means of the Route Mean Square Error (RMSE) and the Normalized Mean Absolute Error (NMAE), calculated for different weather conditions (clear sky, semi-cloudy and cloudy days). For both models considered in this study, the best accuracy is obtained from simulations using the estimated values of unknown parameters delivered by the ABC algorithm. Where, the maximum error values of RMSE and NMAE stay below 6.61% and 2.66% respectively.


  • PV modeling;
  • Simulation;
  • Parameter extraction;
  • Metaheuristic algorithms

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