Estimation of the parameters of the mathematical model of an equivalent diode of a photovoltaic panel using a continuous genetic algorithm



Renewable energy, Solar, photovoltaic, parameters identification, modeling,, Photovoltaic systems, Optimization methods, Mathematical model, Genetic algorithms


This document presents the implementation of a con- tinuous population genetic optimization algorithm (CGA) as a solution method to the parameter estimation problem of a diode model (SDM) of a photovoltaic panel (PV) from experimental data of voltage versus current (V-I). The parameters to be estimated by means of the CGA are: the photoinduced current, the diode saturation current, the ideality factor, the series resistance and the parallel resistance. The estimation of the SDM parameters is carried out in order to obtain the real values that represent the power profile of the panel and thus carry out an analysis of its physical state. For which, the mean square error of the PV current estimated by the solution method from the selected parameters is used as the objective function, with the real curve of the PV panel used as the test scenario. All of the above subject to the set of restrictions that limits the problem under analysis. To validate the effectiveness and robustness of the proposed method, in this document two comparison methods have been used: the particle swarm optimization method (PSO) and a traditional genetic algorithm (GAT). In addition, four different panel types were used to generate the test scenarios: the MSX60, the SOLAR SJ65, the KYOCERA KC200GT, and the STP245S. All simulations were obtained using MATLAB 2019b. The results obtained in this document show that the proposed method presents the best relationship between the estimation of parameters and the computation time required to solve the SDM problem.


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Author Biographies

Jhon Jairo Montano, Instituto Tecnologico Metropolitano: Medellín, Antioquia, CO

Nació en El Doncello, Caquetá, Colombia. Obtuvo el título de Ingeniero Electrónico del Instituto Tecnológico Metropolitano ITM, Medellín Colombia, en 2017. Se graduó de la Maestría en Automatización y Control Industrial del Instituto Tecnológico Metropolitano ITM, en 2020,  desempeñándose como profesor en el Departamento de Electrónica y Energías Renovables. Sus intereses de investigación incluyen energías renovables, electrónica de potencia, redes inteligentes, algoritmos de optimización aplicados a sistemas fotovoltaicos, diagnóstico de fallos en paneles fotovoltaicos, energías renovables, electrónica de potencia y redes inteligentes.

Luis F. Grisales Noreña, Instituto Tecnológico Metropolitano: Medellin, Antioquia, CO

Nació en Cartago, Valle, Colombia. Recibió su licenciatura y maestría en Ingeniería Eléctrica de la Universidad Tecnológica de Pereira, Colombia, en 2013 y 2015 respectivamente. Se graduó con un doctorado en Ingeniería de Automatización de la Universidad Nacional, Manizales Colombia,  trabajando como profesor en el Departamento de Electromecánica y Mecatrónica del Instituto Tecnológico Metropolitano de Medellín, y miembro del grupo de investigación MATyER. Sus
intereses de investigación incluyen la optimización matemática, la planificación y el control de los sistemas energéticos, las energías renovables, el almacenamiento de energía, la electrónica de potencia y las redes inteligentes

Andres Felipe Tobon , Instituto Tecnológico Metropolitano: Medellin, CO

  Nació en Medellín, Antioquia, Colombia. Graduado como ingeniero de instrumentación y control del Politécnico JIC, en 2006. Especialista tecnológico en Gestión de Proyectos del SENA, 2011. Máster en automatización y control industrial del ITM, 2015. Profesor del Instituto Tecnológico Metropolitano ITM desde el 2011. Entre sus líneas de investigación activas están la identificación paramétrica de modelos matemáticos, MPPT, algoritmos de optimización aplicados a las energías renovables

Daniel Gonzalez Montoya, Instituto Tecnológico Metropolitano: Medellin, Antioquia, CO

Nació en Medellín, Colombia. Recibió el título de ingeniero en control de la Universidad Nacional de Colombia en 2010, una maestría en automática industrial de la misma universidad en 2012, y el título de doctor en ingeniería automática de la Universidad Nacional de Colombia en 2017. Desde 2015 es profesor del Instituto Tecnológico Metropolitano ITM. Sus principales intereses de investigación son el diseño de estrategias de control de sistemas de energía renovable y convertidores de conmutación.


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How to Cite

Montano, J. J., Grisales Noreña, L. F., Tobon , A. F., & Gonzalez Montoya, D. (2021). Estimation of the parameters of the mathematical model of an equivalent diode of a photovoltaic panel using a continuous genetic algorithm. IEEE Latin America Transactions, 20(4), 616–623. Retrieved from