Maximum Power Point Tracking of Photovoltaic Panels by Using Improved Pattern Search Methods

Andrés Tobón, Julián Peláez-Restrepo, Juan P. Villegas-Ceballos, Sergio Ignacio Serna-Garcés, Jorge Herrera and Asier Ibeas
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Andrés Tobón: Departamento de Electrónica y Telecomunicaciones, Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellín, Antioquia, Colombia
Julián Peláez-Restrepo: Departamento de Electrónica y Telecomunicaciones, Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellín, Antioquia, Colombia
Juan P. Villegas-Ceballos: Departamento de Electrónica y Telecomunicaciones, Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellín, Antioquia, Colombia
Sergio Ignacio Serna-Garcés: Departamento de Electrónica y Telecomunicaciones, Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellín, Antioquia, Colombia
Jorge Herrera: Departamento de Ingeniería, Facultad de Ciencias Naturales e Ingeniería, Universidad de Bogotá Jorge Tadeo Lozano, Bogotá, Distrito Capital, Colombia
Asier Ibeas: Departamento de Ingeniería, Facultad de Ciencias Naturales e Ingeniería, Universidad de Bogotá Jorge Tadeo Lozano, Bogotá, Distrito Capital, Colombia

Energies, 2017, vol. 10, issue 9, 1-15

Abstract: This paper deals with the optimization of maximum power point tracking when a photovoltaic panel is modelled as two diodes. The adopted control is implemented using a sliding mode control (SMC) and the optimization is implemented using an improved Pattern Search Method. Thus, the problem of maximum power point tracking is reduced to an optimization problem whose solution is implemented by Pattern Search Techniques, inheriting their convergence properties. Simulation examples show the effectiveness of the proposed technique in practice, being able to deal with different radiations. In addition, improved pattern search method (IPSM) is compared with other techniques such as perturb & observe and Particle Swarm optimization, after which IPSM presents lower energy losses in comparison with the other two algorithms, with the advantage of ensuring the location of the optimal power point in all cases.

Keywords: maximum power point tracking (MPPT); particle swarm optimization (PSO); perturb and observe (P&O); pattern search method (PSM); photovoltaic; optimization; sliding mode (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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