González-Castaño, C.Marulanda, J.Restrepo, C.Kouro, S.Alzate, A.Rodriguez, J.2021-05-252021-05-252021-03Sustainability (Switzerland), Volume 13, Issue 6, 2 March 2021, Article number 300020711050http://repositorio.unab.cl/xmlui/handle/ria/18945Indexación ScopusThis paper proposes a new method for maximum power point tracking (MPPT) of the photovoltaic (PV) system while using a DC-DC boost converter. The conventional perturb and observe (P&O) method has a fast tracking response, but it presents oscillation around the maximum power point (MPP) in steady state. Therefore, to satisfy transient and steady-state responses, this paper presents a MPPT method using support vector machines (SVMs). The use of SVM will help to improve the tracking speed of maximum power point of the PV system without oscillations near MPP. A boost converter is used to implement the MPPT method, where the input voltage of the DC-DC converter is regulated using a double loop where the inner loop is a current control that is based on passivity. The MPPT structure is validated by hardware in the loop, a real time and high-speed simulator (PLECS RT Box 1), and a digital signal controller (DSC) are used to model the PV system and implement the control strategies, respectively. The proposed strategy presents low complexity and it is implemented in a commercial low-cost DSC (TI 28069M). The performance of the MPPT proposed is presented under challenging experimental profiles with solar irradiance and temperature variations across the panel. In addition, the performance of the proposed method is compared with the P&O method, which is traditionally most often used in MPPT under demanding tests, in order to demonstrate the superiority of the strategy presented. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.enMaximum Power Point TrackersPowerpointPhotovoltaic SystemCurrent control based on passivityHardware in the loop testingPhotovoltaic systemSupport vector machinesHardware-in-the-loop to test an mppt technique of solar photovoltaic system: A support vector machine approachArtículo10.3390/su13063000