MPPT AND CONTROLLER DESIGN USING METAHEURISTIC ALGORITHMS FOR A BUCK-BOOST CONVERTER CONNECTED TO A PV PANEL
Abstract
In recent years, the increasing energy demand and the depletion of fossil fuels have driven researchers to focus on renewable energy sources. In this context, the efficient control of DC-DC power converters connected to photovoltaic (PV) panels—commonly used for solar energy generation—has become increasingly important. This study employs the recently developed Artificial Hummingbird Algorithm (AHA) and the Cheetah Optimization Algorithm (CO) to optimally control a Buck-Boost converter coupled with a PV panel. Both AHA and COA are applied to enhance control performance based on the Integral of Time-Weighted Squared Error (ITSE) criterion by tracking the maximum power point (MPPT) of the PV panel under varying temperature and irradiance conditions. The algorithm optimizes the parameters of the Proportional–Integral (PI) controller used in the converter, thereby improving the system’s dynamic response. The findings demonstrate that the proposed approach delivers faster, more stable, and more accurate performance.
Keywords
Metaheuristic Algorithms, PV Panel, Buck-Boost Converter, MPPT.
Supporting Institution
Technological Research Council of Türkiye (TUBITAK), Power Electronics Technologies Research and Application Center (PETEC)
Project Number
124E782
Thanks
This study was supported by the Scientific and Technological Research Council of Türkiye (TUBITAK) Research Fund, under the Grant Number 124E782. The authors thank to TUBITAK for their supports, and the Power Electronics Technologies Research and Application Center (PETEC), Sakarya, Türkiye.
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