A New Model Predictive Control Method for Buck-Boost Inverter-Based Photovoltaic Systems

Saeed Danyali (), Omid Aghaei, Mohammadamin Shirkhani, Rahmat Aazami, Jafar Tavoosi, Ardashir Mohammadzadeh and Amir Mosavi ()
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Saeed Danyali: Department of Electrical Engineering, Ilam University, Ilam 6931647574, Iran
Omid Aghaei: Department of Electrical Engineering, Ilam University, Ilam 6931647574, Iran
Mohammadamin Shirkhani: Department of Electrical Engineering, Ilam University, Ilam 6931647574, Iran
Rahmat Aazami: Department of Electrical Engineering, Ilam University, Ilam 6931647574, Iran
Jafar Tavoosi: Department of Electrical Engineering, Ilam University, Ilam 6931647574, Iran
Ardashir Mohammadzadeh: Multidisciplinary Center for Infrastructure Engineering, Shenyang University of Technology, Shenyang 110870, China
Amir Mosavi: Faculty of Civil Engineering, Technische Universität Dresden, 01067 Dresden, Germany

Sustainability, 2022, vol. 14, issue 18, 1-14

Abstract: This study designed a system consisting of a photovoltaic system and a DC-DC boost converter with buck-boost inverter. A multi-error method, based on model predictive control (MPC), is presented for control of the buck-boost inverter. Incremental conductivity and predictive control methods have also been used to track the maximum power of the photovoltaic system. Due to the fact that inverters are in the category of systems with fast dynamics, in this method, by first determining the system state space and its discrete time model, a switching algorithm is proposed to reduce the larger error for the converter. By using this control method, in addition to reducing the total harmonic distortion (THD), the inverter voltage reaches the set reference value at a high speed. To evaluate the performance of the proposed method, the dynamic performance of the converter at the reference voltage given to the system was investigated. The results of system performance in SIMULINK environment were simulated and analyzed by MATLAB software. According to the simulation results, we can point out the advantage of this system in following the reference signal with high speed and accuracy.

Keywords: PV; buck-boost inverter; single-stage inverter; model predictive control (MPC); DC-DC converter; renewable energy; artificial intelligence; machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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