Reducing Cost and Size in Photovoltaic Systems Using Three-Level Boost Converter Based on Fuzzy Logic Controller

Photovoltaic (PV) systems are dependent on two main factors of temperature and solar radiation, changing the PV system into a nonlinear system. Therefore, it is necessary to propose an intelligent control system for power control of PV systems to tackle this issue. So, a three-level boost converter (TLBC) based on the maximum power point tracking (MPPT) with fuzzy intelligent control is suggested to solve the problems. In this paper, instead of using the conventional boost converter, TLBC is used. However, the conventional boost converter is typically used in PV systems as the interface between the PV panel and the consumer. TLBC has a lower weight and cost than the conventional boost converter. In addition, the main scope of this paper is reducing the system weight and employing TLBC with MPPT for controlling the output power without any fluctuations. In addition, the MPPT controller for TLBC is developed based on fuzzy logic and is compared with perturb and observe (P&O) algorithm, proportional–integral (PI) controller, particle swarm optimization (PSO) algorithm, and hybrid simplified accelerated particle swarm optimization (HSAPSO) algorithm. Using fuzzy logic controller (FLC), the value of MPP is tracked suitably under different climatic conditions as well as different temperatures and radiation, where TLBC passes the energy from a PV panel to the output in a high-speed and free-oscillation manner. Furthermore, balancing the voltage of TLBC capacitors with the proportional controller (P) is done due to their non-equivalent series resistance. The simulation results in MATLAB suggest the accuracy and performance of the system.