A PV-Fed Reduced-Switch Nine-Level Inverter for Home Grid Interfacing and Electric Vehicle Charging
Abstract
The rapid penetration of photovoltaic (PV) based distributed generation and the growing demand for residential electric vehicle (EV) charging systems necessitate compact, efficient, and high-power-quality inverter topologies. Conventional multilevel inverters suffer from increased component count, higher switching losses, and complex control requirements, which limit their suitability for home-grid and EV charging applications. This paper presents a PV-fed reduced-switch nine-level switched-capacitor inverter designed to support both grid-connected and islanded operation while supplying residential loads and EV chargers. The proposed topology generates nine distinct voltage levels (±4Vdc, ±3Vdc, ±2Vdc, ±Vdc, and zero) using only eight power switches, four capacitors, and three diodes, thereby significantly reducing hardware complexity and switching losses compared to conventional multilevel inverter structures. A boost converter integrated with a Perturb and Observe (P&O) based Maximum Power Point Tracking (MPPT) algorithm ensures optimal power extraction from the PV array under varying irradiation conditions. Furthermore, a fuzzy logic-based control strategy is employed for grid synchronization, voltage regulation, and smooth transition between grid-connected and islanded modes. The proposed system is validated through detailed MATLAB/Simulink simulations. Simulation results demonstrate stable operation under irradiation variation, load changes, and grid disconnection scenarios. The inverter achieves a high-quality output with a load current total harmonic distortion (THD) of approximately 0.22%, satisfying grid power quality standards. The results confirm that the proposed reduced-switch nine-level inverter is a compact, efficient, and cost-effective solution for PV-based home-grid integration and EV charging applications.
Fields of Study & Subjects
Multilevel Inverters and Converters
Photovoltaic System Optimization Techniques
Microgrid Control and Optimization
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 29 January 2026