Optimized Control of PUC7 Inverter in Photovoltaic Grid Integration

The growing concerns regarding fossil fuels, harmful emissions, and the negative impacts of nuclear energy have underscored the urgent need to transition towards renewable energy sources. Renewable energy technologies, particularly photovoltaic systems, offer a sustainable solution to the escalating energy demands while mitigating the adverse effects of climate change by reducing greenhouse gas emissions and decreasing dependence on limited fossil fuel supplies. PV technology, characterized by its versatility, accessibility, and decentralized nature, plays a pivotal role in promoting energy security and economic growth. However, integrating PV systems into existing grids necessitates maintaining high power quality, which is often challenged by voltage irregularities, harmonic distortions, and reactive power requirements. Multilevel inverters, such as the packed U cell converters, emerge as effective solutions to enhance power quality by generating high-fidelity sinusoidal waveforms with minimal distortion. This study introduces an innovative metaheuristic technique, leveraging a Cuckoo Search Algorithm, to optimize the weighting factor in the Finite Control Set Model Predictive Control strategy for a grid-connected seven-level PUC7 inverter. The proposed method aims to reduce the Total Harmonic Distortion and improve the overall performance of the inverter under varying operating conditions. Key contributions include the development of a new multifunction solar active power system using a double-stage PUC7 inverter, a novel MPC algorithm for ensuring power injection and voltage balance, and an optimized control approach that enhances stability and robustness. The findings demonstrate that the optimized control strategy significantly improves power quality and system efficiency, providing a promising solution for modern renewable energy applications.