A Review on Performance Enhancement of Multilevel Inverters in Renewable Energy Systems Through Advanced Modulation Techniques

Optimised power conversion technologies are in high demand as a result of the introduction of renewable energy sources (RES) including solar, wind, and hydro to the electrical grid. Multilevel inverters (MLIs) have emerged as practical solutions that outperform the conventional two-level inverter in terms of power quality, advantages, efficiency, and harmonic distortion reduction. MLIs transform the RES's fluctuating output from DC to AC so that it may be fed into the grid. The MLI's performance becomes better as the number of voltage levels rises. Because they produce more sinusoidal voltage (better) waveforms, inverter topologies including 5-level, 7-level, and 9-level inverters have received attention for reducing total harmonic distortion (THD) and enhancing system dependability. This study will discuss how sophisticated modulation strategies might increase MLI performance for renewable energy systems. The decrease of switching losses, voltage control, and system efficiency are examined in relation to the key modulation methods of concern here, which include Sinusoidal Pulse Width Modulation (SPWM), Space Vector Modulation (SVM), and Selective Harmonic Elimination (SHE). The study also addresses issues that need intricate solutions for large-scale renewable energy systems, such as sophisticated control algorithms, voltage balancing, and thermal management for higher-level inverters. Along with potential dynamic environment applications, it also explores the potential role of AI-based modulation strategies to further realise performance increase in MLI. For potential future applications in intelligent and adaptive power conversion technologies for renewable energy, the research concludes with a comparative analysis of a few MLI topologies and modulation techniques. Keywords: Multilevel Inverter (MLI), Modulation Techniques, Total Harmonic Distortion (THD), Renewable Energy Systems, Artificial Intelligence (AI)