Overview

Power electronics converters are essential for integrating renewable energy sources (RESs) into the grid. My research journey began with an exploration of various types of multilevel inverters (MLIs). During my Master’s studies, I focused on developing advanced and efficient MLI topologies. While these MLIs were primarily validated under open-loop control environments, it became clear that real-world applications required more sophisticated control solutions as well. This realization motivated me to delve into closed-loop control techniques for converters, ultimately leading me to pursue a PhD.

During my PhD, I explored various closed-loop control strategies for grid-connected voltage source converters (VSCs). My research demonstrated the potential of artificial intelligence (AI)-based control techniques for VSC systems. The goal was to develop advanced control mechanisms for RES systems, particularly solar photovoltaics (PV). We introduced AI-based control solutions for single-stage grid-connected PV systems, ensuring effective operation under various practical scenarios such as partial shading, real-time irradiance, and temperature conditions.

Through this work, we identified a growing need for updated regulations to ensure the active involvement of distributed generation (DG) sources in enhancing system stability. International grid codes are also getting revised, mandating DGs like solar PVs to contribute ancillary services such as frequency support. In response, we developed an advanced AI-based scheme for PV systems that adjusts its output power to support grid frequency when necessary.

Building on this foundation, my current work focuses on developing grid-forming control strategies to enable grid-supporting features (both voltage and frequency) in enhanced STATCOM systems. These advancements will be directly used by various transmission companies to address the stability issues of solar and wind farm systems.