Abstract
The rapid integration of renewable energy sources (RES) into power systems emphasizes the need for advanced inverter technology that effectively manages the variability and integration challenges of renewable energy. Multilevel inverters (MLIs), recognized for their ability to minimize harmonic distortion and improve electrical performance, have become increasingly pivotal in addressing these needs. This paper focuses on the challenges associated with integrating MLIs into RES, particularly the complexity of control and coordination required to ensure efficient operation. We present a novel 15-level cascaded H-bridge multilevel inverter optimized for renewable energy applications, incorporating both solar photovoltaic (PV) systems and battery energy storage systems (BESS). The innovative control strategy employed uses a reinforcement learning algorithm to manage the dynamic interaction between the RES inputs and MLI outputs, ensuring optimized performance under varying conditions. The results demonstrate a robust, adaptable MLI design that reduces component count and enhances operational efficiency, thus validating the effectiveness of the proposed MLI in managing the intricacies of renewable energy integration, offering a significant improvement over traditional systems in terms of efficiency and reliability. The study's outcomes have implications for advancing RES integration technologies, marking a step forward in sustainable energy solutions.
Published Version
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