Abstract
DC/AC inverters play a vital role in microgrids, efficiently converting renewable energy into usable AC power. Parallel operation of inverters presented numerous challenges, including maximizing system efficiency, minimizing circulating current, and maximizing system accuracy. This proposal introduces an analytical optimization technique designed to enhance the efficiency of paralleled inverters in microgrid systems while minimizing circulating current. The system parameter estimation is performed with a rapid recursive least squares (RLS) estimator. An optimized proportional-integral-derivative (PID) controller achieves high accuracy and streamlining system construction. The performance of the proposed optimizer is compared to common optimization methods, such as particle swarm optimization (PSO), neural networks, interior search, and interior point optimizers, focusing on system efficiency and eliminating circulating currents. Simulation investigations validated the method's applicability and demonstrated the proposed optimizer's superiority in efficiency, stability, and limiting circulating currents. It also achieved zero execution time, significantly outperforming alternatives like the neural network optimizer, which took 0.693 s. In various scenarios, the proposed optimizer improved system efficiency by 3% compared to the equally shared current system.