Modeling and control of grid-connected transformerless inverter based on improved fruit fly algorithm optimisation

Abstract

Grid-connected transformerless inverters play a crucial role in modern power systems, facilitating the integration of renewable energy sources into the grid. This study focuses on optimising the performance of such inverters using an improved fruit fly algorithm (IFFAO). The research methodology involves algorithm development, modelling, simulation, and experimental validation. The IFFAO algorithm is tailored to meet the specific optimisation requirements of grid-connected transformerless inverters, enhancing search mechanisms and convergence characteristics. Mathematical models of the inverter system are constructed to capture dynamic behaviour under various operating conditions. Simulation in MATLAB/Simulink optimizes control parameters using the IFFAO algorithm, followed by experimental validation on a physical prototype. Results demonstrate high efficiency (98.5%) with minimal energy losses, low total harmonic distortion (2.1%), and efficient maximum power point tracking (99.2%). Rapid response time (5.7 milliseconds) ensures grid stability. Statistical analysis confirms consistent performance across trials. The proposed methodology effectively optimizes grid-connected transformerless inverters, enhancing efficiency, reliability, and sustainability in solar energy conversion systems.