Enhancing grid-tied solar energy systems with adaptive interval type-2 fuzzy tuned affine projection Lorentzian control for improved power quality

The increasing integration of distributed energy resources has significantly impacted power quality in modern grids. This article addresses the challenge by introducing an advanced control methodology for grid-tied solar energy systems, employing an interval type-2 fuzzy tuned affine projection Lorentzian technique to enhance the performance of three-phase voltage source converters, thereby achieving superior power quality. Key features of the proposed approach include harmonic suppression and load balancing, which are crucial for maintaining grid stability. The proposed technique effectively resolves the tradeoff between steady-state error and convergence rate, ensuring robust performance regardless of load distortions. The algorithm's robustness and stability are rigorously tested under varying conditions, such as fluctuating irradiance, balanced loads and unbalanced loads. Validation through real-time controllers and software-in-loop implementation using the dSPACE 1202 controller demonstrates the system's efficacy in both dynamic and steady-state scenarios. This research exemplifies the practical application of interval type-2 fuzzy to enhance the reliability and stability of grid-tied solar energy systems.