Research on intelligent auxiliary regulation technology of large power grid section based on artificial intelligence

Abstract

In the modern era, large-scale renewable energy systems are integrated with advanced power systems and provide efficient operations. Also, optimized power systems require accurate energy generation and effective control systems to manage and ensure a stable power supply. Nevertheless, uncertainties are the intermittent balance of supply and high electricity demand. In addition, conventional power sources are not applicable for this challenging task and increase electricity costs. Therefore, an efficient Neuro Fuzzy Single phase Unified Power Quality Conditioner with Maximum Power Point Tracking (NF-SP UPQC -MPPT) strategy is developed for enhancing the grid-connected power systems. Here, Neuro-fuzzy logic is used as dynamic reactive power compensation in the grid. Also, this logic can efficiently handle the Energy storage system (ESS). Then SP UPQC was used to enhance power quality in electrical distribution systems. It combines both series and shunt compensators to mitigate various power quality issues such as voltage sags, harmonics, and unbalance. After that MPPT was utilized to extract the maximum power from the grid system. Model Predictive Control (MPC) controller to determine the overall stability and performance of the system. Moreover, the developed model was implemented on the MATLAB platform and performance is analyzed in terms of voltage deviation, grid current, reactive power fluctuations and Total Harmonic Distortion (THD).