Sun Flower Optimization with Self-Tuned Fuzzy Logic MPPT Controller and Reactive Power Compensation for Grid-Connected PV System

Abstract

This paper presents a detailed study on the analysis of the reactive power compensation methodology used for delivering the maximum power to single-phase grid–PV systems. The main purpose of this work is to develop a Sunflower Optimization (SFO) integrated with a Self-tuned Fuzzy Logic Controller (SFLC)-based Maximum Peak Point Tracking (MPPT) controlling mechanism for extracting the maximum power from the solar PV system. For this, an efficient Entwined LUO (ELUO) DC-DC converter has been utilized that helps to regulate the output voltage with reduced ripples. Also, the inverter provides real power in addition to the reactive power without exceeding its current limit. For controlling the capability of energy transmission, the Phased Locked Loop (PLL) based synchronization is performed at the point of common coupling. Additionally, the LCL filtering technique is employed to reduce the harmonics and unbalanced current efficiently. The proposed system improves the overall system performance by producing grid-side current in a clean sinusoidal shape with an appropriate phase shift in grid voltage. The simulation and experimental results are validated to demonstrate the effectiveness of the proposed control method.