Implementation of Multilayer Fifth-Order Generalized Integrator-Based Adaptive Control for Grid-Tied Solar PV Energy Conversion System

Abstract

This paper presents an adaptive control approach based on a novel multilayer fifth-order generalized integrator (MFOGI) and single-input fuzzy-tuned proportional-integral (PI) controller for single-phase two-stage grid-connected partially shaded solar photovoltaic (PV) system, where the global maximum power point (GMPP) is tracked by using a novel human psychology optimization (HPO) algorithm. The MFOGI is used to extract the fundamental component from the grid voltage, even when the grid voltage is characterized by undervoltage, overvoltage, severe harmonics distortion, frequency variations, direct current (dc) offset, etc., on a wide range. Moreover, the single-input fuzzy-tuned PI controller is used for online PI controller gains tuning during different disturbances and dynamic conditions. To ensure a fast dynamic response, a PV feed-forward component is also included in the control algorithm as well as HPO is developed for quick GMPP tracking (GMPPT). The proposed control is modeled and simulated in MATLAB platform, as well as tested on a developed prototype in the laboratory. During simulation and testing, overvoltage, undervoltage, severe harmonics distortion, and dc offset in grid voltage, as well as insolation and temperature variations on PV array are considered. The total harmonic distortions in grid current, during the different complex disturbances and dynamic situations, are found very less, in comparison to the state-of-the-art techniques and IEEE-519 standard, as well as due to the HPO algorithm, the GMPPT time is very less, which shows the superiority over state-of-the-art techniques.