Fuzzy Adaptive Droop Controlled Parallel Inverters for Microgrid Applications

Abstract

Due to rising energy consumption and global climate change difficulties, distributed generation, smart grid, and renewable energy technologies are gaining traction as solutions to global problems. Conventional power systems have been prone to reliability issues, especially with the increase in the electrical power grid. In future, microgrids (MGs) will become a potential trend in power systems. The prime focus of this paper is on the parallel control of inverters which act as grid forming inverters. A comparative study and analysis was done on the droop control, fuzzy adaptive droop control of the voltage source inverters in a stand-alone MG. Droop control scheme imitates the droop characteristics of generators in a conventional grid and controls the frequency and terminal voltage of output in accordance with variation in output power. It allows for decentralized control without the need for external communication lines. These solutions allow for a "plug-andplay" interface and improve system reliability. However, these Vikash Gurugubelli, Student Member, IEEE Department of Electrical Engineering National Institute of Technology Rourkela, India vikas0225@gmail.com as having numerous inverters connected in parallel [6-9]. The so-called distributed generation, which connects generation to the distribution network, is gaining popularity. DG refers to mini-scale generation that is ideally situated near demand to minimize power losses. inverters have no ability to inject virtual inertia adaptively as per power variations. It's prone to slow transient response and frequency and amplitude deviations, and ineffective reactive power-sharing. A novel adaptive droop control scheme with fuzzy logic based virtual moment of injection was proposed to address the issues. In this way, when there’s any deviation in frequency and voltage due to disturbances, the proposed model adaptively varies the droop coefficients to provide better transient response. The simulation results of both the control schemes were compared and an improvement in performance was observed in the adaptive mode.