Open AccessGrid Integration using ANFIS for Hybrid DG and Storage Units to Control and Manage Power
Author(s) -
Ginga Madhu
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.38497
Subject(s) - adaptive neuro fuzzy inference system , photovoltaic system , microgrid , computer science , automotive engineering , renewable energy , grid , supercapacitor , energy storage , power (physics) , fuzzy control system , electrical engineering , engineering , fuzzy logic , chemistry , physics , geometry , mathematics , electrode , quantum mechanics , artificial intelligence , electrochemistry
The significant role in the DC micro grid is renewable sources like hydrogen energy, Photovoltaic (PV), and wind systems. However, the difficult task in the DC micro grid is to balance the power generation and load demand due to the continuous changes in sustainable sources. In this study, focused on the power control and stabilize the power at different dynamic conditions with power management approaches. In this paper, fuel cell (FC), lithium-ion based batteries and super capacitors (SC) are proposed with PV based DC micro grid system for improving the system performance. Furthermore, adaptive neuro-fuzzy inference system (ANFIS) is suggested in this system for mitigating the deviations in PV plant due to variations in temperature. The suggested system has been designed on the MATLAB environment. The simulation results reveal that the suggested approaches give better improvement in various operating conditions with ANFIS approach. Keywords: PV system, Fuel cell, supercapacitor, ANFIS, DC Microgrid.