Open AccessSingle Phase Water Pumping System using Adaptive Neuro Fuzzy Inference MPPT for PV system
Author(s) -
M. Kabilan,
V. Gopalakrishnan
Publication year - 2022
Publication title -
journal of electronics and informatics
Language(s) - English
Resource type - Journals
ISSN - 2582-3825
DOI - 10.36548/jei.2022.1.002
Subject(s) - maximum power point tracking , photovoltaic system , adaptive neuro fuzzy inference system , water pumping , charge controller , control theory (sociology) , computer science , renewable energy , maximum power principle , battery (electricity) , automotive engineering , engineering , power (physics) , inverter , voltage , fuzzy control system , electrical engineering , fuzzy logic , artificial intelligence , physics , mechanical engineering , control (management) , quantum mechanics , inlet
The demand for water in India steadily increases as the population grows. Due to its numerous advantages, research in AC motor-based Water Pumping Systems (WPS) has recently got a lot of attention. Because of its natural abundance and ecologically beneficial properties, renewable energy-based solar photovoltaic (PV) generation is the ideal substitute for conventional energy sources. Maximum power extraction from the PV system is critical for increasing solar power generation efficiency. This proposed work presents a solar power system using Adaptive Neuro-Fuzzy Inference System (ANFIS) Maximum Power Point Tracking (MPPT) for pumping system. A MPPT controller based on ANFIS has been introduced in this research. This approach has the advantage of having a higher tracking accuracy. This tracker captures irradiance and temperature from the solar panel as inputs. This system uses a battery backup for energy storage purpose. The battery is recharged using the solar supply. In this system, Pulse Width Modulated (PWM) inverter is used, where it converts the battery voltage (DC), into AC voltage for running the pumping system. For validation, the proposed model is analysed using MATLAB/Simulink.