Open AccessImplementation of Intelligent Controlling Mechanism to Improve Conversion Efficiency of Solar PV Module
Author(s) -
Kakarla Deepti
Publication year - 2020
Publication title -
international journal of modern trends in science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-3778
DOI - 10.46501/ijmtst060526
Subject(s) - duty cycle , computer science , photovoltaic system , maximum power point tracking , matlab , controller (irrigation) , automaton , learning automata , artificial neural network , control engineering , maximum power principle , fuzzy logic , control theory (sociology) , control (management) , artificial intelligence , inverter , engineering , voltage , electrical engineering , agronomy , biology , operating system
The research article aims at an intelligent control method to improve conversion efficiency of solarphotovoltaic module by tracking maximum operating point irrespective of variations in temperature andirradiance. A novel hybrid maximum power point based on learning automata is proposed. The algorithmworks in two stages, first the learning automata detects the temperature and irradiation of light incidentingon PV module, second it identifies the zone of operation and adjusts the duty cycle of DC-DC converter. Thisimplementation is done by designing the learning automata using artificial neural network and theadjustment of duty cycle is implemented with fuzzy logic controller. The design is verified usingmatlab/simulink environment.