Open AccessSimulation and Control of Photovoltaic Panel Using Nonlinear Autoregressive Moving Average (NARMA Controller)
Author(s) -
Ahmed Harb Najd,
Filiz Sarı
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1279/1/012013
Subject(s) - photovoltaic system , control theory (sociology) , controller (irrigation) , maximum power principle , maximum power point tracking , renewable energy , power (physics) , electric power , autoregressive model , electric power system , computer science , automotive engineering , engineering , electrical engineering , mathematics , voltage , physics , control (management) , artificial intelligence , statistics , agronomy , quantum mechanics , inverter , biology
Recently, the photovoltaics (PVs) is considers as one of important renewable energy systems. Generally, The PVs cell is detecting the solar radiation and converted it into a power electric DC current. In this paper, the PV has designed to produce power electrical of certain power and it has given that power with standard temperatures conditions designed at (1000 W/m 2 , 25 °C) for temperature and solar radiation. In case of increase or decrease in the temperature values and solar radiation the power value will be reduced. Besides, the control systems has utilized to control the power value that effected by the radiation and temperature of the PV system. An artificial neural network (ANN) technique which is nonlinear autoregressive moving average (NARMA) has used to the purpose of get the high efficiency and controlling the maximum power point (MPP) at different conditions of radiation and temperature. This control will be carried out by applying a PV model using the equivalent circuit of the PV. MATLAB-based modelling will be used for simulation and compared between results before and after using NARMA controller.