Ceylan, IlhanGedik, EnginErkaymaz, OkanGurel, Ali Etem2024-09-292024-09-2920140378-77881872-6178https://doi.org/10.1016/j.enbuild.2014.08.003https://hdl.handle.net/20.500.14619/4578Artificial neural network (ANN) is a useful tool that using estimates behavior of the most of engineering applications. In the present study, ANN model has been used to estimate the temperature, efficiency and power of the Photovoltaic module according to outlet air temperature and solar radiation. An experimental system consisted photovoltaic module, heating and cooling sub systems, proportional integral derivative (PID) control unit was designed and built. Tests were realized at the outdoors for the constant ambient air temperatures of photovoltaic module. To preserve ambient air temperature at the determined constant values as 10, 20, 30 and 40 degrees C, cooling and heating subsystems which connected PID control unit were used in the test apparatus. Ambient air temperature, solar radiation, back surface of the photovoltaic module temperature was measured in the experiments. Obtained data were used to estimate the photovoltaic module temperature, efficiency and power with using ANN approach for all 7 region of the Turkey. The study dealing with this paper not only will beneficial for the limited region but also in all region of Turkey which will be thought established of photovoltaic panels by the manufacturer, researchers and etc. (C) 2014 Elsevier B.V. All rights reserved.eninfo:eu-repo/semantics/closedAccessSolar energyPhotovoltaicArtificial neural networkArticle10.1016/j.enbuild.2014.08.0032-s2.0-84907499603267Q125884WOS:000345182000025Q1