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    INTELLIGENT CONTROL TECHNIQUE OF SOLAR PANEL USING NANOFLUID AND POROUS MEDIA
    (2023-08) Aldaaeawe, Alyaa Jaafar Abdulhasan
    The operating temperature of the cells influences the electrical parameters of the photovoltaic modules due to the properties of the crystalline silicon used in photovoltaic panels. The aim of this thesis is to design and experimentally build a photovoltaic panel and to collect data. PV temperature was experimentally checked with and without nanofluid. Experimental works were performed to collect the parameters (ambient temperature, irradiance, humidity, wind speed, and the temperature of the PV module). In addition, the collected input and output data were used to develop a neural network time series with three models, NAR, NARX and nonlinear. The data obtained from the network time series were compared with the parameters of the fuzzy PID controller. The porosity magnitude of the system was used as 0.965. The results showed that NARX with MSE is the best modelling method with 0.2255, while the worst nonlinear I/O with MSE is 2.57. Also, the results manifested that MSE is the best way to control this system with the values of KP, KI, and KD as 80, 88.05, and 11.1, respectively. A cooling system was connected to the PV module, which consists mainly of a jacket (water container) mounted on the back of the PV panel. Al2O3 nano particles were added to the water with a size 20 nm to create nanofluid with concentration of 2 wt.%. The reduction in temperature with using nanofluid as coolant was seen as 23 ºC when compared to non-cooling case. It was concluded that the overall efficiency of the panel increases to 111% with using nanofluid, compared to without cooling case (40%). In the last part of the thesis study, the usage of the controller in the system with the panel temperature set point was carried out. The temperature was set to 40 ?C and it was determined that the control system successfully reaches the set temperature.