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Title:	Theoretical and indoor experimental investigations of different types of dust on the photovoltaic module performance
Authors:	Zeki Ahmed Darwish (P64493)
Supervisor:	Kamaruzzaman Sopian, Prof. Dato' Dr.
Keywords:	Photovoltaic cells Universiti Kebangsaan Malaysia -- Dissertations Dissertations, Academic -- Malaysia
Issue Date:	3-Dec-2018
Description:	Dust accumulation has been one of the main contributing factors for the power loss of photovoltaic (PV) module. Dust consists of small particles that float throughout the atmosphere. The types of the dust often have not been taken into consideration. The aim of this research was to investigate the effect of different types of dust particles on PV performance. The dust particles investigated were Carbon (C), Iron (III) oxide (Fe2O3), Manganese dioxide (MnO2), Mix, Calcium oxide (CaO), Magnesium oxide (MgO), Titanium dioxide (TiO2), Chromium (III) oxide (Cr2O3), Calcium carbonate (CaCO3), Calcium sulfate (CaSO4), includes Lead monoxide (PbO), Aluminum oxide (Al2O3), Calcium sulfate dehydrate (CaSO4.2H2O), Potassium carbonate (K2CO3), Silicate (SiO3) and Sodium chloride (NaCl) (Salt). The study consists of two parts, the first part focused on the effects of different types of pollutants on the external load. The second part focused on the PV performance at variable load. An indoor solar simulator with 23 units of halogen tungsten lamps, with an output power of 11.5kW has been built. The effect of these dust particles on the PV module performance, the current, voltage, power and efficiency of the external load were studied. Other parameters measured were Isc, Im, Voc, Vm, Pm, E, FF, Rs, Rsh and Rm. The IV curves were also plotted. The first dust classification was based on experimental results and classified into four groups namely Group A, Group B, Group C and Group D. The second dust classification was based on modelling using the Adaptive Neuro-Fuzzy Inference System (ANFIS) in MATLAB to predict the type of dust using the data of the effect of 17 types of dust on the PV performance. The experimental and modelling results showed closed agreement on the impact of dust on PV module for fixed load. The overall cross-validation results in terms of RMSE and NDEI is 4.33 and 0.88 respectively. All the resulting classes were in close agreement to the original classes with the average differences of 0.46 only. The values for the observed reduction in the current and voltage of the module with increasing the dust deposition from (0-164.38) g/m2 can be seen on the values power and efficiency. Carbon dust has significant effect on the PV module performance while the Sodium chloride has the least effect. The reduction of the efficiency reached 99% at 20.54 g/m2 for Carbon and 12.61% for NaCl at 164.38 g/m2. Mathematical models for the reduction of efficiency using by CFTOOL of MATLAB and multiple linear regression method were developed and found compatible with the experimental results. Design Expert 10 software was used to evaluate the significant factors in the mathematical model based on the Response Surface Methodology using an F - test. These models have been compared with some of the previous models in literature and valid only for small values for dust deposition density. The multiple regression model was applied to different data and locations around the world and the predicted values were consistent with the actual AC (kWh) data with maximum error of 3.38%. The model was successfully applied in the locations of Kuala Lumpur (Malaysia), Dubai (United Arab Emirates), Sohar (Oman), Kolkata (India), Cairo (Egypt), Berlin (Germany), Paris (France), and Melbourne (Australia).,Ph.D.
Pages:	292
Call Number:	TK8322.D347 2018 3 tesis
Publisher:	UKM, Bangi
Appears in Collections:	Solar Energy Research Institute / Institut Penyelidikan Tenaga Suria (SERI)

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