Current Issue : October - December Volume : 2017 Issue Number : 4 Articles : 5 Articles
Solar cells are now widely used as a clean method for electric energy generation.\nAmong various type of solar cells, we compared the ability between\namorphous and tandem (amorphous and polycrystalline) silicon solar cells by\nmeans of simultaneous running test. This kind of comparison is of importance\npractically, because the comparison of only inherent characteristics\ncannot include environmental parameters such as temperature totally. It was\nconcluded that both types of solar cells provided almost the same energy for\none year. The amorphous silicon solar cell provided more energy in summer\nwhile the tandem solar cell was advantageous in winter. It is due to the fact\nthat the decrease in energy conversion at the higher cell temperature is more\nnoticeable in tandem solar cells....
The optics of axial silicon nanowire solar cells is investigated and compared to silicon\nthin-film solar cells with textured contact layers. The quantum efficiency and short circuit current\ndensity are calculated taking a device geometry into account, which can be fabricated by using\nstandard semiconductor processing. The solar cells with textured absorber and textured contact\nlayers provide a gain of short circuit current density of 4.4 mA/cm2 and 6.1 mA/cm2 compared to a\nsolar cell on a flat substrate, respectively. The influence of the device dimensions on the quantum\nefficiency and short circuit current density will be discussed....
In recent years, learning based machine intelligence has aroused a lot of attention across science and engineering. Particularly in\nthe field of automatic industry inspection, the machine learning based vision inspection plays a more and more important role\nin defect identification and feature extraction. Through learning from image samples, many features of industry objects, such as\nshapes, positions, and orientations angles, can be obtained and then can be well utilized to determine whether there is defect\nor not. However, the robustness and the quickness are not easily achieved in such inspection way. In this work, for solar panel\nvision inspection, we present an extreme learning machine (ELM) and moving least square regression based approach to identify\nsolder joint defect and detect the panel position. Firstly, histogrampeaks distribution (HPD) and fractional calculus are applied for\nimage preprocessing. Then an ELM-based defective solder joints identification is discussed in detail. Finally, moving least square\nregression (MLSR) algorithm is introduced for solar panel position determination. Experimental results and comparisons show\nthat the proposed ELM and MLSR based inspection method is efficient not only in detection accuracy but also in processing speed....
We demonstrated an indium tin oxide (ITO)-free, highly transparent organic solar cell with\nthe potential to be integrated into window panes for energy harvesting purposes. A transparent,\nconductive ZnO/Ag/ZnO multilayer electrode and a Ag:Ca thin film electrode were used in this\ntransparent device as the bottom and top electrode, respectively. To further improve the transmittance\nof the solar cell, the thickness of the top ZnO layer was investigated both experimentally and with\nsimulations. An average visible transmittance of >60% was reached, with a maximum transmittance\nof 73% at 556 nm. Both top and bottom illumination of the solar cell generated comparable power\nconversion efficiencies, which indicates the wide application of this solar cell structure. In addition,\nwe fabricated distributed Bragg reflector mirrors with sputtered SiO2 and TiO2, which efficiently\nincreased the power conversion efficiency over 20% for the solar cells on glass and poly(ethylene\nterephthalate) (PET) substrates....
Technologies influencing alternative means of transportation have been expanding in recent\nyears due to increasing urbanization and motorization. In this paper, a solar powered electric\nauto-rickshaw (SPEA) is designed and developed for Indian conditions. The vehicle developed is\ncomprehensively analyzed techno-economically for its viability in the Indian market. The performance\nanalysis of SPEA results in an optimal charging rate of 2 kWh per day with an average solar irradiance\nof 325 W/m2 on a typical sunny day. The discharging characteristics are studied based on different\nloading conditions. The vehicle achieved a maximum speed of 21.69 km/h with battery discharge rate\nof 296Wat 90 kg load and also reached a maximum discharge rate of 540Wat 390 kg loading with a\nmaximum speed of 12.11 km/h. Environmental analysis of SPEA indicated that the yearly CO2 emissions\nof 1777 kg, 1987 kg and 1938 kg from using Compressed Natural Gas, Liquefied Petroleum Gas and\ngasoline engines respectively can be mitigated using SPEA. The financial analysis of SPEA concluded\nthat the investor�s payback duration is 24.44% less compared to a gasoline-run vehicle. Socio-Economic\nanalysis of SPEA discussed its significant advantages and showed 15.74% and 0.85% increase in yearly\nincome over gasoline driven and battery driven vehicles....
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