Advanced Energy Technologies
Mubarak A. Amoloye; Sulyman A. Abdulkareem; Adewale George Adeniyi
Abstract
The drive to move away from fossil fuels and related products has drawn significant attention to biomass and biomass-related products in recent times. This study reports the effect of three forest biomass sources namely acacia auriculiformis, terminalia randii, and delonix regia as combustion fuels in ...
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The drive to move away from fossil fuels and related products has drawn significant attention to biomass and biomass-related products in recent times. This study reports the effect of three forest biomass sources namely acacia auriculiformis, terminalia randii, and delonix regia as combustion fuels in a retort heated, low-temperature and top-lit updraft gasifier on biochars produced from two agricultural wastes: corn husk and corn cob. The combustion fuels were characterized using Thermogravimetric/Differential thermogravimetric analysis. Their TGA data were fitted to 16 kinetic models using the Coats-Redfern method. Characterization of the products was performed using Scanning Electron Microscopy/Energy Dispersive X-ray Spectroscopy and Fourier Transform Infra-Red Spectroscopy. Results revealed similar decomposition trends for combustion fuels. Different kinetic models predicted decomposition mechanisms of combustion fuels for the regions considered. Negative correlation was found between biochar yields and increasing carbonization temperatures with yields ranging from 64.6-37.8 % and 28.4-24.5% for corn husk and cob, respectively. Results indicate similar effects of combustion fuels on functional groups contained in biochar samples.
Advanced Energy Technologies
Abbas Ahmadi; Mahsa Zaman; Siab Mamipour
Abstract
Clean solar energy is one of the best sources of energy. Solar power plants can generate electricity in Iran due to their large number of sunny days. This paper presents a short-term forecasting approach based on artificial neural networks (ANNs) for selected solar power plants in Iran and ranks the ...
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Clean solar energy is one of the best sources of energy. Solar power plants can generate electricity in Iran due to their large number of sunny days. This paper presents a short-term forecasting approach based on artificial neural networks (ANNs) for selected solar power plants in Iran and ranks the input variables of the neural network according to their importance. Two solar power plants in Hamadan province (Amirkabir and Khalij-Fars) were selected for the project. The output of solar power plants is dependent on weather conditions. Solar radiation on the horizontal plane, air temperature, air pressure, day length, number of sunny hours, cloudiness, and airborne dust particles are considered input variables in this study to predict solar power plant output. Forecasting model selection is based on considering zero and nonzero quantities of target variables. The results show that solar production forecasting based on meteorological parameters in the Khalij-Fars is more accurate than Amirkabir. The global solar radiation, air temperature, number of sunny hours, day length, airborne dust particles, cloudiness, air pressure, and dummy variables[1] are the order of the most important inputs to solar power generation. Results show simultaneous influences of radiation and temperature on solar power plant production.
[1]. The first half of the year is counted as one, and the second half is counted as zero.
Advanced Energy Technologies
Ming Hung Lin; Juin Hung Lin; Mamdouh El Haj Assad; Reza Alayi; Seyed Reza Seyednouri
Abstract
The optimal combination of distributed generation units in recent years has been designed to improve the reliability of distributed generation systems as well as to reduce losses in electrical distribution systems. In this research, the improved Genetic Algorithm has been proposed as a powerful optimization ...
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The optimal combination of distributed generation units in recent years has been designed to improve the reliability of distributed generation systems as well as to reduce losses in electrical distribution systems. In this research, the improved Genetic Algorithm has been proposed as a powerful optimization algorithm for optimizing problem variables. The objective function of this paper includes power loss reduction, hybrid system reliability, voltage profile, optimal size of distributed generation unit, and finally improvement of the construction cost of combined wind and solar power plants. Therefore, the problem variables are subject to reliable load supply and the lowest possible cost during the optimization process. In order to achieve this goal in this study, the IEEE standard 30-bus network is examined. The results of the system simulation show the reduction of total system losses after DG installation compared to the state without DG and the improvement of other variable values in this network. This loss index after installing DG in the desired bus has a reduction of about 200 kWh during the year and has a value equal to 126.42 kWh per year.
Advanced Energy Technologies
Gunasagar Sahu; Hifjur Raheman
Abstract
A solar energy operated two-row weeder was developed for weeding in wetland paddy crop. Its major components are power source, power transmission system, weeding wheels, and a float. The power source comprised a DC motor, solar panel, and power storage unit with maximum power point tracker and motor ...
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A solar energy operated two-row weeder was developed for weeding in wetland paddy crop. Its major components are power source, power transmission system, weeding wheels, and a float. The power source comprised a DC motor, solar panel, and power storage unit with maximum power point tracker and motor controller. Solar panel/power storage unit through a motor controller supplied power to the DC motor and it was transmitted to the shaft of the weeding wheel through a dog clutch. A pair of wheels attached with jaw tooth and plane blades at wheel circumference was used for carrying out weeding and movement of the weeder in the field. A float was used to prevent sinkage of the weeder in soft soil which, in turn, ensured stability during operation. The developed weeder could do weeding at a rate of 0.06 ha per hour with field efficiency, weeding efficiency, and plant damage of 83.3 %, 83 % and 2-3 %, respectively. As compared to cono-weeder, the cost of weeding was 41.2 % lower due to higher field capacity and fewer labor requirements. Annual use less than 4.13 ha for the developed weeder was found uneconomical for carrying out weeding. The developed powering system comprising solar photovoltaic panels could supply power to do weeding continuously for 2 hours with a maximum discharge of 20 % from the battery.
Advanced Energy Technologies
Payam Ghorbannezhad; Maryam Abbasi
Abstract
Fast pyrolysis of sugarcane bagasse was investigated in a tandem micro-pyrolyzer. The effects of temperature and particle size on the phenolic compounds and hemicellulose products distribution were examined during fast pyrolysis process. For this, changes in the micro-reactor parameters were made (particle ...
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Fast pyrolysis of sugarcane bagasse was investigated in a tandem micro-pyrolyzer. The effects of temperature and particle size on the phenolic compounds and hemicellulose products distribution were examined during fast pyrolysis process. For this, changes in the micro-reactor parameters were made (particle size between 0.1 and 0.5 mm and reactor temperature between 450 and 600 °C). Response Surface Methodology (RSM) was used to optimize pyrolysis parameters. The results indicated that the temperature had the highest effect on phenolic and furfural-type compounds, whereas the particle size did not exhibit significant effects on carboxylic acid products. The largest number of phenolic compounds were achieved upon decreasing the temperature and increasing particle size. The ANOVA analysis revealed that the full quadratic model was more adequate for phenolic and furfural compounds, whereas the linear square model was accurate for carboxylic acids. In general, a tandem micro-pyrolyzer interfacing with a GC-MS analysis facilitated a better understanding of a chemical composition of biomass and therefore, could remarkably improve the valorising of sugarcane bagasse application in biorefinery processes.
Advanced Energy Technologies
Negin Maftouni; Minoo Askari
Abstract
Both energy and environmental criticisms push a society toward energy-efficient buildings with green technologies. Green roofs are of significant importance due to their remarkable role in decreasing the thermal loads ofbuildings, especially in summer, and also in sound insulation. Here in, the thermal ...
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Both energy and environmental criticisms push a society toward energy-efficient buildings with green technologies. Green roofs are of significant importance due to their remarkable role in decreasing the thermal loads ofbuildings, especially in summer, and also in sound insulation. Here in, the thermal loads of a residential building were calculated, and then, an optimized green roof was designed for it in three different cities of Tehran, Rasht, and Tabriz. The energy saving was analyzed in each case, and proper plants and roof thickness were selected to achieve both comfortable air conditioning and energy optimization. It is also important to use water resources in an optimized manner. Considering the annual mean rain magnitude, here, a suitable system is designed to harvest rainwater for watering the plants. Results indicate that a sedum grass-based green roof with the thickness of 10 cm leads to a 21.3 % reduction in the annual total thermal loads in Tehran; one with thickness of 8 cm in Tabriz will result in a 11.7 % thermal load reduction per year; a green roof with 9 cm thickness in Rasht, Iran shows 13.2 % energy saving per year. Therefore, Tehran is the best option here to integrate the green roof into the structure of the building. The patterns of the obtained data indicate that the reduction of cooling loads is more noticeable when implementing a green roof in comparison with heating loads. Moreover, it has been revealed that harvested rainwater is sufficient to support about 72 % of required water in Tehran, 81 % of it in Tabriz, and 93 % in Rasht.
