Journal of Renewable Energy and Environment
Volume:2 Issue: 1, Winter 2015

The use of renewable energy sources is often suggested to be a good solution for climate change and the dependency to fossil fuel. Biogas utilization is a one of these promising options that can mitigate these problems since biogas is produced by the fermentation of waste, so is rich in methane and has the same characteristics as natural gas. Biogas has increasingly been noticed in different countries during last decades, but Iran could not reach its deserved position in comparison with others. The authors believe that absence of a proper management and information system is the main reason for this problem. In this article a decision system is designed in order to reduce the involved risks in making decision and helping in selecting the most appropriate commercialization strategies for utilization of biogas which is achievable from Iran’s livestock and poultry wastes. After a short hint to biogas and its techniques, in this article the main related criteria including biogas site selection and production techniques and utilization options in Iran have been chosen and their weights were calculated according to analytical hierarchy process (AHP). The weight obtained in this research should be considered in future development of Biogas by considering local specifications.

In this study, the convective heat transfer and pressure drop in laminar flow of Al2O3/water and CuO/water nanofluids through square and triangular cross-sectional ducts have been numerically investigated using new technique. It has been assumed that there is constant heat flux boundary condition at walls. In addition, to include the presence of nanoparticles, the dispersion model has been used, and the system was solved numerically. Results show that by increasing the volumetric concentration and decreasing the size of nanoparticles, Nusselt number has been enhanced. Also, the Nusselt number increases by increasing the Reynolds number. In all cases, it has been observed that heat transfer coefficient of nanofluid increases in comparison with heat transfer coefficient of pure water. The results show that by adding nanoparticles, pressure drop increases in ducts. In square and triangular ducts, pressure drop is higher when we use CuO/water nanofluid instead of Al2O3/water nanofluid. In the same way, pressure drop increases by increase of faces of non-circular ducts.

In this research, 11 yeast strains with ability to grow on petroleum sludge were isolated from effluent of a petroleum refinery. Based on growth on mineral media contaminated petroleum sludge, two isolates were selected as the super strains. Meanwhile, results based on biochemical and morphological experiments on the strains indicated that the two selected isolates belonged to Candida and Prototheca genus. Optimization with Taguchi Statistical Method (TSM) indicated that appropriate conditions for both isolates considering sludge concentrations, nitrogen source, pH, temperature and shaking rate (rpm) are equal to 10%, 2 g/l sodium nitrate, 6.5, 25°C and 190 rpm, respectively. Biomass production in optimal growing conditions for Candida and Prototheca were 1.54 g/l and 2.3 g/l, respectively. Gas Chromatography analyses of extracted fatty acids from supernatants and surface portions after methyl-esterifies with methanol: KOH solvents, indicated that content quantity of fatty acids on the surface was more than other portions and mainly in the forms of 16 and 18 saturated carbons and in the forms of palmitic acid and stearic acid. Therefore, these isolates can be used for recycling of petroleum sludge in production of yeast biomass and cell oil.

a new intelligent photovoltaic (PV) panel structure to extract the maximum power in mismatch irradiance is proposed. In conventional structures, difference of irradiance between series panels can cause the deviation of maximum power point. In this condition tracking MPP becomes difficult and reduces efficiency. Improvements in power electronics and its effects in PV industrial technology, developed many new PV structure in recent years. This paper proposes a new intelligent structure with module integrated converter for increasing energy capture in the PV series string. The advantage of new structure is that the MPP region extends from single panel MPP to a much wider range, causing the panels to operate independent of each other in mismatch condition. To study and show advantage of intelligent structure, a real simple model is selected and verified. For operating in MPP region, P&O algorithm is selected. Despite conventional structures, voltage is not appropriately varied for P&O algorithm used in intelligent structure and system experiences instability. To solve this instability problem, resistance is proposed as variable.MATLAB/Simulink is used for simulation and demonstration of expression. The results of this work have shown that using intelligent structure improves the energy harvesting up to 14 percent, and resistance is the best variable in tracking speed and accuracy.

The effect of storage time on some properties of groundnut shell briquette with 5, 10, 15 and 20% binder (cassava gel) was studied. The briquettes were prepared using a motorized briquetting machine. The moisture content, durability rating, water penetration, calorific value and the ash content were determined after every 30 days for 6 months. The results reveals that the moisture content of briquettes decreases during storage during the hot season, the result also reveals a decrease in the durability rating. However, there is an increase in the water penetration with storage time. There is also an increase in the ash content with storage, and this is believed to be responsible for the decrease in the calorific value of the briquettes with storage. However, briquettes with 15 and 20% binder remained relatively stable after 6 months of storage.

In this study, an artificial neural network based model for prediction of solar energy potential in Kerman province in Iran has been developed. Meteorological data of 12 cities for period of 17 years (1997–2013) and solar radiation for five cities around and inside Kerman province from the Iranian Meteorological Office data center were used for the training and testing the network. Meteorological and geographical data were used as inputs to the network, while the solar radiation intensity was used as the output of the network. The results show that the correlation coefficients between the predictions and actual global solar radiation intensities for training and testing datasets were higher than 97%, suggesting a high reliability of the model for evaluating solar radiation in locations where solar radiation data are not available. The predicted solar radiation values are illustrated in the form of maps that were made by ArcGIS.

Sediment microbial fuel cells (SMFCs) are a promising technology for a viable source of energy. This technology is faced with many challenges, such as limited mass transfer and low electricity generation. The aim of this research was to investigate the effect of electrolyte conductivity and aeration effect on power generation from SMFCs. Electrical conductivity was adjusted at 6different levels by adding several concentrations of NaCl and KCl, which are abundant and economic salts. By adding NaCl, the performance of SMFCs improved about 3.25 fold. Maximum generated power and current density of 32.76 mW/m2 and 330.14 mA/m2are obtained,respectively afterNaCl addition. Also, with aeration dissolved oxygen level increased as an electron acceptor in cathode portion, thereby power density enhanced from 16.36 mW/m2 to 38.31 mW/m2which was a 234% increase compared to the situation before aeration.