فهرست مطالب

Journal of Renewable Energy and Environment
Volume:3 Issue: 3, Summer 2016

  • تاریخ انتشار: 1395/11/11
  • تعداد عناوین: 7
|
  • H. Ghaderi, M. Asadi, S. Shavalpour Pages 1-10
    Switchgrass is known as one of the best second generation lignocellulosic feedstock for bioethanol production. Designing an efficient switchgrass-based bioethanol supply chain (SBSC) is an essential requirement for commercialization of bioethanol production. This paper presents a mixed integer linear programming (MILP) model to design SBSC in which the bioethanol demand is under ARMA time series models. It is studied how ARMA time series structure of bioethanol demand affect the supply chain design. A case study based on North Dakota state in the United States demonstrates application of the proposed model to design the most optimal SBSC.in addition, to provide insights for efficiently designing the SBSC, the ARMA models of bioethanol demand is used to forecast SBSC design for the period 2013 to 2020.
    Keywords: ARMA, switchgrass, bioethanol supply chain, network design, mixed integer programming
  • G. Shahgolian Pages 11-20
    The hydro turbine dynamics have a considerable influence on the dynamic stability of the power system. This paper provides an analysis of the small signal stability in a of hydropower plant equipped with low head Kaplan turbine connected as single-machine infinite-bus (SMIB) power system under different system conditions and operating loads. The dynamical behaviors of the points with representative characteristics are identified and studied in detail. The model of the system is described by state-space equations. The eigenvalues analysis are used to show the effects of change in parameters for damping the load angle and speed oscillations through the excitation and governor subsystems.
    Keywords: Hydro power system, small signal stability, eigenvalues analysis, oscillation
  • H. Ghasemi Mobtaker, Y. Ajabshirchi, S. F. Ranjbar, M. Matloobi, M. Taki Pages 21-30
    Precise knowledge of the amount of global solar radiation plays an important role in designing of a renewable energy systems. In this study, using long-term meteorological data, 19 empirical models were tested for prediction of monthly mean daily global solar radiation in Tabriz. Also various artificial neural networks (ANN) models were designed for the comparison with the empirical models. For this purpose, the meteorological data recorded by Iran Meteorological Office (1992–2013) was used. These data included: monthly mean daily sunshine duration, monthly mean ambient temperature, monthly mean maximum and minimum ambient temperature and monthly mean relative humidity. The results showed that the yearly average of solar radiation in the region was 16.37 MJ m-2 day-1. Among the empirical models, the best result was acquired for model (19) with correlation coefficient of 0.9663. Results also showed that the ANN model trained with total meteorological data in input layer produces better results than the others. RMSE and r for this model were 1.0800 MJ m-2 and 0.9714, respectively. Comparison between the two models demonstrated that modeling of monthly mean daily global solar radiation through the use of the ANN technique shows better estimates rather than the empirical models.
    Keywords: Solar energy, Meteorological data, Sunshine hour, Prediction, Artificial neural networks
  • M. Jamali, F. Ommi Pages 31-43
    In this paper, a solar based hydrogen production in the city of Tehran, the capital of Iran is simulated and the cost of produced hydrogen is evaluated. Local solar power profile is obtained using TRNSYS software for a typical parking station in Tehran. The generated electricity is used to supply power to a Proton Exchange Membrane (PEM) electrolyzer for hydrogen production. Dynamic nature of solar power and necessity of reasonable accuracy for estimating of amount of hydrogen production leads to propose a new 1D dynamic fluid flow model for PEM electrolyzer cell simulation. The hydrogen price in this system is estimated using Equivalent Annual Worth (EAW) analysis. Although it is convenient to select a yearly useful lifetime for electrolyzer as well as solar cells in this paper an hourly lifetime is considered which allows finding the hydrogen cost based on electrolyzer operating time. Also, electrolyzer sizing is done by selecting various number of cells for each stack and alternatives are compared from performance and economic point of view. In this regards 4 cases consist of 2, 3, 4 and 5 electrolyzer cell are compared. Hydrogen price at each case is evaluated and sensitivity analysis is performed. The results represent that the system with higher efficiency is not always an economical choice. As an alternative, the electrolyzer turning off at some conditions is also investigated for possibility of extending lifetime and reducing the hydrogen price. It is found that turning off the electrolyzer under specified minimum current density (2000 A/m2) in all cases reduce the final produced hydrogen price however this price and electrolyzer size is still strongly dependent to the electrolyzer capital cost.
    Keywords: Electrolysis, PEM, Dynamic modeling, Hydrogen production
  • M. Ahmadzadehtalatapeh Pages 44-52
    Air pre-cooling equipment is normally being employed in air-conditioning systems for pre-cooling the ambient outdoor air to enhance the air-conditioning systems performance. In this study, the potential of a passive water-to-air heat pipe based heat exchanger (HPHEX) for air pre-cooling purpose in air-conditioning systems for the high cooling load demanding regions of Iran was investigated. To this end, effectiveness-NTU approach was employed to determine the thermal performance of the heat exchanger. Water-to-air HPHEX with different numbers of rows namely two, four, and six was studied to determine the heat transfer characteristics of the heat exchanger. The thermal performance of the water-to-air HPHEX was investigated under different operating conditions in terms of evaporator inlet air and condenser inlet water coil face velocities and temperatures. After determining the thermal performance of the water-to-air HPHEX, the air pre-cooling capability of the water-to-air HPHEX was explored hour-by-hour for the required months of the year by using TRNSYS software. Based on the simulations results, the water-to-air HPHEX shows an acceptable thermal performance under the operating conditions. In addition, studies showed that the water-to-air HPHEX has a significant capability for air pre-cooling, which makes it applicable to be implemented in the air-conditioning systems operating in south of Iran.
    Keywords: Effectiveness-NTU, heat pipe based heat exchanger, air pre-cooling, thermal performance
  • Imologie M. Simeon, R. Abdulganiy, A. Gbabo, C. Okoro Shekwaga Pages 53-58
    Soil is beginning to attract research attention as suitable inoculums for Microbial Fuel Cells (MFCs) designed for remediation and for electricity generation probably due to its high microbial load. However, not much has been done in this aspect beyond laboratory based experiment. This study was aimed at generating electricity from agricultural soil, utilizing the microorganisms present in the soil, and investigating the performance of the soil MFC across varied external loads. The study used the mud watt MFC kit inoculated with mud prepared from topsoil collected from a garden. The electrodes, made from carbon felt material with conducting wires made from graphite, were housed in the same chamber and placed 4cm apart. Voltage drop across seven external resistances of 4670, 2190, 1000, 470, 220, 100, and 47 Ω were measured every 24 hours, with a digital multi-meter, for 40 days. The maximum open circuit voltage from this study was 731 mV, whereas the maximum power density was 65.40 m/Wm2 at a current density of 190.1mA/m2. The optimum performance of the MFC was achieved with the 470Ω at an internal resistance of 484.14 Ω. This study revealed that MFCs constructed from agricultural topsoil are capable of producing electrical power continuously, across different external loads, without addition of any substrate. However, there is need for further studies to keep the MFC output constant at the maximum achievable power.
    Keywords: Microorganisms, metabolism, performance, soil, resistance, electricity
  • H. Bagheri Tolabi, R. Hosseini Pages 59-66
    In this paper, a novel approach for the estimation of global solar irradiance is proposed based on a combination of empirical correlation and ant colony optimization. Empirical correlation has been used to estimate monthly average of daily global solar irradiance on a horizontal surface. The Ant Colony Optimization (ACO) algorithm has been applied as a swarm-intelligence technique to tune the coefficients of linear and nonlinear empirical models. . The performance of the models is investigated for the estimation of global solar irradiance at four different climatic regions of Iran based on statistical indicators like coefficient of determination (R2) and root mean square error (RMSE). The results obtained from the proposed model are superior in comparison with the other well established models.
    Keywords: Ant Colony Optimization (ACO), Empirical models, Global solar irradiance, Intelligent models