Renewable Energy Economics, Policies and Planning
Ali Mostafaeipour; Afsaneh Nasiri
Abstract
In hot and dry regions, air conditioning is used for many different applications like residential, industry, and agriculture and dairy products. This research studies the applicability of wind and solar energies for cooling fruit storage warehouse in the hot and dry region of Yazd in Iran. The studied ...
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In hot and dry regions, air conditioning is used for many different applications like residential, industry, and agriculture and dairy products. This research studies the applicability of wind and solar energies for cooling fruit storage warehouse in the hot and dry region of Yazd in Iran. The studied case is a fruit warehouse with an area of 4240 m2 resulting in a storage capacity of about 1000 tons. For this purpose, the heat gain of the warehouse is determined, and the obtained cooling load is then used to examine the solar and wind energy to power a conventional warehouse system. Different scenarios are examined for this research such as solar air conditioner, solar absorption chiller, wind catcher, and a combination of solar air conditioners and solar absorption chiller for cooling the fruit warehouse. Comparison and economic evaluation of different scenarios show that the solar air conditioning ranks first for this purpose. Results are then validated using value engineering methodology. Solar air conditioning with the highest net present value (NPV) of 4,865,040,418 Rials and the best internal rate of return (IRR) value of 182.98 % was determined to be the best approach among the studied methods. The results of this research can be applied to other regions with similar climatic conditions too.
Advanced Energy Technologies
Ali Mostafaeipour; Mojtaba Qolipour; Hossein Goudarzi; Mehdi Jahangiri; Amir-Mohammad Golmohammadi; Mostafa Rezaei; Alireza Goli; Ladan Sadeghikhorami; Ali Sadeghi Sedeh; Seyad Rashid Khalifeh Soltani
Abstract
Fuel cells are potential candidates for storing energy in many applications; however, their implementation is limited due to poor efficiency and high initial and operating costs. The purpose of this research is to find the most influential fuel cell parameters by applying the adaptive neuro-fuzzy inference ...
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Fuel cells are potential candidates for storing energy in many applications; however, their implementation is limited due to poor efficiency and high initial and operating costs. The purpose of this research is to find the most influential fuel cell parameters by applying the adaptive neuro-fuzzy inference system (ANFIS). The ANFIS method is implemented to select highly influential parameters for proton exchange membrane (PEM) element of fuel cells. Seven effective input parameters are considered including four parameters of semi-empirical coefficients, parametric coefficient, equivalent contact resistance, and adjustable parameter. Parameters with higher influence are then identified. An optimal combination of the influential parameters is presented and discussed. The ANFIS models used for predicting the most influential parameters in the performance of fuel cells were performed by the well-known statistical indicators of the root-mean-squared error (RMSE) and coefficient of determination (R2). Conventional error statistical indicators, RMSE, r, and R2, were calculated. Values of R2 were calculated as of 1.000, 0.9769, and 0.9652 for three different scenarios, respectively. R2 values showed that the ANFIS could be properly used for yield prediction in this study
Renewable Energy Resources and Technologies
Ali Mostafaeipour; Mohammad Saidi Mehrabad; Mojtaba Qolipour; Mohadese Basirati; Mostafa Rezaei; Amir Mohammad Golmohammadi
Abstract
The present study aimed at ranking and selecting the superior geothermal project for hydrogen production in 14 provinces of Iran using a multi-objective optimization fuzzy hybrid approach through analyzing the ratio (fuzzy Moora) and expanded entropy weighting method. In this research, the extended entropy ...
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The present study aimed at ranking and selecting the superior geothermal project for hydrogen production in 14 provinces of Iran using a multi-objective optimization fuzzy hybrid approach through analyzing the ratio (fuzzy Moora) and expanded entropy weighting method. In this research, the extended entropy weighing method and the Fuzzy-Moora approach were utilized to weigh the criteria and project the ranking, respectively. In this research, 13 criteria for ranking the geothermal projects in Iran have been selected for hydrogen production. At first, the technical-economic feasibility of the projects was carried out in Homer software, and then the ranking process was performed with the proposed hybrid approach. The results showed that among 14 studied provinces using geothermal energy, the provinces of Bushehr, Hormozgan, Isfahan, Mazandaran, East Azarbaijan, Fars, Qazvin, Zanjan, Ardebil, Khorasan Razavi, Kerman, Sistan and Baluchestan, South Khorasan and West Azarbaijan were ranked in that order in terms of hydrogen production.
Ali Mostafaeipour; Mohammad Saidi-Mehrabad; Mostafa Rezaei; Mojtaba Qolipour
Abstract
The energy insecurity, environmental pollution, climate change and even reduced rainfall in some countries are prime examples of consequences of the world’s excessive reliance on fossil fuels. This study suggests that in some southern islands and coastal areas of Iran, two such problems, ...
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The energy insecurity, environmental pollution, climate change and even reduced rainfall in some countries are prime examples of consequences of the world’s excessive reliance on fossil fuels. This study suggests that in some southern islands and coastal areas of Iran, two such problems, namely the growing shortage of potable water and air pollution can be addressed by building a wind-powered seawater desalination plant at the locations. To evaluate such project, first the sites that may provide the highest efficiency need to be identified. In this study, 10 ports and 5 islands in southern Iran, which suffer from water shortage but have access to seawater, are identified as preliminary candidate sites for such project. The criteria influencing the suitability of a location are considered to be wind power density, economic feasibility, topographic condition, frequency of natural disasters, population, and the wind farm’s distance from desalination facility. After analyzing and weighting the criteria, the locations are ranked using the ELECTRE III method, and the results are validated using the PROMETHEE method. In conclusion, the results of ranking techniques show that Qeshm Island is the best location for construction of a wind-powered seawater desalination plant.
