کلیدواژهها
|
Data Envelopment Analysis (DEA), Andersen-Petersen (AP), Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS), Analytical Hierarchy Process (AHP),
|
چکیده
|
© IEOM Society International
Using MCDM approaches to rank different locations for harnessing wind energy to produce hydrogen
Mostafa Rezaei
Industrial Engineering Department
Yazd University
Yazd, Iran
mm.sr6870@yahoo.com
Mojtaba Qolipour
Industrial Engineering Department
Yazd University
Yazd, Iran
qolipourmojtaba@yahoo.com
Amir-Mohammad Golmohammadi
Industrial Engineering Department
Yazd University
amir88.golmohamadi@yahoo.com
Hengameh Hadian
Department of Industrial Engineering
University of Nahavand
Nahavand, Iran
hengameh.hadian@gmail.com
Abstract
Utilizing wind turbines to produce electricity has been increasing in recent years, due to technology advancement, global warming and environmental pollution. Identification of the most suitable place for harnessing wind energy is enormously important, so effective criteria must be considered. This study is aimed to prioritize different cities of Fars province for establishment wind farm facilities. In order to this purpose six major criteria including wind power density, topographic situation, distance to distribution net, population, land cost and natural disasters were investigated. Wind power as the foremost criterion, that a candidate site must have, is the high degree of continues and persistent windiness. The Weibull distribution function has been applied to estimate the wind power density by using 3-h wind speed and other meteorological data. The function’s results indicated that Izadkhast has the most value of wind power with amount of 166.64 W/m2. Data Envelopment Analysis (DEA) and Andersen-Petersen (AP) were used to rank the under study areas. FTOPSIS and AHP were applied for validating calculated results. Finally it is suggested that Izadkhast is the best city for wind-hydrogen conversion constructions. About 21.9 ton hydrogen will be produced per year by using a 900 kW wind turbine in the city.
|