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Evaluation of wind energy potential in province of Bushehr, Iran

Journal

RENEWABLE & SUSTAINABLE ENERGY REVIEWS
Volume 55, Issue -, Pages 455-466

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2015.10.148

Keywords

Wind energy potential; Bushehr; Weibull distribution; Power density; Wind turbine analysis

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Renewable energy is receiving increasing interest from industry and government in Iran. Among the many types of renewable energy available in the country, wind energy is currently one of the fastest growing, most commonly used and commercially attractive renewable sources for generating electricity. In this paper, the wind energy potential is assessed for four locations in Bushehr province of Iran: Asaluyeh, Bordkhun, Delvar and Haft-Chah. The analysis utilizes wind speed data measured in 2011 at heights of 10 m, 30 m and 40 m above ground level. The goal is to improve understanding of the potential of wind energy for the selected locations and to thereby improve the prospects for its usage. The Weibull probability distribution function is employed to calculate the wind power density and energy for the regions. We found that the Weibull distribution fits the experimental data well over an acceptable range. The statistical analyses of the wind data include estimations of the monthly and diurnal mean wind speed cumulative curves, and the creation of wind rose diagrams. The results indicate that Bordkhun has better potential for using wind energy than the other three areas in the province examined. The annual mean wind power density for this location is found to be about 265 W/m(2) for winds at a height of 40 m. Energy analyses are used to determine the best wind turbines for each location. Twelve wind turbines with generating capacities ranging from 1 kW to 100 kW are examined, and the annual capacity factor and annual energy output of the selected wind turbines are calculated. A comparison of the results for the wind turbines indicates that the Proven 15 has the highest capacity factor and economically is the best choice for all of the locations considered. (C) 2015 Elsevier Ltd. All rights reserved.

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