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http://hdl.handle.net/10397/80283
Title: | Optimizing layout of wind farm turbines using genetic algorithms in Tehran province, Iran | Authors: | Khanali, M Ahmadzadegan, S Omid, M Nasab, FK Chau, KW |
Issue Date: | 2018 | Source: | International journal of energy and environmental engineering, Dec. 2018, v. 9, no. 4, p. 399-411 | Abstract: | Installation layout of wind turbines plays a prominent role in the design of every wind farm. Thus, the wind farm layout optimization problem is proposed to maximize the total power output with the minimum cost. In this research, Kahrizak region in Tehran province of Iran is selected as a windy region and its real wind speed data are gleaned. Three different scenarios are also considered, with various number of generations and populations for GA parameters, effective distances, and longitude and latitude distances of turbines from each other. Among these scenarios, the best result is obtained for the one in which the longitudinal distance between turbines is greater than the latitudinal distance. By observing the wind rose of Kahrizak region, it is observed that the dominant wind direction of the region is toward the east and south-east. Therefore, by increasing the longitudinal distance of the turbines from each other, the efficiency can be improved and the turbine layout becomes more realistic. In this case, the efficiency rate and normalized cost of turbines are 89.5% and 37.4, respectively, and also 56 turbines are needed. The amounts of efficiency and power output are very convenient for real wind speed data of a region. | Keywords: | Wind farm layout Optimization Genetic algorithm Kahrizak Turbine |
Publisher: | SpringerOpen | Journal: | International journal of energy and environmental engineering | ISSN: | 2008-9163 | DOI: | 10.1007/s40095-018-0280-x | Rights: | © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The following publication Khanali, M., Ahmadzadegan, S., Omid, M., Nasab, F.K., & Chau, K.W. (2018). Optimizing layout of wind farm turbines using genetic algorithms in Tehran province, Iran. International journal of energy and environmental engineering, 9 (4), 399-411 is available at https://dx.doi.org/10.1007/s40095-018-0280-x |
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