مکانیابی صفحه‌های خورشیدی با استفاده از فراسنج های اقلیمی و سامانه اطلاعات جغرافیایی (مطالعه موردی: استان خوزستان)
محورهای موضوعی :
انرژی های تجدید پذیر
مختار کرمی
1
,
رسول سروستان
2
1 - استادیار آب و هواشناسی، دانشکده جغرافیا و علوم محیطی، دانشگاه حکیم سبزواری، سبزوار، ایران.
2 - دکترای در رشته آب و هواشناسی شهری، دانشکده جغرافیا و علوم محیطی، دانشگاه حکیم سبزواری، سبزوار، ایران. *(مسوول مکاتبات)
تاریخ دریافت : 1396/03/09
تاریخ پذیرش : 1396/09/22
تاریخ انتشار : 1401/02/01
کلید واژه:
مکانیابی,
تاپسیس فازی,
GIS,
صفحه‌های خورشیدی,
خوزستان,
چکیده مقاله :
زمینه و هدف: در این پژوهش تلاش شده تا مکانیابی صفحه‌های خورشیدی با استفاده از فراسنج های اقلیمی و سامانه اطلاعات جغرافیایی در گستره استان خوزستان مورد بررسی قرار گیرید.
روش بررسی: در ابتدا داده‌های اقلیمی (مجموع بارندگی سالانه، میانگین دما سالانه، تعداد ساعات آفتابی و تعداد روزهای گردوغباری) مربوط به 21 ایستگاه هواشناسی و لایه‌های ارتفاع، شیب، جهت شیب، گسل، رودخانه، کاربری اراضی و جاده به عنوان مهم‌ترین عوامل اقلیمی، توپوگرافی، محیط زیستی و محیط انسانی مؤثر بر میزان صفحه‌های خورشیدی در GIS با استفاده از روش IDW تولید شدند، سپس با توجه به مدل FTOPSIS وزن بندی شده و این لایه‌ها از طریق روش همپوشانی با هم تلفیق شده و لایه‌های پهنه‌ای جهت استقرار صفحه‌های خورشیدی در استان تهیه گردید.
یافته‌ها: پس از ایجاد لایه‌های پهنه‌ای، آن‌ها را در محیط GIS درنهایت با تلفیق لایه‌های اطلاعاتی مختلف و تعیین وزن هر لایه اطلاعاتی، کلاس‌بندی نقشه مکانیابی صفحه‌های خورشیدی در 5 کلاسه بسیار مطلوب با (020/2-050/3)، در محدوده مطلوب (054/1-010/2)، متوسط (220/1-530/1)، در محدوده نامطلوب (941-210/1) و بسیار نامطلوب (512-940) طبقه‌بندی شدند.
بحث و نتیجه‌گیری: این پژوهش نشان داد که؛ با تلفیق لایه‌های اطلاعاتی مختلف و اعمال محدودیت‌ها و پتانسیل‌ها، پهنه‌هایی محدوده شرقی شامل شهرهای دهدز و ایذه دارای بالاترین درجه از مطلوبیت احداث صفحه‌های خورشیدی هستند. نتایج همچنین نشان داد که سیستم اطلاعات جغرافیایی به عنوان یک سیستم پشتیبانی تصمیم‌گیری و فرآیند تحلیل تاپسیس فازی FTOPSIS)) مدل انعطاف پذیری در مدل‌سازی داده‌های مکانی در انتخاب مکان مناسب صفحه‌های خورشیدی می‌باشد.
چکیده انگلیسی:
Background and Objective: In this research, it is tried to find the location of solar panels using climate and geographic information systems in the province of Khuzestan.
Material and Methodology: At first, climatic data (total annual precipitation, annual average, sunshine and number of days of dust) related to 21 meteorological stations and elevation, slope, tilt, fault, fault, land use and road layers as the most important climatic factors, Topography, environment and human environment, which were influenced by the amount of solar panels in GIS, were generated using the IDW method, then weighed according to the FTOPSIS model, and these layers were combined through the overlapping method and the layer layers To establish solar panels in the province was provided.
Findings: After creating the layered layers, they were finally placed in the GIS environment by combining different layers of information and determining the weight of each information layer. The classification of the map of the solar panels in 5 highly desirable categories with (2.020-3.020- 3.050), in the desirable range (1.540-2.090), moderate (1.220-1.530), in the unfavorable range (941-1.210) and very unfavorable (512-940).
Discussion and Conclusion: The study showed that, by combining different information layers and applying limitations and potentials, the eastern boundary zones including the cities of Dahdz and Izeh have the highest degree of utility in the construction of solar panels. The results also showed that the GIS as a decision support system and fuzzy overhead analysis process (FTOPSIS) is a flexible model for locating data in the selection of suitable solar panels.
منابع و مأخذ:
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Zohoori M., 2012. Exploiting Renewable Energy Sources in Iran. Interdisciplinary J. of Contemporary Research in Business,4, pp:849-862.
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Gurdo, M,. 2009. Understanding organizational trust-foundations, constellations, and issues of Journal of Managerial psychology 19(6), pp:557.
Yun, W,. sheng, F,. Tian, K,. Lina, L,. Wei, F,. Macrosite selection of wind/solar hybrid power station based on Ideal Matter-Element Model. International Journal of Electrical Power & Energy Systems, 50, pp: 76-84.
Heydari, M., 2001. Location of construction of solar power plants, in Iran, oil and energy, pp:38-49. (In Persian)
Esfandiari, A., 2011. Potential Assessment of Solar Power Plant Construction by Studying Climatic Parameters in Khuzestan Province Using GIS, National Geomatics Conference, Tehran. (In Persain)
A.A. 2007. A simple formula for estimating global solar radiation in central ariddeserts of Iran. Renewable Energy, 48: 116-125. (In Persain)
Paltridge, G.W. and Proctor, D. 1976. Monthly mean solar radiation statistics for Australia. J. Solar Energy, 18: 235-43.
Yousefi, H., Divine light, y., Sultan Mohammadi, M., Arjmandi R., 2013. Application of Fuzzy Logic and FTOPSIS for Location of Solar Power Plant Using GIS (Case Study of Tehran Province), Iranian Journal of Energy, 15 (4). (In Persain)
Taghvai, M. And Saboohi, A., 2017. Zoning and location of solar power plants in Isfahan province, Journal of Urban Research and Planning, 28, pp:82-61. (In Persian)
Statistical yearbook of Khuzestan province 2016
Sun, Chia Chi and Lin. Grace T.L, 2008, Application of Fuzzy TOPSIS forEstimating the Industrial Cluster Policy, Institute of Management ofTechnology, National Chiao Tung University, Taiwan.
Salimi, M., Hosseini, M., Shabani Bahar, G., Location of sports venues using continuous and discrete spatial models based on the combination of two models AHP and TOPSIS, Sports Management Studies, 13. (In Persain)
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Daneshyar, M. 1978. Solar radiation statistics for Iran. Solar Energy, 21 pp: 345-349.
Hove, T., Manyumbu, E., and Rukweza, G., 2014. Developing an improved global solar radiation map for Zimbabwe through correlating long-term ground- and satellite-based monthly clearness index values, Renewable Energy, Vol.63, PP: 687-697.
Sabbagh, J. Aayugh, A., and El Salam, E., 1971. Estimation of the total solar radiation from meteorological data. J. Solar Energy, 19, pp:349-357.
Asadi, M. and Karami, M. (2017) Locating of Wind Power Farms by Analytic Hierarchy Process Method (Case Study: Sistan and Baluchistan Province, Iran). Computational Water, Energy, and Environmental Engineering, 6, 41-55.
Sánchez, M., Teruel, J., Soto, P., and Socorro G, 2013. Geographical Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms locations: Case study in south-eastern Spain, Renewable and Sustainable Energy Reviews, Vol.24, PP: 544-556.
Zohoori M., 2012. Exploiting Renewable Energy Sources in Iran. Interdisciplinary J. of Contemporary Research in Business,4, pp:849-862.
Bahrami, M., and P, Abbaszadeh,. 2013. An overview of renewable energies in Renewable and Sustainable Energy Reviews, 24, pp: 198-208.
Yang, K,. and Toshio, K,. 2005. A general model to estimate hourly and daily solar radiation for hydrological studies, Water Resources Research, 41. W10403, doi: 10.1029/2005WR003976
Gurdo, M,. 2009. Understanding organizational trust-foundations, constellations, and issues of Journal of Managerial psychology 19(6), pp:557.
Yun, W,. sheng, F,. Tian, K,. Lina, L,. Wei, F,. Macrosite selection of wind/solar hybrid power station based on Ideal Matter-Element Model. International Journal of Electrical Power & Energy Systems, 50, pp: 76-84.
Heydari, M., 2001. Location of construction of solar power plants, in Iran, oil and energy, pp:38-49. (In Persian)
Esfandiari, A., 2011. Potential Assessment of Solar Power Plant Construction by Studying Climatic Parameters in Khuzestan Province Using GIS, National Geomatics Conference, Tehran. (In Persain)
A.A. 2007. A simple formula for estimating global solar radiation in central ariddeserts of Iran. Renewable Energy, 48: 116-125. (In Persain)
Paltridge, G.W. and Proctor, D. 1976. Monthly mean solar radiation statistics for Australia. J. Solar Energy, 18: 235-43.
Yousefi, H., Divine light, y., Sultan Mohammadi, M., Arjmandi R., 2013. Application of Fuzzy Logic and FTOPSIS for Location of Solar Power Plant Using GIS (Case Study of Tehran Province), Iranian Journal of Energy, 15 (4). (In Persain)
Taghvai, M. And Saboohi, A., 2017. Zoning and location of solar power plants in Isfahan province, Journal of Urban Research and Planning, 28, pp:82-61. (In Persian)
Statistical yearbook of Khuzestan province 2016
Sun, Chia Chi and Lin. Grace T.L, 2008, Application of Fuzzy TOPSIS forEstimating the Industrial Cluster Policy, Institute of Management ofTechnology, National Chiao Tung University, Taiwan.
Salimi, M., Hosseini, M., Shabani Bahar, G., Location of sports venues using continuous and discrete spatial models based on the combination of two models AHP and TOPSIS, Sports Management Studies, 13. (In Persain)
