مکانیابی بهینه نیروگاه خورشیدی با استفاده از روش بهترین-بدترین، سوارا و سیستم اطلاعات مکانی (مطالعه موردی: استان فارس)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد سیستم‏های اطلاعات مکانی،گروه مهندسی نقشه‏برداری، دانشکدۀ مهندسی عمران، دانشگاه تربیت دبیر شهید رجایی، تهران، ایران

2 دانشیار گروه مهندسی نقشه‏برداری، دانشکدۀ مهندسی عمران، دانشگاه تربیت دبیر شهید رجایی، تهران، ایران

10.22059/ses.2024.380640.1085

چکیده

کشور ایران که به عنوان یکی از تولیدکنندگان بزرگ سوخت‏های فسیلی در جهان شناخته می‏شود و قسمت اعظم سبد انرژی‏اش سوخت‏های فسیلی است، در منطقۀ پرتابشی از کرۀ زمین قرار گرفته است که می‏تواند به منظور تولید انرژی خورشیدی از آن استفاده کند. اولین گام به منظور ایجاد نیروگاه‏های خورشیدی، مکان‌یابی علمی و عملیاتی محل احداث آن است. تحقیق حاضر با هدف مکان‌یابی نیروگاه خورشیدی در استان فارس، به ارائۀ یک رویکرد مبتنی‏ بر سیستم اطلاعات مکانی و تصمیم‏گیری چندمعیاره پرداخته است. در رویکرد ارائه‌شده، تهیۀ لایه‏های اطلاعاتی، تحلیل‏های فضایی و بصری‏سازی با استفاده از سیستم اطلاعات مکانی انجام شده است. همچنین، وزن‌دهی و تلفیق معیارها با استفاده از تصمیم‏گیری چندمعیاره صورت گرفته است. تحقیق حاضر به منظور وزن‌دهی معیارهای مکان‌یابی، دو روش بهترین‌ـ بدترین و سوارا که در تحقیقات پیشین کمتر مورد استفاده بوده‏اند، را با هم مقایسه کرده و همچنین از عملگرد میانگین هندسی به منظور تلفیق نتایج آن‌ها استفاده کرده است. براساس نتایج، معیارهای مکان‌یابی نیروگاه خورشیدی براساس اهمیت به‌ترتیب پتانسیل فتوولتائیک (241/0)، تابش نرمال مستقیم (156/0)، دما (120/0)، بارش (092/0)، فاصله از راه‏ها (089/0)، فاصله از مراکز شهری (085/0)، فاصله از گسل‏ها (066/0) و ارتفاع (054/0) بوده است. نقشه‏های تناسب اراضی تهیه‌شده نشان داد ‌بیش از 50 درصد مساحت استان فارس از تناسب زیاد و خیلی زیاد جهت احداث نیروگاه خورشیدی برخوردار بوده و مناطق شمالی، شمال شرقی و مرکزی مانند شهرستان‏های آباده، خرم بید، پاسارگاد و سرچهان باید در اولویت قرار گیرند.

کلیدواژه‌ها

عنوان مقاله [English]

Optimal Site Selection of Solar Power Plant Via Best-Worst Method, SWARA and Geospatial Information System (A Case Study: Fars Province)

نویسندگان [English]

  • Vahidreza Atabati 1
  • Mahdi Arabi 2
1 M.Sc. Student, Department of Geomatics Engineering, Faculty of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
2 Associate Professor, Department of Geomatics Engineering, Faculty of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
چکیده [English]

Iran recognized as one of the major fossil fuel producers in the world with a substantial portion of its energy basket reliant on fossil fuels, is situated in a region of the Earth with high solar radiation potential, making it suitable for solar energy production. The first step towards establishing solar power plants is the scientific and operational site selection for their construction. This study aims to identify suitable locations for solar power plants in Fars Province using a Geospatial Information System (GIS) and a multi-criteria decision-making approach. The proposed methodology involves the preparation of informational layers, spatial analyses, and visualizations using GIS. Additionally, criteria weighting and integration were performed using multi-criteria decision-making techniques. The study compares two methods for weighting the location criteria, Best-Worst Method (BWM) and Step-wise Weight Assessment Ratio Analysis (SWARA), which have been less utilized in previous research, and combines their results using geometric mean operator. According to the results, the criteria for solar power plant site selection, ranked by importance, are photovoltaic potential (0.241), direct normal irradiation (0.156), temperature (0.120), precipitation (0.092), distance from roads (0.089), distance from urban centers (0.085), distance from faults (0.066), and elevation (0.054). The land suitability maps indicate that over 50% of the area in Fars Province is highly or very highly suitable for the construction of solar power plants, with the northern, northeastern, and central regions, including the counties of Abadeh, Khorrambid, Pasargad, and Sarchehan, being prioritized.

کلیدواژه‌ها [English]

  • Best-Worst Method(BWM)
  • Geospatial Information System(GIS)
  • Multi-Criteria Decision-Making(MCDM)
  • Solar Power Plant Site Selection
  • Step-wise Weight Assessment Ratio Analysis(SWARA)

مراجع

[1] Mamouri SJ, Derami HG, Ghiasi M, Shafii MB, Shiee Z. Experimental investigation of the effect of using thermosyphon heat pipes and vacuum glass on the performance of solar still. Energy. 2014;75:501-7.
[2] Alamdari P, Nematollahi O, Alemrajabi AA. Solar energy potentials in Iran: A review. Renewable and Sustainable Energy Reviews. 2013;21:778-88.
[3] Moghaddam NB, Mousavi SM, Nasiri M, Moallemi EA, Yousefdehi H. Wind energy status of Iran: Evaluating Iran's technological capability in manufacturing wind turbines. Renewable and Sustainable Energy Reviews. 2011;15(8):4200-11.
[4] Firozjaei MK, Nematollahi O, Mijani N, Shorabeh SN, Firozjaei HK, Toomanian A. An integrated GIS-based Ordered Weighted Averaging analysis for solar energy evaluation in Iran: Current conditions and future planning. Renewable Energy. 2019;136:1130-46.
[5] Bhattacharya M, Churchill SA, Paramati SR. The dynamic impact of renewable energy and institutions on economic output and CO2 emissions across regions. Renewable Energy. 2017;111:157-67.
[6] Owusu PA, Asumadu-Sarkodie S. A review of renewable energy sources, sustainability issues and climate change mitigation. Cogent Engineering. 2016;3(1):1167990.
[7] Creutzig F, Goldschmidt JC, Lehmann P, Schmid E, von Blücher F, Breyer C, Fernandez B, Jakob M, Knopf B, Lohrey S, Susca T. Catching two European birds with one renewable stone: Mitigating climate change and Eurozone crisis by an energy transition. Renewable and Sustainable Energy Reviews. 2014;38:1015-28.
[8] Al Garni HZ, Awasthi A. Solar PV power plants site selection: A review. Advances in renewable energies and power technologies. 2018:57-75.
 [9] Ghasempour R, Nazari MA, Ebrahimi M, Ahmadi MH, Hadiyanto H. Multi-Criteria Decision Making (MCDM) Approach for Selecting Solar Plants Site and Technology: A Review. International Journal of Renewable Energy Development. 2019;8(1).
[10] Sengupta M, Habte A, Wilbert S, Gueymard C, Remund J. Best practices handbook for the collection and use of solar resource data for solar energy applications. National Renewable Energy Lab. (NREL), Golden, CO (United States); 2021.
[11] Dweiri F, Khan SA, Almulla A. A multi-criteria decision support system to rank sustainable desalination plant location criteria. Desalination. 2018;444:26-34.
[12] Hooshangi N, Gharakhanlou NM, Razin SR. Evaluation of potential sites in Iran to localize solar farms using a GIS-based Fermatean Fuzzy TOPSIS. Journal of Cleaner Production. 2023;384:135481.
[13] Zandi I, Pahlavani P, Bigdeli B, Lotfata A, Alesheikh AA, Garau C. GIS-Enabled Multi-Criteria Assessment for Hospital Site Suitability: A Case Study of Tehran. Sustainability. 2024;16(5):2079.
[14] Hasti F, Mamkhezri J, McFerrin R, Pezhooli N. Optimal solar photovoltaic site selection using geographic information system–based modeling techniques and assessing environmental and economic impacts: The case of Kurdistan. Solar Energy. 2023;262:111807.
[15] Hassan I, Alhamrouni I, Azhan NH. A CRITIC–TOPSIS multi-criteria decision-making approach for optimum site selection for solar PV farm. Energies. 2023;16(10):4245.
[16] Settou B, Settou N, Gouareh A, Negrou B, Mokhtara C, Messaoudi D. A high-resolution geographic information system-analytical hierarchy process-based method for solar PV power plant site selection: a case study Algeria. Clean Technologies and Environmental Policy. 2021;23:219-34.
[17] Agyekum EB, Amjad F, Shah L, Velkin VI. Optimizing photovoltaic power plant site selection using analytical hierarchy process and density-based clustering–Policy implications for transmission network expansion, Ghana. Sustainable Energy Technologies and Assessments. 2021;47:101521.
[18] Karimipour H, Alesheikh AA. Location of Solar Power Plants by Combining the Best-worst Methods, Danp, Copras and TOPSIS Case Study of Fars Province. Journal of Geomatics Science and Technology. 2021;10(3):183-99, [Persian].
[19] Samani NN, Tahouni A. The Evaluation of suitable Sites for Solar Farms by Multi Criteria Decision Making in GIS (Case Study: East Azarbaijan Province). Human Geography Research. 2019;51(3):747-64, [Persian].
[20] Asakereh A, Soleymani M, Sheikhdavoodi MJ. A GIS-based Fuzzy-AHP method for the evaluation of solar farms locations: Case study in Khuzestan province, Iran. Solar Energy. 2017;155:342-53.
[21] Ayough A, Boshruei S, Khorshidvand B. A new interactive method based on multi-criteria preference degree functions for solar power plant site selection. Renewable Energy. 2022;195:1165-73.
[22] Khanlari A, Alhuyi Nazari M. A review on the applications of multi-criteria decision-making approaches for power plant site selection. Journal of Thermal Analysis and Calorimetry. 2021 May:1-7.
[23] Zandi I, Pahlavani P, Bigdeli B. Land Suitability Assessment for Construction of a Hospital: An Integrated Modeling Approach based on MCDM and GIS (A Case Study: The Second District of Tehran). Geography and Environmental Planning. 2023;34(4):69-88, [Persian].
[24] Zandi I, Pahlavani P, Bigdeli B. Preparation of Flood Susceptibility Map using Multi-Criteria Spatial Analysis and Data Fusion (A Case Study: Maneh and Samalqan County). Journal of Geomatics Science and Technology. 2023;12(4):53-76, [Persian].
[25] Dehshiri SS. New hybrid multi criteria decision making method for offshore windfarm site location in Persian Gulf, Iran. Ocean Engineering. 2022;256:111498.
[26] Rezaei J. Best-worst multi-criteria decision-making method. Omega. 2015;53:49-57.
[27] Thakkar JJ, Thakkar JJ. Stepwise weight assessment ratio analysis (SWARA). Multi-Criteria Decision Making. 2021:281-9.
[28] Agricultural Organization of Fars (2020). Fars Province Atlas of Weather and Climatology. Modern Agricultural Technology, Great Iran Publication, Shiraz, Iran, [Persian].
[29] Noorollahi E, Fadai D, Akbarpour Shirazi M, Ghodsipour SH. Land suitability analysis for solar farms exploitation using GIS and fuzzy analytic hierarchy process (FAHP)—a case study of Iran. Energies. 2016;9(8):643.
[30] Mi X, Tang M, Liao H, Shen W, Lev B. The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?. Omega. 2019;87:205-25.
[31] Safarzadeh S, Khansefid S, Rasti-Barzoki M. A group multi-criteria decision-making based on best-worst method. Computers & Industrial Engineering. 2018;126:111-21.
[32] Keršuliene V, Zavadskas EK, Turskis Z. Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of business economics and management. 2010;11(2):243-58.
[33] Chang KH. Integrating subjective–objective weights consideration and a combined compromise solution method for handling supplier selection issues. Systems. 2023;11(2):74.
[34] Şimşek K, Alp S. Evaluation of landfill site selection by combining fuzzy tools in GIS-based multi-criteria decision analysis: a case study in Diyarbakır, Turkey. Sustainability. 2022;14(16):9810.
[35] Zavadskas EK, Čereška A, Matijošius J, Rimkus A, Bausys R. Internal combustion engine analysis of energy ecological parameters by neutrosophic MULTIMOORA and SWARA methods. Energies. 2019;12(8):1415.
[36] Ayyildiz E, Yildiz A, Taskin Gumus A, Ozkan C. An integrated methodology using extended swara and dea for the performance analysis of wastewater treatment plants: Turkey case. Environmental Management. 2021;67(3):449-67.
[37] Zolfani SH, Esfahani MH, Bitarafan M, Zavadskas EK, Arefi SL. Developing a new hybrid MCDM method for selection of the optimal alternative of mechanical longitudinal ventilation of tunnel pollutants during automobile accidents. Transport. 2013;28(1):89-96.
[38] Najafi G, Ghobadian B, Mamat R, Yusaf T, Azmi WH. Solar energy in Iran: Current state and outlook. Renewable and Sustainable Energy Reviews. 2015;49:931-42.
[39] Gorjian S, Ghobadian B. Solar thermal power plants: progress and prospects in Iran. Energy Procedia. 2015;75:533-9.
[40] Zandi, I, Pahlavani P, Bigdeli B. Different Multi-Criteria Strategies in Hospital Location Ranking using Dempster–Shafer Decision-Level Fusion and Quantifier-guided OWA, A Case Study. Earth Observation and Geomatics Engineering. 2022;6(2):10-27.
[41] Maserrat Z, Alesheikh AA, Jafari A, Charandabi NK, Shahidinejad J. A Dempster–Shafer Enhanced Framework for Urban Road Planning Using a Model-Based Digital Twin and MCDM Techniques. ISPRS International Journal of Geo-Information. 2024;13(9):302.
[42] Więckowski J, Wątróbski J, Sałabun W. Inaccuracies in expert judgment: Comparative analysis of RANCOM and AHP methods in housing location selection problem. IEEE Access. 2024
فصلنامه سیستم های انرژی پایدار
دوره 3، شماره 2
فروردین 1403
صفحه 209-227

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