ارائۀ چارچوبی جامع برای مکان‏یابی مزارع هیبریدی بادی‌ـ فتوولتائیک (مطالعۀ موردی: استان خراسان جنوبی)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد، گروه مهندسی سیستم‏های انرژی پایدار، دانشکدۀ مهندسی انرژی و منابع پایدار، دانشگاه تهران، تهران، ایران

2 استاد، گروه مهندسی سیستم‏های انرژی پایدار، دانشکدۀ مهندسی انرژی و منابع پایدار، دانشگاه تهران، تهران، ایران

10.22059/ses.2024.369625.1046

چکیده

آلودگی‏های زیست‌محیطی، تغییرات اقلیمی و کمبود منابع سوخت فسیلی، از جمله عواملی هستند که باعث حرکت کشورها به سمت منابع تجدیدپذیر شده‏اند. بین منابع تجدیدپذیر، سهم انرژی بادی و خورشیدی در تولید برق، در سال‏های اخیر رشد زیادی داشته است. به دلیل ماهیت نامشخص و غیر قابل پیش‌بینی این منابع، استفاده از آن‏ها به صورت منفرد، برای تأمین تقاضای بار، قابلیت اطمینان پایینی دارد. با ترکیب منابع بادی و خورشیدی و تشکیل یک سیستم انرژی تجدیدپذیر هیبریدی، قابلیت اطمینان سیستم بالاتر خواهد رفت و همچنین می‏توان در برخی هزینه‏ها صرفه‏جویی کرد. اولین و مهم‏ترین مرحله در فرایند توسعۀ مزارع تجدیدپذیر، یافتن مکان‏های مناسب و بهینه برای احداث این مزارع است. هدف این مطالعه، ارائۀ یک چارچوب جامع برای مکان‏یابی مزارع هیبریدی بادی‌ـ فتوولتائیک در استان خراسان جنوبی است. برای نیل به این هدف، رویکرد تصمیم‏گیری چندمعیاره و سیستم اطلاعات جغرافیایی با یکدیگر ترکیب شدند. در این مطالعه برای استانداردسازی و وزن‏دهی به معیارهای ارزیابی، به‌ترتیب از توابع عضویت فازی و روش فرایند تحلیل سلسله‌مراتبی استفاده شد. نتایج این پژوهش نشان داد 02/0 درصد (54/36 کیلومتر مربع) از مساحت استان، پتانسیل بسیار خوبی برای توسعۀ مزارع هیبریدی بادی‌ـ فتوولتائیک دارند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Providing a comprehensive framework for site selection of hybrid wind-PV farms (case study: South Khorasan province)

نویسندگان [English]

  • Mohammadreza Khalili Tari 1
  • Younes Noorollahi 2
1 Master of Science, Department of Sustainable Energy Systems Engineering, Faculty of Energy Engineering and Sustainable Resources, University of Tehran, Tehran, Iran
2 Professor, Department of Sustainable Energy Systems Engineering, Faculty of Energy Engineering and Sustainable Resources, University of Tehran, Tehran, Iran
چکیده [English]

Environmental pollution, climate change, and lack of fossil fuel resources are among the factors that have caused countries to move towards renewable sources. Among renewable sources, the share of wind and solar energy in electricity production has grown a lot in recent years. Due to the uncertain and unpredictable nature of these sources, using them individually to meet load demand has low reliability. By combining wind and solar resources and forming a hybrid renewable energy system (HRES), the reliability of the system will increase. Also, some costs can be saved. The first and most important step in developing renewable farms is to find suitable and optimal places to build these farms. This study aims to provide a comprehensive framework for site selection of hybrid wind-PV farms in South Khorasan province. A multi-criteria decision-making approach and geographic information system were combined to achieve this goal. This study used the fuzzy membership functions and the Analytic Hierarchy Process (AHP) to standardize and weight evaluation criteria. The results of this research showed that 0.02 percent (36.54 square kilometers) of the area of the province has a very good potential for the development of hybrid wind-PV farms.

کلیدواژه‌ها [English]

  • Site selection
  • Hybrid renewable energy systems
  • wind-PV farms
  • Multi-criteria decision-making
  • Geographic information system

مراجع

  1.       REN21. Renewables 2022 Global Status Report [Internet]. REN21 Secretariat; 2022 [cited 2023 Apr 27]. Available from: https://www.ren21.net/wp-content/uploads/2019/05/GSR2022_Full_Report.pdf

    1. Patibandla A, Kollu R, Rayapudi SR, Manyala RR. A multi-objective approach for the optimal design of a standalone hybrid renewable energy system. Int J Energy Res. 2021 Oct 10;45(12):18121–48.
    2. Al Busaidi AS, Kazem HA, Al-Badi AH, Farooq Khan M. A review of optimum sizing of hybrid PV-Wind renewable energy systems in oman. Vol. 53, Renewable and Sustainable Energy Reviews. Elsevier Ltd; 2016. p. 185–93.
    3. AECOM Australia Pty Ltd. Co-location investigation: a study into the potential for co-locating wind and solar farms in Australia [Internet]. Sydney; 2016 [cited 2023 Apr 27]. Available from: http://www.aecom.com/au/wp-content/uploads/2016/03/Wind-solar-Co-location-Study-Final.pdf
    4. Noorollahi Y, Ghenaatpisheh Senani A, Fadaei A, Simaee M, Moltames R. A framework for GIS-based site selection and technical potential evaluation of PV solar farm using Fuzzy-Boolean logic and AHP multi-criteria decision-making approach. Renew Energy. 2022 Mar 1;186:89–104.
    5. The country’s wind energy technology development document [Internet]. 1st ed. Niroo Research Institute; 2016 [cited 2023 Aug 31]. Available from: https://www.nri.ac.ir/Tech-Plan
    6. Iran’s energy balance sheet in 1399 (2020-2021) [Internet]. Deputy of Electricity and Energy Affairs of Iran, Iran’s Ministry of Energy; 2023 [cited 2023 Apr 27]. Available from: https://pep.moe.gov.ir/
    7. Iran data overview and analysis [Internet]. U.S. Energy Information Administration (EIA). [cited 2023 Apr 27]. Available from: https://www.eia.gov/international/analysis/country/IRN
    8. Taherdoost H, Madanchian M. Multi-Criteria Decision Making (MCDM) Methods and Concepts. Encyclopedia. 2023 Jan 9;3(1):77–87.
    9. What is GIS? [Internet]. Environmental Systems Research Institute (Esri). [cited 2023 Apr 27]. Available from: https://www.esri.com/en-us/what-is-gis/overview
    10. Sánchez-Lozano JM, Teruel-Solano J, Soto-Elvira PL, Socorro García-Cascales M. Geographical Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms locations: Case study in south-eastern Spain. Vol. 24, Renewable and Sustainable Energy Reviews. Elsevier Ltd; 2013. p. 544–56.
    11. Sun L, Jiang Y, Guo Q, Ji L, Xie Y, Qiao Q, et al. A GIS-based multi-criteria decision making method for the potential assessment and suitable sites selection of PV and CSP plants. Resour Conserv Recycl. 2021 May 1;168.
    12. Azizkhani M, Vakili A, Noorollahi Y, Naseri F. Potential survey of photovoltaic power plants using Analytical Hierarchy Process (AHP) method in Iran. Vol. 75, Renewable and Sustainable Energy Reviews. Elsevier Ltd; 2017. p. 1198–206.
    13. Alami Merrouni A, Elwali Elalaoui F, Mezrhab A, Mezrhab A, Ghennioui A. Large scale PV sites selection by combining GIS and Analytical Hierarchy Process. Case study: Eastern Morocco. Renew Energy. 2018 Apr 1;119:863–73.
    14. Colak HE, Memisoglu T, Gercek Y. Optimal site selection for solar photovoltaic (PV) power plants using GIS and AHP: A case study of Malatya Province, Turkey. Renew Energy. 2020 Apr 1;149:565–76.
    15. 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.
    16. Zoghi M, Houshang Ehsani A, Sadat M, javad Amiri M, Karimi S. Optimization solar site selection by fuzzy logic model and weighted linear combination method in arid and semi-arid region: A case study Isfahan-IRAN. Vol. 68, Renewable and Sustainable Energy Reviews. Elsevier Ltd; 2017. p. 986–96.
    17. Sánchez-Lozano JM, García-Cascales MS, Lamata MT. Comparative TOPSIS-ELECTRE TRI methods for optimal sites for photovoltaic solar farms. Case study in Spain. J Clean Prod. 2016 Jul 20;127:387–98.
    18. Moradi S, Yousefi H, Noorollahi Y, Rosso D. Multi-criteria decision support system for wind farm site selection and sensitivity analysis: Case study of Alborz Province, Iran. Energy Strategy Reviews. 2020 May 1;29.
    19. Baseer MA, Rehman S, Meyer JP, Alam MM. GIS-based site suitability analysis for wind farm development in Saudi Arabia. Energy. 2017;141:1166–76.
    20. Arca D, Keskin Citiroglu H. Geographical information systems-based analysis of site selection for wind power plants in Kozlu District (Zonguldak-NW Turkey) by multi-criteria decision analysis method. Energy Sources, Part A: Recovery, Utilization and Environmental Effects. 2020;
    21. Villacreses G, Gaona G, Martínez-Gómez J, Jijón DJ. Wind farms suitability location using geographical information system (GIS), based on multi-criteria decision making (MCDM) methods: The case of continental Ecuador. Renew Energy. 2017;109:275–86.
    22. Li M, Xu Y, Guo J, Li Y, Li W. Application of a GIS-based fuzzy multi-criteria evaluation approach for wind farm site selection in China. Energies (Basel). 2020 May 1;13(10).

    24 Tercan E. Land suitability assessment for wind farms through best-worst method and GIS in Balıkesir province of Turkey. Sustainable Energy Technologies and Assessments. 2021 Oct 1;47.

    1. Koc A, Turk S, Şahin G. Multi-criteria of wind-solar site selection problem using a GIS-AHP-based approach with an application in Igdir Province/Turkey. Environmental Science and Pollution Research. 2019 Nov 1;26(31):32298–310.
    2. Chapter 1 - LAND AND CLIMATE. In: South Khorasan Province Statistical Yearbook 1399 (2020-2021) [Internet]. Statistical Center of Iran; [cited 2023 Apr 28]. Available from: https://nnt.sci.org.ir/sites/Apps/yearbook/Lists/year_book_req/Item/newifs.aspx
    3. Hafeznia H, Yousefi H, Razi Astaraei F. A novel framework for the potential assessment of utility-scale photovoltaic solar energy, application to eastern Iran. Energy Convers Manag. 2017 Nov 1;151:240–58.
    4. Hansen MOL. Aerodynamics of Wind Turbines. 3rd ed. Routledge; 2015.
    5. Günen MA. A comprehensive framework based on GIS-AHP for the installation of solar PV farms in Kahramanmaraş, Turkey. Renew Energy. 2021 Nov 1;178:212–25.
    6. Doljak D, Stanojević G, Miljanović D. A GIS-MCDA BASED ASSESSMENT FOR SITING WIND FARMS AND ESTIMATION OF THE TECHNICAL GENERATION POTENTIAL FOR WIND POWER IN SERBIA. Int J Green Energy. 2021;18(4):363–80.
    7. Giamalaki M, Tsoutsos T. Sustainable siting of solar power installations in Mediterranean using a GIS/AHP approach. Renew Energy. 2019 Oct 1;141:64–75.
    8. Al-Ghussain L, Darwish Ahmad A, Abubaker AM, Mohamed MA. An integrated photovoltaic/wind/biomass and hybrid energy storage systems towards 100% renewable energy microgrids in university campuses. Sustainable Energy Technologies and Assessments. 2021 Aug 1;46.
    9. Aly A, Jensen SS, Pedersen AB. Solar power potential of Tanzania: Identifying CSP and PV hot spots through a GIS multicriteria decision making analysis. Renew Energy. 2017;113:159–75.
    10. Ali S, Taweekun J, Techato K, Waewsak J, Gyawali S. GIS based site suitability assessment for wind and solar farms in Songkhla, Thailand. Renew Energy. 2019 Mar 1;132:1360–72.
    11. Noorollahi Y, Yousefi H, Mohammadi M. Multi-criteria decision support system for wind farm site selection using GIS. Sustainable Energy Technologies and Assessments. 2016 Feb 1;13:38–50.
    12. Yousefi H, Hafeznia H, Yousefi-Sahzabi A. Spatial site selection for solar power plants using a gis-based boolean-fuzzy logic model: A case study of Markazi Province, Iran. Energies (Basel). 2018;11(7).
    13. Ayodele TR, Ogunjuyigbe ASO, Odigie O, Munda JL. A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process: The case study of Nigeria. Appl Energy. 2018 Oct 15;228:1853–69.
    14. Santana-Sarmiento F, Velázquez-Medina S. Development of a Territorial Planning Model of Wind and Photovoltaic Energy Plants for Self-Consumption as a Low Carbon Strategy. Complexity. 2021;2021.
    15. Atici KB, Simsek AB, Ulucan A, Tosun MU. A GIS-based Multiple Criteria Decision Analysis approach for wind power plant site selection. Util Policy. 2015 Dec 1;37:86–96.
    16. Zadeh LA. Fuzzy sets. Information and Control [Internet]. 1965;8(3):338–53. Available from: https://www.sciencedirect.com/science/article/pii/S001999586590241X
    17. Latinopoulos D, Kechagia K. A GIS-based multi-criteria evaluation for wind farm site selection. A regional scale application in Greece. Renew Energy. 2015;78:550–60.
    18. Nasehi S, Karimi S, Jafari H. Application of fuzzy GIS and ANP for wind power plant site selection in East Azerbaijan Province of Iran. Computational Research Progress in Applied Science & Engineering. 2016;2(3):116–24.
    19. Saaty TL. The analytic hierarchy process : planning, priority setting, resource allocation. New York ; London : McGraw-Hill International Book Co.; 1980.
    20. Ghasemi G, Noorollahi Y, Alavi H, Marzband M, Shahbazi M. Theoretical and technical potential evaluation of solar power generation in Iran. Renew Energy. 2019 Aug 1;138:1250–61.
    21. Barzehkar M, Parnell KE, Mobarghaee Dinan N, Brodie G. Decision support tools for wind and solar farm site selection in Isfahan Province, Iran. Clean Technol Environ Policy. 2021 May 1;23(4):1179–95.

     

فصلنامه سیستم های انرژی پایدار
دوره 2، شماره 3
تیر 1402
صفحه 237-255

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