Abstract
The objective of this study was to find the most suitable places for wind power plants by using geographic information systems (GIS) and the fuzzy analytic hierarchy process (FAHP). To this purpose, a FAHP–GIS based model was developed with 17 main criteria and 81 sub-criteria relevant to wind power plants. These included a number of important criteria which have been ignored or not used to date in the wind power plant site selection studies in the literature. Weights showing the degree of importance of each criteria were calculated via the fuzzy analytic hierarchy process method and integrated to the model. The geographic data for the sample study area were collected and processed via GIS, and a suitability map for wind power plants and restricted regions in the sample study area was generated by overlaying all the weighted maps. As a result of the study, restricted areas, the most suitable areas and less suitable areas for the study area were determined with the help of the suitability map created by introducing the new criteria. With this study, the proposed FAHP-GIS model, which is developed with the proposed new criteria, will provide more accurate results in the wind power plant site selection studies.
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References
Alizadeh, R., Soltanisehat, L., Lund, P. D., & Zamanisabzi, H. (2020). Improving renewable energy policy planning and decision-making through a hybrid MCDM method. Energy Policy. https://doi.org/10.1016/j.enpol.2019.111174
Aydin, N. Y., Kentel, E., & Duzgun, S. (2010). GIS-based environmental assessment of wind energy systems for spatial planning: A case study from Western Turkey. Renewable and Sustainable Energy Reviews, 14(1), 364–373. https://doi.org/10.1016/j.rser.2009.07.023
Ayodele, T. R., Ogunjuyigbe, A. S. O., Odigie, O., & Munda, J. L. (2018). A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process: The case study of Nigeria. Applied Energy, 228(April), 1853–1869. https://doi.org/10.1016/j.apenergy.2018.07.051
Baban, S. M. J., & Parry, T. (2001). Developing and applying a GIS-assisted approach to locating wind farms in the UK. Renewable Energy, 24(1), 59–71. https://doi.org/10.1016/S0960-1481(00)00169-5
Büyüközkan, G., Göçer, F., & Karabulut, Y. (2019). A new group decision making approach with IF AHP and IF VIKOR for selecting hazardous waste carriers. Measurement: Journal of the International Measurement Confederation, 134, 66–82. https://doi.org/10.1016/j.measurement.2018.10.041.
Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649–655. https://doi.org/10.1016/0377-2217(95)00300-2
Charabi, Y., & Gastli, A. (2011). PV site suitability analysis using GIS-based spatial fuzzy multi-criteria evaluation. Renewable Energy, 36(9), 2554–2561. https://doi.org/10.1016/j.renene.2010.10.037
Chatzimouratidis, A. I., & Pilavachi, P. A. (2008). Sensitivity analysis of the evaluation of power plants impact on the living standard using the analytic hierarchy process. Energy Conversion and Management, 49(12), 3599–3611. https://doi.org/10.1016/j.enconman.2008.07.009
Chingulpitak, S., & Wongwises, S. (2014). Critical review of the current status of wind energy in Thailand. Renewable and Sustainable Energy Reviews, 31, 312–318. https://doi.org/10.1016/j.rser.2013.11.038
Choudhary, D., & Shankar, R. (2012). An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India. Energy, 42(1), 510–521. https://doi.org/10.1016/j.energy.2012.03.010
Das, N., & Mukhopadhyay, S. (2018). Application of multi-criteria decision making technique for the assessment of groundwater potential zones: a study on Birbhum district, West Bengal, India. Environment, Development and Sustainability,. https://doi.org/10.1007/s10668-018-0227-7
Defne, Z., Haas, K. A., & Fritz, H. M. (2011). GIS based multi-criteria assessment of tidal stream power potential: A case study for Georgia, USA. Renewable and Sustainable Energy Reviews, 15(5), 2310–2321. https://doi.org/10.1016/j.rser.2011.02.005
Deveci, M., Özcan, E., John, R., Covrig, C.-F., & Pamucar, D. (2020). A study on offshore wind farm siting criteria using a novel interval-valued fuzzy-rough based Delphi method. Journal of Environmental Management, 270(May), 110916. https://doi.org/10.1016/j.jenvman.2020.110916
Didier Dubois, H. P. (1980). Fuzzy sets and systems: Theory and applications. Mathematics in Science and Engineering. https://doi.org/10.1137/1027081
Doljak, D., & Stanojević, G. (2017). Evaluation of natural conditions for site selection of ground-mounted photovoltaic power plants in Serbia. Energy, 127, 291–300. https://doi.org/10.1016/j.energy.2017.03.140
Erbil, A. Ö. (2011). Social acceptance of the clean energy concept: Exploring the clean energy understanding of Istanbul residents. Renewable and Sustainable Energy Reviews, 15(9), 4498–4506. https://doi.org/10.1016/j.rser.2011.07.101
Eroğlu, H., & Aydin, M. (2015). Optimization of electrical power transmission lines’ routing using AHP, fuzzy AHP, and GIS. Turkish Journal of Electrical Engineering and Computer Sciences, 23(5), 1418–1430. https://doi.org/10.3906/elk-1211-59
Ertay, T., Kahraman, C., & Kaya, İ. (2013). Evaluation of renewable energy alternatives using macbeth and fuzzy ahp multicriteria methods: The case of Turkey. Technological and Economic Development of Economy, 19(1), 38–62. https://doi.org/10.3846/20294913.2012.762950
Gao, J., Guo, F., Ma, Z., Huang, X., & Li, X. (2020). Multi-criteria group decision-making framework for offshore wind farm site selection based on the intuitionistic linguistic aggregation operators. Energy, 204, 117899. https://doi.org/10.1016/j.energy.2020.117899
Gorsevski, P. V., Cathcart, S. C., Mirzaei, G., Jamali, M. M., Ye, X., & Gomezdelcampo, E. (2013). A group-based spatial decision support system for wind farm site selection in Northwest Ohio. Energy Policy, 55, 374–385. https://doi.org/10.1016/j.enpol.2012.12.013
Haq, A. N., & Kannan, G. (2006). Fuzzy analytical hierarchy process for evaluating and selecting a vendor in a supply chain model. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-005-2562-8
Heo, E., Kim, J., & Boo, K. J. (2010). Analysis of the assessment factors for renewable energy dissemination program evaluation using fuzzy AHP. Renewable and Sustainable Energy Reviews, 14(8), 2214–2220. https://doi.org/10.1016/j.rser.2010.01.020
Höfer, T., Sunak, Y., Siddique, H., & Madlener, R. (2016). Wind farm siting using a spatial analytic hierarchy process approach: A case study of the Städteregion Aachen. Applied Energy, 163, 222–243. https://doi.org/10.1016/j.apenergy.2015.10.138
Huang, C. C., Chu, P. Y., & Chiang, Y. H. (2008). A fuzzy AHP application in government-sponsored R&D project selection. Omega. https://doi.org/10.1016/j.omega.2006.05.003
Ibrahim, G. R. F., Hamid, A. A., Darwesh, U. M., & Rasul, A. (2020). A GIS-based Boolean logic-analytical hierarchy process for solar power plant (case study: Erbil Governorate—Iraq). Environment, Development and Sustainability. https://doi.org/10.1007/s10668-020-00862-3
Janke, J. R. (2010). Multicriteria GIS modeling of wind and solar farms in Colorado. Renewable Energy, 35(10), 2228–2234. https://doi.org/10.1016/j.renene.2010.03.014
Kahraman, C., & Kaya, I. (2010). A fuzzy multicriteria methodology for selection among energy alternatives. Expert Systems with Applications, 37(9), 6270–6281. https://doi.org/10.1016/j.eswa.2010.02.095
Kengpol, A., Rontlaong, P., & Tuominen, M. (2013). A decision support system for selection of solar power plant locations by applying fuzzy AHP and TOPSIS: An empirical study. Journal of Software Engineering and Applications, 06(09), 470–481. https://doi.org/10.4236/jsea.2013.69057
Khan, A. A., Shameem, M., Nadeem, M., & Akbar, M. A. (2021). Agile trends in Chinese global software development industry: Fuzzy AHP based conceptual mapping. Applied Soft Computing. https://doi.org/10.1016/j.asoc.2021.107090
Kim, C. K., Jang, S., & Kim, T. Y. (2018). Site selection for offshore wind farms in the southwest coast of South Korea. Renewable Energy, 120, 151–162. https://doi.org/10.1016/j.renene.2017.12.081
Lee, A. H. I., Chen, H. H., & Kang, H. Y. (2009). Multi-criteria decision making on strategic selection of wind farms. Renewable Energy, 34(1), 120–126. https://doi.org/10.1016/j.renene.2008.04.013
Liu, Y., Eckert, C. M., & Earl, C. (2020). A review of fuzzy AHP methods for decision-making with subjective judgements. Expert Systems with Applications. Elsevier Ltd. https://doi.org/10.1016/j.eswa.2020.113738.
Majumder, P., Majumder, M., & Saha, A. K. (2020a). Real-time monitoring of power production in modular hydropower plant: most significant parameter approach. Environment, Development and Sustainability, 22(5), 4025–4042. https://doi.org/10.1007/s10668-019-00369-6
Majumder, P., Majumder, M., Saha, A. K., & Nath, S. (2020b). Selection of features for analysis of reliability of performance in hydropower plants: a multi-criteria decision making approach. Environment, Development and Sustainability, 22(4), 3239–3265. https://doi.org/10.1007/s10668-019-00343-2
Mari, R., Bottai, L., Busillo, C., Calastrini, F., Gozzini, B., & Gualtieri, G. (2011). A GIS-based interactive web decision support system for planning wind farms in Tuscany (Italy). Renewable Energy, 36(2), 754–763. https://doi.org/10.1016/j.renene.2010.07.005
Marques, A. T., Batalha, H., Rodrigues, S., Costa, H., Pereira, M. J. R., Fonseca, C., et al. (2014). Understanding bird collisions at wind farms: An updated review on the causes and possible mitigation strategies. Biological Conservation, 179, 40–52. https://doi.org/10.1016/j.biocon.2014.08.017
Moradi, S., Yousefi, H., Noorollahi, Y., & Rosso, D. (2020). Multi-criteria decision support system for wind farm site selection and sensitivity analysis: Case study of Alborz Province, Iran. Energy Strategy Reviews. https://doi.org/10.1016/j.esr.2020.100478
Özdağoğlu, A., & Özdağoğlu, G. (2007). Comparison of AHP and Fuzzy AHP for the multi-criteria decision making processes with linguistic evaluations. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, 6(11), 65–85
Pechak, O., Mavrotas, G., & Diakoulaki, D. (2011). Role and contribution of the clean development mechanism to the development of wind energy. Renewable and Sustainable Energy Reviews, 15(7), 3380–3387. https://doi.org/10.1016/j.rser.2011.04.030
Saaty, T. L. (2010). The analytic hierarchy and analytic network measurement processes. The Measurement of Intangibles, 1, 91–166. https://doi.org/10.1007/978-3-540-92828-7_4
Sánchez-Lozano, J. M., García-Cascales, M. S., & Lamata, M. T. (2014). Identification and selection of potential sites for onshore wind farms development in region of murcia, Spain. Energy, 73, 311–324. https://doi.org/10.1016/j.energy.2014.06.024
Saraswat, S. K., Digalwar, A. K., Yadav, S. S., & Kumar, G. (2021). MCDM and GIS based modelling technique for assessment of solar and wind farm locations in India. Renewable Energy, 169, 865–884. https://doi.org/10.1016/j.renene.2021.01.056
Shahid, A., Taweekun, J., Techato, K., Waewsak, J., & Gyawali, S. (2019). GIS based site suitability assessment for wind and solar farms in Songkhla, Thailand. Renewable Energy, 132, 1360–1372. https://doi.org/10.1016/j.renene.2018.09.035
Sliz-Szkliniarz, B., & Vogt, J. (2011). GIS-based approach for the evaluation of wind energy potential: A case study for the Kujawsko-Pomorskie Voivodeship. Renewable and Sustainable Energy Reviews, 15(3), 1696–1707. https://doi.org/10.1016/j.rser.2010.11.045
Song, M., Wen, Y., Duan, B., Wang, J., & Gong, Q. (2017). Micro-siting optimization of a wind farm built in multiple phases. Energy, 137, 95–103. https://doi.org/10.1016/j.energy.2017.06.127
Sten, H. (2005). GIS-based Multi-Criteria Analysis of Wind Farm Development. Published in: ScanGis 2005. ScanGIS’2005, (January 2003), 75–87.
Syamsuddin, I. (2013). Multicriteria evaluation and sensitivity analysis on information security. International Journal of Computer Applications, 69(24), 22–25. https://doi.org/10.5120/12120-8242
Tan, Q., Wei, T., Peng, W., Yu, Z., & Wu, C. (2020a). Comprehensive evaluation model of wind farm site selection based on ideal matter element and grey clustering. Journal of Cleaner Production, 272, 122658. https://doi.org/10.1016/j.jclepro.2020.122658
Tegou, L. I., Polatidis, H., & Haralambopoulos, D. A. (2010). Environmental management framework for wind farm siting: Methodology and case study. Journal of Environmental Management, 91(11), 2134–2147. https://doi.org/10.1016/j.jenvman.2010.05.010
Tezer, A., Turkay, Z., Uzun, O., Terzi, F., Koylu, P., Karacor, E., et al. (2018). Ecosystem services-based multi-criteria assessment for ecologically sensitive watershed management. Environment, Development and Sustainability,. https://doi.org/10.1007/s10668-018-00300-5
Van Haaren, R., & Fthenakis, V. (2011). GIS-based wind farm site selection using spatial multi-criteria analysis (SMCA): Evaluating the case for New York State. Renewable and Sustainable Energy Reviews, 15(7), 3332–3340. https://doi.org/10.1016/j.rser.2011.04.010
Wang, B., Song, J., Ren, J., Li, K., Duan, H., & Wang, X. (2019). Selecting sustainable energy conversion technologies for agricultural residues: A fuzzy AHP-VIKOR based prioritization from life cycle perspective. Resources, Conservation and Recycling. https://doi.org/10.1016/j.resconrec.2018.11.011
Yildirim, V., & Nisanci, R. (2010). Developing a Geospatial Model for Power Transmission Line Routing in Turkey. In Developing a Geospatial Model for Power Transmission Line Routing in Turkey (pp. 11–16).
Yucesan, M., & Kahraman, G. (2019). Risk evaluation and prevention in hydropower plant operations: A model based on Pythagorean fuzzy AHP. Energy Policy. https://doi.org/10.1016/j.enpol.2018.11.039
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Eroğlu, H. Multi-criteria decision analysis for wind power plant location selection based on fuzzy AHP and geographic information systems. Environ Dev Sustain 23, 18278–18310 (2021). https://doi.org/10.1007/s10668-021-01438-5
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DOI: https://doi.org/10.1007/s10668-021-01438-5