Advertisement

Environmental Science and Pollution Research

, Volume 25, Issue 20, pp 19753–19766 | Cite as

MCDM analysis of wind energy in Turkey: decision making based on environmental impact

  • Sinem Değirmenci
  • Ferhat Bingöl
  • Sait C. Sofuoglu
Research Article
  • 157 Downloads

Abstract

Development of new wind energy projects require complex planning process involving many social, technical, economic, environmental, political concerns, and different agents such as investors, utilities, governmental agencies, or social groups. The aim of this study is to develop a tool combining Geographic Information System (GIS) and Multi-Criteria Decision-Making (MCDM) methodologies, and its application for Turkey as a case study. A variety of constraints and criteria were identified based on a literature review and regulations gathered from variety of agencies, use of which resulted in determination of infeasible sites. Then, pairwise comparisons were carried out using analytic hierarchy process as the MCDM method to estimate relative importance of the criteria, and to visualize a suitability map with three classes. As the final stage, decision making was carried out based on environmental impact where 45.5% of the Turkish territory was found as infeasible area. Sixty percent of the remaining area are covered by the moderate suitability class, followed by the highly suitable area (20.3%) and low suitable area (19.8%). The output of this study can be used by energy planners to estimate the extent that wind energy can be developed based on public perception, administrative, and environmental aspects.

Keywords

Wind Energy Environmental impact MCDM AHP GIS 

Notes

Acknowledgements

The authors express their gratitude to Doğa Derneği for providing the necessary data concerning Important Bird Areas. Furthermore, the authors would like to thank two projects which provided some of the ground dataset layers for the study: (i) Wind data from DTU Wind Energy Global Wind Atlas, funded by Danish Energy Agency EUDP 11-II; (ii) elevation, air density, and wind farm data from the TUBITAK project “Adaptation of Uniform Wind Atlases” (114C016).

Supplementary material

11356_2018_2004_MOESM1_ESM.pdf (145 kb)
Online Resource 1 (PDF 145 kb)
11356_2018_2004_MOESM2_ESM.pdf (365 kb)
Online Resource 2 (PDF 364 kb)

References

  1. Abromas J, Kamičaitytė-Virbašienė J (2014) Identification of visual influence zones of wind farms in Lithuania. Rigas Tehniskas Universitates Zinatniskie Raksti 9:43.  https://doi.org/10.7250/aup.2014.006
  2. Al-Yahyai S, Charabi Y, Gastli A, Al-Badi A (2012) Wind farm land suitability indexing using multi-criteria analysis. Renew Energy 44:80–87CrossRefGoogle Scholar
  3. Atici KB, Simsek AB, Ulucan A, Tosun MU (2015) A GIS-based multiple criteria decision analysis approach for wind power plant site selection. Util Policy 37:86–96CrossRefGoogle Scholar
  4. AWEA (2008) Wind energy for a new era. American Wind Energy Association, Washington, D.C.Google Scholar
  5. Aydin NY, Kentel E, Duzgun S (2010) GIS-based environmental assessment of wind energy systems for spatial planning: a case study from Western Turkey. Renew Sust Energ Rev 14(1):364–373CrossRefGoogle Scholar
  6. Baban SM, Parry T (2001) Developing and applying a GIS-assisted approach to locating wind farms in the UK. Renew Energy 24(1):59–71CrossRefGoogle Scholar
  7. Bennui A, Rattanamanee P, Puetpaiboon U, Phukpattaranont P, Chetpattananondh K (2007) Site selection for large wind turbine using GIS. PSU-UNS International Conference on Engineering and EnvironmentGoogle Scholar
  8. Bilgili M, Simsek E (2012) Wind energy potential and turbine installations in Turkey. Energy Sources Part B 7(2):140–151CrossRefGoogle Scholar
  9. Bingöl F (2016) TUBITAK project adaptation of uniform wind atlases (114C016)Google Scholar
  10. Coordinates of Special Environmentally Protected Areas (1990) Turkish Republic Official Journal, 20702, 24218, 24055, 27793, 26551, 25339, 28737, 21 November 1990, 2 November 2000, 21 May 2000, 22 December 2010, 13 June 2007, 07 January 2004, 16 August 2013Google Scholar
  11. Coordinates of Special Environmentally Protected Areas (2000) Turkish Republic Official Journal, 20702, 24218, 24055, 27793, 26551, 25339, 28737, 21 November 1990, 2 November 2000, 21 May 2000, 22 December 2010, 13 June 2007, 07 January 2004, 16 August 2013Google Scholar
  12. Coordinates of Special Environmentally Protected Areas (2004) Turkish Republic Official Journal, 20702, 24218, 24055, 27793, 26551, 25339, 28737, 21 November 1990, 2 November 2000, 21 May 2000, 22 December 2010, 13 June 2007, 07 January 2004, 16 August 2013Google Scholar
  13. Coordinates of Special Environmentally Protected Areas (2007) Turkish Republic Official Journal, 20702, 24218, 24055, 27793, 26551, 25339, 28737, 21 November 1990, 2 November 2000, 21 May 2000, 22 December 2010, 13 June 2007, 07 January 2004, 16 August 2013Google Scholar
  14. Coordinates of Special Environmentally Protected Areas (2010) Turkish Republic Official Journal, 20702, 24218, 24055, 27793, 26551, 25339, 28737, 21 November 1990, 2 November 2000, 21 May 2000, 22 December 2010, 13 June 2007, 07 January 2004, 16 August 2013Google Scholar
  15. Coordinates of Special Environmentally Protected Areas (2013) Turkish Republic Official Journal, 20702, 24218, 24055, 27793, 26551, 25339, 28737, 21 November 1990, 2 November 2000, 21 May 2000, 22 December 2010, 13 June 2007, 07 January 2004, 16 August 2013Google Scholar
  16. CORINE (2002) Land Cover Technical Guide - Addendum 2000, EEA, 2000; EEA: I&CLC2000 Technical GuidelinesGoogle Scholar
  17. Demirtaş R (2005) Kentsel Planlamada Diri Faylar Etrafında Tampon Bölge Oluşturma Esasları. Ankara University Press, AnkaraGoogle Scholar
  18. DTU (2016) Data from DTU Wind Energy Global Wind Atlas, funded by Danish Energy Agency EUDP 11-II, Globalt Vind Atlas J.nr. 64011-0347Google Scholar
  19. Dursun B, Gokcol C (2014) Impacts of the renewable energy law on the developments of wind energy in Turkey. Renew Sust Energ Rev 40:318–325CrossRefGoogle Scholar
  20. EMRA (2015) Electricity Generation Licenses. http://lisans.epdk.org.tr/epvys-web/faces/pages/lisans/elektrikUretim/elektrikUretimOzetSorgula.xhtml. Accessed 31 July 2015
  21. EWEA (2015). Wind energy scenarios for 2030, European Wind Energy AssociationGoogle Scholar
  22. Forest Law (1956) Turkish Republic Official Journal, 9402, 08 October 1956Google Scholar
  23. Gass V, Schmidt J, Strauss F, Schmid E (2013) Assessing the economic wind power potential in Austria. Energy Policy 53:323–330CrossRefGoogle Scholar
  24. Georgiou A, Polatidis H, Haralambopoulos D (2012) Wind energy resource assessment and development: decision analysis for site evaluation and application. Energy Sources Part A 34(19):1759–1767CrossRefGoogle Scholar
  25. Góralczyk M (2003) Life-cycle assessment in the renewable energy sector. Appl Energy 75(3–4):205–211CrossRefGoogle Scholar
  26. Gorsevski PV, Cathcart SC, Mirzaei G, Jamali MM, Ye X, Gomezdelcampo E (2013) A group-based spatial decision support system for wind farm site selection in Northwest Ohio. Energy Policy 55:374–385CrossRefGoogle Scholar
  27. Grassi S, Chokani N, Abhari RS (2012) Large scale technical and economical assessment of wind energy potential with a GIS tool: case study Iowa. Energy Policy 45:73–85CrossRefGoogle Scholar
  28. Hansen HS (2005) GIS-based multi-criteria analysis of wind farm development. In: H Hauska, Tveite H (eds) ScanGis 2005: Proceedings of the 10th Scandinavian Research Conference on Geographical Information Science. Department of Planning and Environment, Stockholm, pp 75–87Google Scholar
  29. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25(15):1965–1978CrossRefGoogle Scholar
  30. 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. Appl Energy 163:222–243CrossRefGoogle Scholar
  31. Hughes G (2012) The performance of wind farms in the United Kingdom and Denmark. Renewable Energy Foundation, LondonGoogle Scholar
  32. Ilkılıç C, Aydın H, Behçet R (2011) The current status of wind energy in Turkey and in the world. Energy Policy 39(2):961–967CrossRefGoogle Scholar
  33. Jarvis, A. ; H. I. Reuter ; A. Nelson ; E. Guevara (2008) Hole-filled SRTM for the globe Version 4. available from the CGIAR-CSI SRTM 90m Database (http://srtm.csi.cgiar.org)
  34. KOERI. Boğaziçi University Kandilli Obsevatory and Earthquake Research Instıtute Regional Earthquake-Tsunami Monitoring Center. Retrieved [10 November 2015]Google Scholar
  35. Kumar I, Tyner WE, Sinha KC (2016) Input–output life cycle environmental assessment of greenhouse gas emissions from utility scale wind energy in the United States. Energy Policy 89:294–301CrossRefGoogle Scholar
  36. KusBank Veritabanı, Doğa Derneği: Royal Society for the Protection of Birds and BirdLife International. Erciyes Üniversitesi www.kusbank.org. [19 May 2016]
  37. Latinopoulos D, Kechagia K (2015) A GIS-based multi-criteria evaluation for wind farm site selection. A regional scale application in Greece. Renew Energy 78:550–560CrossRefGoogle Scholar
  38. Law on National Parks (1983) Turkish Republic Official Journal, 18132, 11 August 1983Google Scholar
  39. Law on Protection of Cultural and Natural Properties (1983) Turkish Republic Official Journal, 18113, 23 July 1983Google Scholar
  40. Law on Wildlife Protection and Development Areas (2004) Turkish Republic Official Journal, 25637, 8 November 2004Google Scholar
  41. Legislation for Construction Criteria Around the Airports (2012) Turkish Republic General Directorate of Civil NavigationGoogle Scholar
  42. Legistration on Prelicence of Wind and Solar Power (2014) Turkish Republic Official Journal, 29033, 17 June 2014Google Scholar
  43. Lejeune P, Feltz C (2008) Development of a decision support system for setting up a wind energy policy across the Walloon Region (southern Belgium). Renew Energy 33(11):2416–2422CrossRefGoogle Scholar
  44. Malczewski J (2010) Multiple criteria decision analysis and geographic information systems. In: Ehrgott M, Figueira RJ, Greco S (eds) Trends in multiple criteria decision analysis. Springer, Boston, pp 369–395CrossRefGoogle Scholar
  45. Moeinaddini M, Khorasani N, Danehkar A, Darvishsefat AA (2010) Siting MSW landfill using weighted linear combination and analytical hierarchy process (AHP) methodology in GIS environment (case study: Karaj). Waste Manag 30(5):912–920CrossRefGoogle Scholar
  46. Noorollahi Y, Yousefi H, Mohammadi M (2016) Multi-criteria decision support system for wind farm site selection using GIS. Sustain Energy Technol Assess 13:38–50Google Scholar
  47. OpenStreetMap (2015). Available: http://planet.openstreetmap.org [20 June 2016]
  48. Phuangpornpitak N, Tia S (2011) Feasibility study of wind farms under the Thai very small scale renewable energy power producer (VSPP) program. Energy Procedia 9:159–170CrossRefGoogle Scholar
  49. Pohekar S, Ramachandran M (2004) Application of multi-criteria decision making to sustainable energy planning—a review. Renew Sust Energ Rev 8(4):365–381CrossRefGoogle Scholar
  50. Regulation for Article 18 of the 17/3 of the Forest Law (2014) Turkish Republic Official Journal, 28976, 18 April 2014Google Scholar
  51. Regulation on Assessment and Management of Environmental Noise (2008) Turkish Republic Official Journal, 26809, 7 March 2008Google Scholar
  52. Regulation on the Technical Assessment of Applications related to Wind Power Generation (2015) Turkish Republic Official Journal, 29508, 20 October 2015Google Scholar
  53. REPA (2007) Turkish wind energy potential atlas. General Directorate of Renewable Energy, AnkaraGoogle Scholar
  54. Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New YorkGoogle Scholar
  55. Saaty TL (2008) Decision making with the analytic hierarchy process. Int J Serv Sci 1(1):83–98Google Scholar
  56. Sánchez-Lozano JM, García-Cascales M, Lamata M (2014) Identification and selection of potential sites for onshore wind farms development in region of Murcia, Spain. Energy 73:311–324CrossRefGoogle Scholar
  57. Schallenberg-Rodríguez J, Notario-del Pino J (2014) Evaluation of on-shore wind techno-economical potential in regions and islands. Appl Energy 124:117–129CrossRefGoogle Scholar
  58. Sliz-Szkliniarz B, Vogt J (2011) GIS-based approach for the evaluation of wind energy potential: a case study for the Kujawsko–Pomorskie Voivodeship. Renew Sust Energ Rev 15(3):1696–1707CrossRefGoogle Scholar
  59. Tegou L-I, Polatidis H, Haralambopoulos DA (2010) Environmental management framework for wind farm siting: methodology and case study. J Environ Manag 91(11):2134–2147CrossRefGoogle Scholar
  60. TEIAS (2015) Capacity report of electricity distribution companies’ production. Turkish Electricity Distribution General Directorate. https://www.epdk.org.tr/Detay/Download/5023. Accessed 1 March 2016
  61. Tremeac B, Meunier F (2009) Life cycle analysis of 4.5 MW and 250 W wind turbines. Renew Sust Energ Rev 13(8):2104–2110CrossRefGoogle Scholar
  62. TUIK (2014). Turkey in Statistics, Available: http://www.turkstat.gov.tr [31 May 2016]. Turkish Statistical Institute
  63. Turkey (2014) Revenue administration, The minimum land costs, Available: https://intvd.gib.gov.tr/2014_Emlak_Arsa/ [31 October 2015].
  64. TWEA (2015) Turkish Wind Energy Statistics Report-July. Turkish Wind Energy Association. https://www.tureb.com.tr/yayinlar. Accessed 13 Dec 2015
  65. TWEA (2016) Turkish wind energy statistics report-January. Turkish Wind Energy Association. https://www.tureb.com.tr/yayinlar. Accessed 25 May 2016
  66. Twidell J, Weir T (2015) Renewable energy resources, 3rd edn. Taylor and Francis, LondonGoogle Scholar
  67. UNESCO (2016a) Camili-United Nations Educational, Scientific and Cultural Organization. http://www.unesco.org/new/en/natural-sciences/environment/ecological-sciences/biosphere-reserves/europe-north-america/turkey/camili/. Accessed 2 Feb 2016
  68. UNESCO (2016b) World Heritage list. whc.unesco.org/en/list/kml. Accessed 28 Jan 2016
  69. 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. Renew Sust Energ Rev 15(7):3332–3340CrossRefGoogle Scholar
  70. Voivontas D, Assimacopoulos D, Mourelatos A, Corominas J (1998) Evaluation of renewable energy potential using a GIS decision support system. Renew Energy 13(3):333–344CrossRefGoogle Scholar
  71. Watson JJ, Hudson MD (2015) Regional scale wind farm and solar farm suitability assessment using GIS-assisted multi-criteria evaluation. Landsc Urban Plan 138:20–31CrossRefGoogle Scholar
  72. Weisser D (2007) A guide to life-cycle greenhouse gas (GHG) emissions from electric supply technologies. Energy 32(9):1543–1559CrossRefGoogle Scholar
  73. Zimmerling JR, Pomeroy AC, d’Entremont MV, Francis CM (2013) Canadian estimate of bird mortality due to collisions and direct habitat loss associated with wind turbine developments estimation de la mortalité aviaire canadienne attribuable aux collisions et aux pertes directes d’habitat associées à l’éolien. Avian Conserv Ecol 8(2):10Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Environmental EngineeringIzmir Institute of TechnologyIzmirTurkey
  2. 2.Department of Energy System EngineeringIzmir Institute of TechnologyIzmirTurkey
  3. 3.Department of Chemical EngineeringIzmir Institute of TechnologyIzmirTurkey

Personalised recommendations