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A hybrid AHP-PROMETHEE II onshore wind farms multicriteria suitability analysis using kNN and SVM regression models in northeastern Greece

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  • Sotiropoulou, Kalliopi F.
  • Vavatsikos, Athanasios P.
  • Botsaris, Pantelis N.

Abstract

Wind energy presents a high growth potential in the EU as an emission reduction strategy and to achieve the climate neutrality goal by 2050. Wind farms suitability analysis is one of the primary goals in the spatial planning of wind energy developments. This research paper introduces a hybrid spatial multicriteria GIS-based framework that combines Analytic Hierarchy Process (AHP), PROMETHEE II and Machine Learning algorithms to determine and predict the most efficient onshore wind farm locations by generating suitability index mappings. The methodology allows to overcome PROMETHEE II limitations in raster driven suitability analysis, utilizing machine learning regression methods as the k Nearest Neighbor and Support Vector Machines to predict a graduating mapping of suitability index for wind farm locations in northeastern Greece. The best configured models presented a RMSE of 0.0344 and 0.0154 respectively, indicating a quite high predictive performance. Suitability results indicate that 56.10 % of the feasible locations in the Thrace area present a positive outranking character for the kNN model and 56.79 % for the SVR model. The proposed framework, enriched by PROMETHEE II capabilities, assists energy and spatial planners in identifying suitable sites for wind farm siting and enables rational decision making that enhances efficient wind energy investments.

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  • Sotiropoulou, Kalliopi F. & Vavatsikos, Athanasios P. & Botsaris, Pantelis N., 2024. "A hybrid AHP-PROMETHEE II onshore wind farms multicriteria suitability analysis using kNN and SVM regression models in northeastern Greece," Renewable Energy, Elsevier, vol. 221(C).
    • Handle: RePEc:eee:renene:v:221:y:2024:i:c:s096014812301710x
    DOI: 10.1016/j.renene.2023.119795
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    References listed on IDEAS

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    1. Bertrand Mareschal & Jean Pierre Brans, 1994. "PROMCALC & GAIA: a new decision support system for multicriteria decision aid," ULB Institutional Repository 2013/9349, ULB -- Universite Libre de Bruxelles.
    2. Thomas L. Saaty, 1986. "Axiomatic Foundation of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 32(7), pages 841-855, July.
    3. Ishizaka, Alessio & Nemery, Philippe & Lidouh, Karim, 2013. "Location selection for the construction of a casino in the Greater London region: A triple multi-criteria approach," Tourism Management, Elsevier, vol. 34(C), pages 211-220.
    4. Athanasios P. Vavatsikos & Kalliopi F. Sotiropoulou & Veniamin Tzingizis, 2022. "GIS-assisted suitability analysis combining PROMETHEE II, analytic hierarchy process and inverse distance weighting," Operational Research, Springer, vol. 22(5), pages 5983-6006, November.
    5. Shao, Meng & Han, Zhixin & Sun, Jinwei & Xiao, Chengsi & Zhang, Shulei & Zhao, Yuanxu, 2020. "A review of multi-criteria decision making applications for renewable energy site selection," Renewable Energy, Elsevier, vol. 157(C), pages 377-403.
    6. Dell’Ovo, Marta & Capolongo, Stefano & Oppio, Alessandra, 2018. "Combining spatial analysis with MCDA for the siting of healthcare facilities," Land Use Policy, Elsevier, vol. 76(C), pages 634-644.
    7. Karatzoglou, Alexandros & Meyer, David & Hornik, Kurt, 2006. "Support Vector Machines in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 15(i09).
    8. Saraswat, S.K. & Digalwar, Abhijeet K. & Yadav, S.S. & Kumar, Gaurav, 2021. "MCDM and GIS based modelling technique for assessment of solar and wind farm locations in India," Renewable Energy, Elsevier, vol. 169(C), pages 865-884.
    9. Despotovic, Milan & Nedic, Vladimir & Despotovic, Danijela & Cvetanovic, Slobodan, 2016. "Evaluation of empirical models for predicting monthly mean horizontal diffuse solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 246-260.
    10. Sotiropoulou, Kalliopi F. & Vavatsikos, Athanasios P., 2021. "Onshore wind farms GIS-Assisted suitability analysis using PROMETHEE II," Energy Policy, Elsevier, vol. 158(C).
    11. Thomas L. Saaty, 2005. "The Analytic Hierarchy and Analytic Network Processes for the Measurement of Intangible Criteria and for Decision-Making," International Series in Operations Research & Management Science, in: Multiple Criteria Decision Analysis: State of the Art Surveys, chapter 0, pages 345-405, Springer.
    12. Yildiz, B. & Bilbao, J.I. & Sproul, A.B., 2017. "A review and analysis of regression and machine learning models on commercial building electricity load forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1104-1122.
    13. Zhang, Yongli & Yang, Yuhong, 2015. "Cross-validation for selecting a model selection procedure," Journal of Econometrics, Elsevier, vol. 187(1), pages 95-112.
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