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Multi-objective turbine allocation on a wind farm site

Author

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  • Dinçer, A.E.
  • Demir, A.
  • Yılmaz, K.

Abstract

The Multi-Objective Turbine Allocation (MOTA) method is introduced as a novel approach for wind farm layout optimization and site selection. By incorporating Geographic Information System (GIS) tools and the Analytical Hierarchy Process (AHP), the MOTA method offers a comprehensive solution to balance energy production, cost factors, and environmental impacts. In this study, the MOTA method is applied to Gökçeada, Türkiye, for wind farm development. Results show that the MOTA method effectively proposes the optimum wind farm layout by selecting the best site for each turbine. The sequential turbine allocation approach, integration of multiple objectives, and use of GIS tools and AHP are the key capabilities and novelties of the MOTA method. The method allows for flexible investment decisions, considering technical and economic aspects. The outcomes from the Gökçeada case study highlight the effectiveness of the MOTA method in maximizing energy production while considering cost factors and environmental impacts. The results indicate that for the selected objective functions, the optimal net profit is attained with the installation of 155 turbines on Gökçeada. The MOTA method presents a practical and efficient solution for wind farm development, contributing to sustainable and efficient renewable energy generation.

Suggested Citation

  • Dinçer, A.E. & Demir, A. & Yılmaz, K., 2024. "Multi-objective turbine allocation on a wind farm site," Applied Energy, Elsevier, vol. 355(C).
  • Handle: RePEc:eee:appene:v:355:y:2024:i:c:s0306261923017105
    DOI: 10.1016/j.apenergy.2023.122346
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    References listed on IDEAS

    as
    1. Emami, Alireza & Noghreh, Pirooz, 2010. "New approach on optimization in placement of wind turbines within wind farm by genetic algorithms," Renewable Energy, Elsevier, vol. 35(7), pages 1559-1564.
    2. Pookpunt, Sittichoke & Ongsakul, Weerakorn, 2013. "Optimal placement of wind turbines within wind farm using binary particle swarm optimization with time-varying acceleration coefficients," Renewable Energy, Elsevier, vol. 55(C), pages 266-276.
    3. Long, Huan & Li, Peikun & Gu, Wei, 2020. "A data-driven evolutionary algorithm for wind farm layout optimization," Energy, Elsevier, vol. 208(C).
    4. Cao, Lichao & Ge, Mingwei & Gao, Xiaoxia & Du, Bowen & Li, Baoliang & Huang, Zhi & Liu, Yongqian, 2022. "Wind farm layout optimization to minimize the wake induced turbulence effect on wind turbines," Applied Energy, Elsevier, vol. 323(C).
    5. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2018. "Continuous adjoint formulation for wind farm layout optimization: A 2D implementation," Applied Energy, Elsevier, vol. 228(C), pages 2333-2345.
    6. Marmidis, Grigorios & Lazarou, Stavros & Pyrgioti, Eleftheria, 2008. "Optimal placement of wind turbines in a wind park using Monte Carlo simulation," Renewable Energy, Elsevier, vol. 33(7), pages 1455-1460.
    7. Shin, Dongheon & Ko, Kyungnam, 2022. "Experimental study on application of nacelle-mounted LiDAR for analyzing wind turbine wake effects by distance," Energy, Elsevier, vol. 243(C).
    8. Moreno, Sinvaldo Rodrigues & Pierezan, Juliano & Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2021. "Multi-objective lightning search algorithm applied to wind farm layout optimization," Energy, Elsevier, vol. 216(C).
    9. Hugo Díaz & Carlos Guedes Soares, 2021. "A Multi-Criteria Approach to Evaluate Floating Offshore Wind Farms Siting in the Canary Islands (Spain)," Energies, MDPI, vol. 14(4), pages 1-18, February.
    10. Yılmaz, Kutay & Dinçer, Ali Ersin & Ayhan, Elif N., 2023. "Exploring flood and erosion risk indices for optimal solar PV site selection and assessing the influence of topographic resolution," Renewable Energy, Elsevier, vol. 216(C).
    11. Yamani Douzi Sorkhabi, Sami & Romero, David A. & Yan, Gary Kai & Gu, Michelle Dao & Moran, Joaquin & Morgenroth, Michael & Amon, Cristina H., 2016. "The impact of land use constraints in multi-objective energy-noise wind farm layout optimization," Renewable Energy, Elsevier, vol. 85(C), pages 359-370.
    12. Guirguis, David & Romero, David A. & Amon, Cristina H., 2016. "Toward efficient optimization of wind farm layouts: Utilizing exact gradient information," Applied Energy, Elsevier, vol. 179(C), pages 110-123.
    13. Hossein Yousefi & Saheb Ghanbari Motlagh & Mohammad Montazeri, 2022. "Multi-Criteria Decision-Making System for Wind Farm Site-Selection Using Geographic Information System (GIS): Case Study of Semnan Province, Iran," Sustainability, MDPI, vol. 14(13), pages 1-27, June.
    14. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2016. "Optimization of wind turbine layout position in a wind farm using a newly-developed two-dimensional wake model," Applied Energy, Elsevier, vol. 174(C), pages 192-200.
    15. Park, Jinkyoo & Law, Kincho H., 2015. "Layout optimization for maximizing wind farm power production using sequential convex programming," Applied Energy, Elsevier, vol. 151(C), pages 320-334.
    16. Chowdhury, Souma & Zhang, Jie & Messac, Achille & Castillo, Luciano, 2013. "Optimizing the arrangement and the selection of turbines for wind farms subject to varying wind conditions," Renewable Energy, Elsevier, vol. 52(C), pages 273-282.
    17. González, Javier Serrano & Gonzalez Rodriguez, Angel G. & Mora, José Castro & Santos, Jesús Riquelme & Payan, Manuel Burgos, 2010. "Optimization of wind farm turbines layout using an evolutive algorithm," Renewable Energy, Elsevier, vol. 35(8), pages 1671-1681.
    18. Hou, Peng & Hu, Weihao & Soltani, Mohsen & Chen, Cong & Chen, Zhe, 2017. "Combined optimization for offshore wind turbine micro siting," Applied Energy, Elsevier, vol. 189(C), pages 271-282.
    19. Grady, S.A. & Hussaini, M.Y. & Abdullah, M.M., 2005. "Placement of wind turbines using genetic algorithms," Renewable Energy, Elsevier, vol. 30(2), pages 259-270.
    20. Turner, S.D.O. & Romero, D.A. & Zhang, P.Y. & Amon, C.H. & Chan, T.C.Y., 2014. "A new mathematical programming approach to optimize wind farm layouts," Renewable Energy, Elsevier, vol. 63(C), pages 674-680.
    21. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2020. "Optimal design of wind farms in complex terrains using computational fluid dynamics and adjoint methods," Applied Energy, Elsevier, vol. 261(C).
    22. Jun, Dong & Tian-tian, Feng & Yi-sheng, Yang & Yu, Ma, 2014. "Macro-site selection of wind/solar hybrid power station based on ELECTRE-II," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 194-204.
    23. Kusiak, Andrew & Song, Zhe, 2010. "Design of wind farm layout for maximum wind energy capture," Renewable Energy, Elsevier, vol. 35(3), pages 685-694.
    24. Nicolas Kirchner-Bossi & Fernando Porté-Agel, 2021. "Wind Farm Area Shape Optimization Using Newly Developed Multi-Objective Evolutionary Algorithms," Energies, MDPI, vol. 14(14), pages 1-25, July.
    25. Parada, Leandro & Herrera, Carlos & Flores, Paulo & Parada, Victor, 2017. "Wind farm layout optimization using a Gaussian-based wake model," Renewable Energy, Elsevier, vol. 107(C), pages 531-541.
    26. Adaramola, M.S. & Krogstad, P.-Å., 2011. "Experimental investigation of wake effects on wind turbine performance," Renewable Energy, Elsevier, vol. 36(8), pages 2078-2086.
    27. Dimitra G. Vagiona & Manos Kamilakis, 2018. "Sustainable Site Selection for Offshore Wind Farms in the South Aegean—Greece," Sustainability, MDPI, vol. 10(3), pages 1-18, March.
    28. Song, Zhe & Zhang, Zijun & Chen, Xingying, 2016. "The decision model of 3-dimensional wind farm layout design," Renewable Energy, Elsevier, vol. 85(C), pages 248-258.
    29. Nicolas Kirchner-Bossi & Fernando Porté-Agel, 2018. "Realistic Wind Farm Layout Optimization through Genetic Algorithms Using a Gaussian Wake Model," Energies, MDPI, vol. 11(12), pages 1-26, November.
    30. Li, Wenwen & Özcan, Ender & John, Robert, 2017. "Multi-objective evolutionary algorithms and hyper-heuristics for wind farm layout optimisation," Renewable Energy, Elsevier, vol. 105(C), pages 473-482.
    31. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Determination of the Most Optimal On-Shore Wind Farm Site Location Using a GIS-MCDM Methodology: Evaluating the Case of South Korea," Energies, MDPI, vol. 10(12), pages 1-22, December.
    32. 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, Elsevier, vol. 228(C), pages 1853-1869.
    33. Kuo, Jim Y.J. & Romero, David A. & Amon, Cristina H., 2015. "A mechanistic semi-empirical wake interaction model for wind farm layout optimization," Energy, Elsevier, vol. 93(P2), pages 2157-2165.
    34. Kusiak, Andrew & Zheng, Haiyang, 2010. "Optimization of wind turbine energy and power factor with an evolutionary computation algorithm," Energy, Elsevier, vol. 35(3), pages 1324-1332.
    35. Yunna, Wu & Ruhang, Xu, 2013. "Current status, future potentials and challenges of renewable energy development in Gansu province (Northwest China)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 73-86.
    36. Song, Mengxuan & Wen, Yi & Duan, Bin & Wang, Jun & Gong, Qi, 2017. "Micro-siting optimization of a wind farm built in multiple phases," Energy, Elsevier, vol. 137(C), pages 95-103.
    37. Dou, Bingzheng & Guala, Michele & Lei, Liping & Zeng, Pan, 2019. "Experimental investigation of the performance and wake effect of a small-scale wind turbine in a wind tunnel," Energy, Elsevier, vol. 166(C), pages 819-833.
    38. Reddy, Sohail R., 2020. "Wind Farm Layout Optimization (WindFLO) : An advanced framework for fast wind farm analysis and optimization," Applied Energy, Elsevier, vol. 269(C).
    39. Tingey, Eric B. & Ning, Andrew, 2017. "Trading off sound pressure level and average power production for wind farm layout optimization," Renewable Energy, Elsevier, vol. 114(PB), pages 547-555.
    40. Chowdhury, Souma & Zhang, Jie & Messac, Achille & Castillo, Luciano, 2012. "Unrestricted wind farm layout optimization (UWFLO): Investigating key factors influencing the maximum power generation," Renewable Energy, Elsevier, vol. 38(1), pages 16-30.
    41. Yin, Peng-Yeng & Wu, Tsai-Hung & Hsu, Ping-Yi, 2017. "Risk management of wind farm micro-siting using an enhanced genetic algorithm with simulation optimization," Renewable Energy, Elsevier, vol. 107(C), pages 508-521.
    42. Sánchez-Lozano, J.M. & García-Cascales, M.S. & Lamata, M.T., 2016. "GIS-based onshore wind farm site selection using Fuzzy Multi-Criteria Decision Making methods. Evaluating the case of Southeastern Spain," Applied Energy, Elsevier, vol. 171(C), pages 86-102.
    43. DuPont, Bryony & Cagan, Jonathan & Moriarty, Patrick, 2016. "An advanced modeling system for optimization of wind farm layout and wind turbine sizing using a multi-level extended pattern search algorithm," Energy, Elsevier, vol. 106(C), pages 802-814.
    44. Song, M.X. & Chen, K. & Zhang, X. & Wang, J., 2015. "The lazy greedy algorithm for power optimization of wind turbine positioning on complex terrain," Energy, Elsevier, vol. 80(C), pages 567-574.
    45. Wagner, Markus & Day, Jareth & Neumann, Frank, 2013. "A fast and effective local search algorithm for optimizing the placement of wind turbines," Renewable Energy, Elsevier, vol. 51(C), pages 64-70.
    46. Chaouachi, Aymen & Covrig, Catalin Felix & Ardelean, Mircea, 2017. "Multi-criteria selection of offshore wind farms: Case study for the Baltic States," Energy Policy, Elsevier, vol. 103(C), pages 179-192.
    47. Ju, Xinglong & Liu, Feng, 2019. "Wind farm layout optimization using self-informed genetic algorithm with information guided exploitation," Applied Energy, Elsevier, vol. 248(C), pages 429-445.
    48. Baseer, M.A. & Rehman, S. & Meyer, J.P. & Alam, Md. Mahbub, 2017. "GIS-based site suitability analysis for wind farm development in Saudi Arabia," Energy, Elsevier, vol. 141(C), pages 1166-1176.
    49. Rahim Moltames & Mohammad Sajad Naghavi & Mahyar Silakhori & Younes Noorollahi & Hossein Yousefi & Mostafa Hajiaghaei-Keshteli & Behzad Azizimehr, 2022. "Multi-Criteria Decision Methods for Selecting a Wind Farm Site Using a Geographic Information System (GIS)," Sustainability, MDPI, vol. 14(22), pages 1-19, November.
    50. Mengran Li & Ye Xu & Junhong Guo & Ye Li & Wei Li, 2020. "Application of a GIS-Based Fuzzy Multi-Criteria Evaluation Approach for Wind Farm Site Selection in China," Energies, MDPI, vol. 13(10), pages 1-19, May.
    51. Kuo, Jim Y.J. & Romero, David A. & Beck, J. Christopher & Amon, Cristina H., 2016. "Wind farm layout optimization on complex terrains – Integrating a CFD wake model with mixed-integer programming," Applied Energy, Elsevier, vol. 178(C), pages 404-414.
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