IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v189y2019ics0360544219318444.html
   My bibliography  Save this article

Optimizing wind farm layout by addressing energy-variance trade-off: A single-objective optimization approach

Author

Listed:
  • Wang, Longyan
  • Zuo, Ming J.
  • Xu, Jian
  • Zhou, Yunkai
  • Tan, Andy C.

Abstract

Wind farm layout optimization results depend on the optimization objectives, such as power output and variance. This paper investigates an alternative strategy for wind farm layout optimization by trading off the mean wind power output and power variance. Two optimization schemes, the weighted optimization and confidence interval optimization are compared in term of their performances on trading off energy-variance. For the weighted optimization, the objective function weight value α varies from 0 to 1 (implying the optimization objective shifts its weight from the power variance to the power output), while for the confidence interval (CI) optimization, either the lower or the upper limit of power output CI is maximized/minimized. It is found that the CI maximization achieves a trade-off of mean power output and power variance similar to the weighted optimization with α≥0.6, and the same individual power output range (192 kW–207 kW) is obtained with staggered placements of wind turbines. The CI minimization obtains a trade-off of average power output and power variance close to the weighted optimization with α≤0.4, and the optimal wind turbine locations are aligned. The advantage of CI optimization lies on its capability of predicting the power output uncertainty.

Suggested Citation

  • Wang, Longyan & Zuo, Ming J. & Xu, Jian & Zhou, Yunkai & Tan, Andy C., 2019. "Optimizing wind farm layout by addressing energy-variance trade-off: A single-objective optimization approach," Energy, Elsevier, vol. 189(C).
    • Handle: RePEc:eee:energy:v:189:y:2019:i:c:s0360544219318444
    DOI: 10.1016/j.energy.2019.116149
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219318444
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.116149?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Longyan & Tan, Andy C.C. & Gu, Yuantong & Yuan, Jianping, 2015. "A new constraint handling method for wind farm layout optimization with lands owned by different owners," Renewable Energy, Elsevier, vol. 83(C), pages 151-161.
    2. Martínez, E. & Latorre-Biel, J.I. & Jiménez, E. & Sanz, F. & Blanco, J., 2018. "Life cycle assessment of a wind farm repowering process," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 260-271.
    3. Shakoor, Rabia & Hassan, Mohammad Yusri & Raheem, Abdur & Rasheed, Nadia, 2016. "Wind farm layout optimization using area dimensions and definite point selection techniques," Renewable Energy, Elsevier, vol. 88(C), pages 154-163.
    4. 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.
    5. Wang, Longyan & Tan, Andy C.C. & Cholette, Michael E. & Gu, Yuantong, 2017. "Optimization of wind farm layout with complex land divisions," Renewable Energy, Elsevier, vol. 105(C), pages 30-40.
    6. 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.
    7. Wilson, Dennis & Rodrigues, Silvio & Segura, Carlos & Loshchilov, Ilya & Hutter, Frank & Buenfil, Guillermo López & Kheiri, Ahmed & Keedwell, Ed & Ocampo-Pineda, Mario & Özcan, Ender & Peña, Sergio Iv, 2018. "Evolutionary computation for wind farm layout optimization," Renewable Energy, Elsevier, vol. 126(C), pages 681-691.
    8. Kusiak, Andrew & Song, Zhe, 2010. "Design of wind farm layout for maximum wind energy capture," Renewable Energy, Elsevier, vol. 35(3), pages 685-694.
    9. 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.
    10. Dai, Hancheng & Xie, Xuxuan & Xie, Yang & Liu, Jian & Masui, Toshihiko, 2016. "Green growth: The economic impacts of large-scale renewable energy development in China," Applied Energy, Elsevier, vol. 162(C), pages 435-449.
    11. Ju Feng & Wen Zhong Shen, 2015. "Modelling Wind for Wind Farm Layout Optimization Using Joint Distribution of Wind Speed and Wind Direction," Energies, MDPI, vol. 8(4), pages 1-18, April.
    12. Abdelsalam, Ali M. & El-Shorbagy, M.A., 2018. "Optimization of wind turbines siting in a wind farm using genetic algorithm based local search," Renewable Energy, Elsevier, vol. 123(C), pages 748-755.
    13. Wang, Longyan & Cholette, Michael E. & Zhou, Yunkai & Yuan, Jianping & Tan, Andy C.C. & Gu, Yuantong, 2018. "Effectiveness of optimized control strategy and different hub height turbines on a real wind farm optimization," Renewable Energy, Elsevier, vol. 126(C), pages 819-829.
    14. Hosseini, Seyed Ehsan & Wahid, Mazlan Abdul, 2016. "Hydrogen production from renewable and sustainable energy resources: Promising green energy carrier for clean development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 850-866.
    15. Imholte, D.D. & Nguyen, R.T. & Vedantam, A. & Brown, M. & Iyer, A. & Smith, B.J. & Collins, J.W. & Anderson, C.G. & O’Kelley, B., 2018. "An assessment of U.S. rare earth availability for supporting U.S. wind energy growth targets," Energy Policy, Elsevier, vol. 113(C), pages 294-305.
    16. MirHassani, S.A. & Yarahmadi, A., 2017. "Wind farm layout optimization under uncertainty," Renewable Energy, Elsevier, vol. 107(C), pages 288-297.
    17. Katzenstein, Warren & Apt, Jay, 2012. "The cost of wind power variability," Energy Policy, Elsevier, vol. 51(C), pages 233-243.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yasemin Ayaz Atalan & Mete Tayanç & Kamil Erkan & Abdulkadir Atalan, 2020. "Development of Nonlinear Optimization Models for Wind Power Plants Using Box-Behnken Design of Experiment: A Case Study for Turkey," Sustainability, MDPI, vol. 12(15), pages 1-17, July.
    2. Froese, Gabrielle & Ku, Shan Yu & Kheirabadi, Ali C. & Nagamune, Ryozo, 2022. "Optimal layout design of floating offshore wind farms," Renewable Energy, Elsevier, vol. 190(C), pages 94-102.
    3. Wu, Yunna & Liao, Mingjuan & Hu, Mengyao & Lin, Jiawei & Zhou, Jianli & Zhang, Buyuan & Xu, Chuanbo, 2020. "A decision framework of low-speed wind farm projects in hilly areas based on DEMATEL-entropy-TODIM method from the sustainability perspective: A case in China," Energy, Elsevier, vol. 213(C).
    4. Petrović, A. & Đurišić, Ž., 2021. "Genetic algorithm based optimized model for the selection of wind turbine for any site-specific wind conditions," Energy, Elsevier, vol. 236(C).
    5. Jian Xu & Longyan Wang & Stephen Ntiri Asomani & Wei Luo & Rong Lu, 2020. "Improvement of Internal Flow Performance of a Centrifugal Pump-As-Turbine (PAT) by Impeller Geometric Optimization," Mathematics, MDPI, vol. 8(10), pages 1-23, October.
    6. Azlan, F. & Kurnia, J.C. & Tan, B.T. & Ismadi, M.-Z., 2021. "Review on optimisation methods of wind farm array under three classical wind condition problems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    7. Wang, Longyan & Luo, Wei & Xu, Jian & Xie, Junhang & Luo, Zhaohui & Tan, Andy C.C., 2022. "Comparative study of decentralized instantaneous and wind-interval-based controls for in-line two scale wind turbines," Renewable Energy, Elsevier, vol. 189(C), pages 1218-1233.
    8. Masoudi, Seiied Mohsen & Baneshi, Mehdi, 2022. "Layout optimization of a wind farm considering grids of various resolutions, wake effect, and realistic wind speed and wind direction data: A techno-economic assessment," Energy, Elsevier, vol. 244(PB).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wu, Yan & Zhang, Shuai & Wang, Ruiqi & Wang, Yufei & Feng, Xiao, 2020. "A design methodology for wind farm layout considering cable routing and economic benefit based on genetic algorithm and GeoSteiner," Renewable Energy, Elsevier, vol. 146(C), pages 687-698.
    2. Azlan, F. & Kurnia, J.C. & Tan, B.T. & Ismadi, M.-Z., 2021. "Review on optimisation methods of wind farm array under three classical wind condition problems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    3. 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.
    4. Parada, Leandro & Herrera, Carlos & Flores, Paulo & Parada, Victor, 2018. "Assessing the energy benefit of using a wind turbine micro-siting model," Renewable Energy, Elsevier, vol. 118(C), pages 591-601.
    5. Kyoungboo Yang & Kyungho Cho, 2019. "Simulated Annealing Algorithm for Wind Farm Layout Optimization: A Benchmark Study," Energies, MDPI, vol. 12(23), pages 1-15, November.
    6. Yang, Kyoungboo & Kwak, Gyeongil & Cho, Kyungho & Huh, Jongchul, 2019. "Wind farm layout optimization for wake effect uniformity," Energy, Elsevier, vol. 183(C), pages 983-995.
    7. 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).
    8. Dhunny, A.Z. & Timmons, D.S. & Allam, Z. & Lollchund, M.R. & Cunden, T.S.M., 2020. "An economic assessment of near-shore wind farm development using a weather research forecast-based genetic algorithm model," Energy, Elsevier, vol. 201(C).
    9. Houssem R. E. H. Bouchekara & Yusuf A. Sha’aban & Mohammad S. Shahriar & Makbul A. M. Ramli & Abdullahi A. Mas’ud, 2023. "Wind Farm Layout Optimization/Expansion with Real Wind Turbines Using a Multi-Objective EA Based on an Enhanced Inverted Generational Distance Metric Combined with the Two-Archive Algorithm 2," Sustainability, MDPI, vol. 15(3), pages 1-32, January.
    10. 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.
    11. Masoudi, Seiied Mohsen & Baneshi, Mehdi, 2022. "Layout optimization of a wind farm considering grids of various resolutions, wake effect, and realistic wind speed and wind direction data: A techno-economic assessment," Energy, Elsevier, vol. 244(PB).
    12. Wang, Longyan & Cholette, Michael E. & Tan, Andy C.C. & Gu, Yuantong, 2017. "A computationally-efficient layout optimization method for real wind farms considering altitude variations," Energy, Elsevier, vol. 132(C), pages 147-159.
    13. Reddy, Sohail R., 2021. "A machine learning approach for modeling irregular regions with multiple owners in wind farm layout design," Energy, Elsevier, vol. 220(C).
    14. Lo Brutto, Ottavio A. & Nguyen, Van Thinh & Guillou, Sylvain S. & Thiébot, Jérôme & Gualous, Hamid, 2016. "Tidal farm analysis using an analytical model for the flow velocity prediction in the wake of a tidal turbine with small diameter to depth ratio," Renewable Energy, Elsevier, vol. 99(C), pages 347-359.
    15. Siyu Tao & Andrés Feijóo & Jiemin Zhou & Gang Zheng, 2020. "Topology Design of an Offshore Wind Farm with Multiple Types of Wind Turbines in a Circular Layout," Energies, MDPI, vol. 13(3), pages 1-16, January.
    16. Yin, Peng-Yeng & Wu, Tsai-Hung & Hsu, Ping-Yi, 2017. "Simulation based risk management for multi-objective optimal wind turbine placement using MOEA/D," Energy, Elsevier, vol. 141(C), pages 579-597.
    17. Guirguis, David & Romero, David A. & Amon, Cristina H., 2017. "Gradient-based multidisciplinary design of wind farms with continuous-variable formulations," Applied Energy, Elsevier, vol. 197(C), pages 279-291.
    18. Yamani Douzi Sorkhabi, Sami & Romero, David A. & Beck, J. Christopher & Amon, Cristina H., 2018. "Constrained multi-objective wind farm layout optimization: Novel constraint handling approach based on constraint programming," Renewable Energy, Elsevier, vol. 126(C), pages 341-353.
    19. Tao, Siyu & Xu, Qingshan & Feijóo, Andrés & Zheng, Gang & Zhou, Jiemin, 2020. "Wind farm layout optimization with a three-dimensional Gaussian wake model," Renewable Energy, Elsevier, vol. 159(C), pages 553-569.
    20. Muhammad Nabeel Hussain & Nadeem Shaukat & Ammar Ahmad & Muhammad Abid & Abrar Hashmi & Zohreh Rajabi & Muhammad Atiq Ur Rehman Tariq, 2022. "Micro-Siting of Wind Turbines in an Optimal Wind Farm Area Using Teaching–Learning-Based Optimization Technique," Sustainability, MDPI, vol. 14(14), pages 1-24, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:189:y:2019:i:c:s0360544219318444. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.