INVESTIGATION OF OFFSHORE-WIND-FARM LAYOUT OPTIMIZATION UNDER GEOMETRICAL CONSTRAINTS

被引：0

作者：

Zhang Z. ^{[1
]}

Guo N. ^{[2
]}

Yi K. ^{[1
]}

Li J. ^{[3
]}

Mu J. ^{[4
]}

机构：

[1] Science and Technology Research Institute, China Three Gorges Corporation, Beijing

[2] Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing

[3] Shanghai Investigation, Design and Research Institute Co.，Ltd., Shanghai

[4] China Three Gorges Renewables（Group）Co.，Ltd., Beijing

来源：

Taiyangneng Xuebao/Acta Energiae Solaris Sinica | 2023年 / 44卷 / 02期

关键词：

differential evolution algorithm; geometrical constraint; layout; offshore wind farms; wind turbines;

D O I：

10.19912/j.0254-0096.tynxb.2021-1079

中图分类号：

学科分类号：

摘要：

Considering the actual engineering requirements，this paper proposes an intelligent offshore-wind-farm layout optimization approach under geometrical constraints. The proposed approach adopts the Gaussian wake model to calculate the velocity deficit，and maximizes the wind-farm annual energy production（AEP）with a differential evolution algorithm，which can meet various geometrical constraints in the offshore-wind-farm layout optimization. Then this approach is used to optimize the wind turbine layout for a practical offshore wind farm under 3-，4-，7-rows geometrical constraints. The optimized results indicate that compared with the original layout scheme，the layout optimization scheme can increase the AEP of the wind farm by 2.13%-2.64% when considering the increase of cable laying cost. Further analysis suggests that the setup of potential solution number should consider the difficulty of getting the optimized result for this intelligent method. © 2023 Science Press. All rights reserved.

引用

页码：116 / 122

页数：6

共 19 条

[1] SHAMSODDIN S., Wind-turbine and wind-farm flows：a review［J］, Boundary-layer meteorology, 174, 1, pp. 1-59, (2020)
[2] CHENG Y, ZHANG M M，, ZHANG Z L，, Et al., A new analytical model for wind turbine wakes based on Monin-Obukhov similarity theory［J］, Applied energy, 239, pp. 96-106, (2019)
[3] GAO X X，, WANG T Y，, LI B B，, Et al., Investigation of wind turbine performance coupling wake and topography effects based on LiDAR measurements and SCADA data ［J］, Applied energy, 255, (2019)
[4] HERBERT-ACERO J F, RETHORE P E，, Et al., A review of methodological approaches for the design and optimization of wind farms［J］, Energies, 7, 11, pp. 6930-7016, (2014)
[5] GONZALEZ J S, SANTOS J M R，, Et al., A review and recent developments in the optimal wind-turbine micro-siting problem［J］, Renewable and sustainable energy reviews, 30, pp. 133-144, (2014)
[6] YANG X S，, ZHAO N, TIAN L L，, Et al., Influence of atmospheric stability on layout optimization based on Park-Gauss model［J］, Acta energiae solaris sinica, 42, 3, pp. 43-47, (2021)
[7] DIVIACCO B., Optimization of wind turbine positioning in large windfarms by means of a genetic algorithm［J］, Journal of wind engineering and industrial aerodynamics, 51, 1, pp. 105-116, (1994)
[8] MITTAL A., Optimization of the layout of large wind farms using a genetic algorithm［D］, (2010)
[9] GRADY S A，, HUSSAINI M Y，, ABDULLAH M M., Placement of wind turbines using genetic algorithms［J］, Renewable energy, 30, 2, pp. 259-270, (2005)
[10] GUO N Z, ZHANG M M，, LI B，, Et al., Influence of atmospheric stability on wind farm layout optimization based on an improved Gaussian wake model［J］, Journal of wind engineering and industrial aerodynamics, 211, (2021)

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