计及气象不确定性的海上风电场建设多目标资源配置策略优化

潘国兵; 徐源; 何蓉蓉; 楚文楷; 林子义; 祁廉臻

doi:10.19912/j.0254-0096.tynxb.2025-0119

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计及气象不确定性的海上风电场建设多目标资源配置策略优化

更新时间：2026-07-22

- 计及气象不确定性的海上风电场建设多目标资源配置策略优化
- 计及气象不确定性的海上风电场建设多目标资源配置策略优化
- 太阳能学报 2026年47卷第6期页码：354-360
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- DOI：10.19912/j.0254-0096.tynxb.2025-0119
  中图分类号： TK89
- 网络首发：2026-07-08，
  
  纸质出版：2026
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潘国兵, 徐源, 何蓉蓉, 等. 计及气象不确定性的海上风电场建设多目标资源配置策略优化[J]. 太阳能学报, 2026,47(6):354-360.

潘国兵, 徐源, 何蓉蓉, et al. 计及气象不确定性的海上风电场建设多目标资源配置策略优化[J]. 2026, 47(6): 354-360.
潘国兵, 徐源, 何蓉蓉, 等. 计及气象不确定性的海上风电场建设多目标资源配置策略优化[J]. 太阳能学报, 2026,47(6):354-360. DOI： 10.19912/j.0254-0096.tynxb.2025-0119.

潘国兵, 徐源, 何蓉蓉, et al. 计及气象不确定性的海上风电场建设多目标资源配置策略优化[J]. 2026, 47(6): 354-360. DOI： 10.19912/j.0254-0096.tynxb.2025-0119.

摘要

为改善海上风电传统资源配置的局限性

分析了基于气象不确定性的海上风电场建设资源配置策略优化的流程

提出涵盖最小工作时长、资源配置优化率、窗口期利用率、成本效益比值等的多目标的策略优化指标;建立基于离散数字仿真平台的海上风电资源配置优化模型

统计各项优化指标

评估海上风电建设配置资源优化效益。以老挝孟松风电项目为算例进行仿真

仿真结果表明所建立的资源配置策略优化模型可模拟海上风电场施工流程

显示气象、风电机组、人员等的实时状态

并较为准确地推算出最小工作时长、资源配置优化率、窗口期利用率及成本效益比值关键指标

有效优化了风电场安装时的资源配置

提高了海上风电场的施工效率

为海上风电场项目施工提供前期规划

实现降本增效的目的。

Abstract

To address the limitations of traditional resource allocation methods

this study analyzes the process of optimizing resource allocation strategies for offshore wind farm construction under meteorological uncertainty. A multi-objective optimization framework is proposed

incorporating four key performance indicators： minimum total working time

resource allocation optimization rate

window period utilization rate

and cost-benefit ratio. A discrete-event digital simulation-based optimization model is developed to support this framework

enabling systematic evaluation of the benefits of resource allocation strategies through statistical analysis of these indicators.The Laotian Monsoon Wind Power Project is selected as a case study for simulation. Results demonstrate that the established model can effectively simulate the entire construction process of offshore wind farms

providing real-time visualization of meteorological conditions

wind turbine unit statuses

and personnel dynamics. It also accurately quantifies critical metrics including minimum working time

resource allocation optimization rate

window period utilization rate

and cost-benefit ratio. The model also to significantly enhances resource allocation during wind farm installation

improves overall construction efficiency

and provides valuable pre-construction planning support. These outcomes collectively contribute to achieving the dual goals of cost reduction and efficiency improvement in offshore wind farm development.

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references

刘展志, 王诗超, 郝为瀚, 等. 大规模海上风电集中送出建设模式研究[J]. 南方能源建设, 2023, 10(1): 13-20.

马宇轩, 闵烨, 闫中杰, 等. 基于离散数值分析技术的海上风电机组安装施工规划模拟研究[J]. 太阳能学报, 2024, 45(6): 673-679.

WU Y N, HU Y, LIN X S, et al.Identifying and analyzing barriers to offshore wind power development in China using the grey decision-making trial and evaluation laboratory approach[J]. Journal of cleaner production, 2018, 189: 853-863.

URSAVAS E.A benders decomposition approach for solving the offshore wind farm installation planning at the North Sea[J]. European journal of operational research, 2017, 258(2): 703-714.

WEI Y Z, ZOU Q P, LIN X H.Evolution of price policy for offshore wind energy in China: trilemma of capacity, price and subsidy[J]. Renewable and sustainable energy reviews, 2021, 136: 110366.

TYAPIN I, HOVLAND G, JORDE J.Comparison of Markov theory and Monte Carlo simulations for analysis of marine operations related to installation of an offshore wind turbine[C]//24th International Congress on Condition Monitoring (COMADEM). Stavanger, Norway, 2011.

TEZCANER ÖZTÜRK D, BARLOW E, AKARTUNALI K, et al. Robust rolling horizon optimisation model for offshore wind farm installation logistics[R]. Glasgow: University of Strathclyde, 2017.

MORANDEAU M, WALKER R T, ARGALL R, et al.Optimisation of marine energy installation operations[J]. International journal of marine energy, 2013, 3: 14-26.

SCHOLZ-REITER B, LÜTJEN M, HEGER J, et al. Planning and control of logistics for offshore wind farms[C]//Proceedings of the 12th WSEAS International Conference on Mathematical and Computational Methods in Science and Engineering. Faro, Portugal, 2010: 242-247.

AIT-ALLA A, QUANDT M, LÜTJEN M. Simulation-based aggregate installation planning of offshore wind farms[C]//Proceedings of the 12th WSEAS International Conference on Mathematical and Computational Methods in Science and Engineering (MACMESE’10). Faro: WSEAS Press, 2010: 242-247.

GOPALAN ACHARY VENKITACHALAM G. Modelling the installation of offshore wind farms: defining the installation of offshore wind submarine power cables using a discrete event simulation based logistics model[D]. Delft: Delft University of Technology, 2020.

WU M N, GAO Z, ZHAO Y N.Assessment of allowable sea states for offshore wind turbine blade installation using time-domain numerical models and considering weather forecast uncertainty[J]. Ocean engineering, 2022, 260: 111801.

TEOTÓNIO C, FORTES P, ROEBELING P, et al. Assessing the impacts of climate change on hydropower generation and the power sector in Portugal: a partial equilibrium approach[J]. Renewable and sustainable energy reviews, 2017, 74: 788-799.

林益楷, 邓双军, 杨昆鹏, 等. 中国海洋工程装备制造产业发展现状及建议[J]. 中国海上油气, 2024, 36(4): 190-198.

YANG Z H, LIN Y F, DONG S.Weather window and efficiency assessment of offshore wind power construction in China adjacent seas using the calibrated SWAN model[J]. Ocean engineering, 2022, 259: 111933.

杜剑强, 李木盛, 付小军, 等. 海上风电建设成本趋势分析及石化行业投资建议[J]. 工程造价管理, 2022, 33(6): 85-91.

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