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[11] 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.
[12] 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.
[13] 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.
[14] 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.
LIN Y K, DENG S J, YANG K P, et al.Development status and suggestions for China’s offshore engineering equipment manufacturing industry[J]. China offshore oil and gas, 2024, 36(4): 190-198.
[15] 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.
[16] 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.
DU J Q, LI M S, FU X J, et al.Construction cost trend analysis of offshore wind power and investment suggestions of petrochemical industry[J]. Engineering cost management, 2022, 33(6): 85-91.)
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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
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潘国兵, 徐源, 何蓉蓉, 楚文楷, 林子义, 祁廉臻
太阳能学报 | 2026,47(6): 354-360
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太阳能学报 2026 , 47 (6) : 354 -360
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
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潘国兵, 徐源, 何蓉蓉, 楚文楷, 林子义, 祁廉臻
作者信息
MULTI-OBJECTIVE RESOURCE CONFIGURATION STRATEGY OPTIMIZATION FOR OFFSHORE WIND FARM CONSTRUCTION CONSIDERING METEOROLOGICAL UNCERTAINTY
Pan Guobing, Xu Yuan, He Rongrong, Chu Wenkai, Lin Ziyi, Qi Lianzhen
Affiliations
    1. Institute of Distributed Energy and Microgrid, Zhejiang University of Technology, Hangzhou 310014, China;
    2. PowerChina Huadong Engineering Corporation Limited, Hangzhou 311122, China
doi: 10.19912/j.0254-0096.tynxb.2025-0119
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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。
海上风电  /  资源配置  /  策略优化  /  气象不定性  /  离散仿真
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.
offshore wind power  /  resource allocation  /  strategy optimization  /  meteorological uncertainty  /  discrete simulation
潘国兵, 徐源, 何蓉蓉, 楚文楷, 林子义, 祁廉臻. 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 , 47 (6) : 354 -360 . DOI: 10.19912/j.0254-0096.tynxb.2025-0119
Pan Guobing, Xu Yuan, He Rongrong, Chu Wenkai, Lin Ziyi, Qi Lianzhen. MULTI-OBJECTIVE RESOURCE CONFIGURATION STRATEGY OPTIMIZATION FOR OFFSHORE WIND FARM CONSTRUCTION CONSIDERING METEOROLOGICAL UNCERTAINTY[J]. Acta Energiae Solaris Sinica, 2026 , 47 (6) : 354 -360 . DOI: 10.19912/j.0254-0096.tynxb.2025-0119

    浙江省海洋产业科技项目深远海风电机组电能质量机/电机理研究与治理装置研制(2026HYC01012)

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[10] 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.
[11] 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.
[12] 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.
[13] 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.
[14] 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.
LIN Y K, DENG S J, YANG K P, et al.Development status and suggestions for China’s offshore engineering equipment manufacturing industry[J]. China offshore oil and gas, 2024, 36(4): 190-198.
[15] 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.
[16] 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.
DU J Q, LI M S, FU X J, et al.Construction cost trend analysis of offshore wind power and investment suggestions of petrochemical industry[J]. Engineering cost management, 2022, 33(6): 85-91.
2026年第47卷第6期
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doi: 10.19912/j.0254-0096.tynxb.2025-0119
  • 接收时间:2025-01-20
  • 首发时间:2026-07-17
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
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