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.
关键词
海上风电 /
资源配置 /
策略优化 /
气象不定性 /
离散仿真
Key words
offshore wind power /
resource allocation /
strategy optimization /
meteorological uncertainty /
discrete simulation
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基金
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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