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