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China has become the world second largest energy consumer, and IEA predicted that its primary energy demand will double from 2025 to 2030. Offshore wind power construction is difficult and carries high risk. It is extremely difficult to control the cost, of which the construction period is the biggest variable. As to meet the requirements of cost reduction and efficiency increase in the coming era of flat rate, the construction procedures, primary vessels, and equipment need to be properly planned prior to the project startup. For this purpose, an algorithm based on Mixed Integer Linear Programming (MILP) for accurately calculating weather window and construction efficiency of offshore wind power was firstly proposed in this study, which comprehensively takes the complex construction procedures, duration of each link and environmental restrictions into account. Focusing on the offshore seas of Fujian province, utilizing the 1-hour hindcast wind and wave data respectively from the validated reanalysis wind field and SWAN model with a time span of 25 years (1996–2020), the weather window and construction efficiency for monopile foundation construction and offshore wind turbine installation were evaluated both on spatial and temporal scope. With respects to the specific wind farms that will be constructed, the detailed analysis and construction suggestions were provided.

To ensure acceptable operation and/or survival of floating structures in extreme conditions, nonlinear time-domain simulations are often used to predict the structural response at the design stage. An environmental contour (EC) is commonly employed to identify critical sea states that serve as input for numerical simulations to assess the safety and performance of marine structures. In many studies, marginal and conditional distributions are defined to construct bivariate joint probability distributions for variables such as significant wave height and zero-crossing period; then, environmental contours can be constructed using the inverse first-order reliability method (IFORM). This study adopts alternative models to describe the generalized dependence structure between the environmental variables using copulas; the Nataf transformation is also discussed as a special case. Environmental contours are constructed, making use of measured wave data from moored buoys. Derived design loads are applied on a semi-submersible platform to assess possible differences. In addition, the long-term extremes of the tension of the mooring lines are estimated, considering uncertainties in the structural response using a 3D model (that includes response variability, ignored with the EC approach) to help establish more accurate design loads using Monte Carlo simulation. Results offer a clear indication of the extreme response of the floating structure based on the different models.