Micro-siting for Floating Wind Farms based on Two-phase Optimization

As offshore wind farm construction advances to distant and deep waters, research on micro-siting of floating wind turbines (FWTs) for such environments is urgent. Current micro-siting studies rely on a single FWT type and ignore platform displacement, which deviates from practical conditions. This paper generates wind scenarios and simulates the probability distribution of FWTs displacement and employs the Jensen wake model to characterize wake effects. A two-phase full-life-cycle optimization model is established: in the first phase, an uncertainty-based mixed-integer quadratic programming (MIQP) model is built to initially determine the positions and types of FWTs; in the second phase, the coordinates of FWTs are further optimized to maximize power generation. Case studies apply the model to multiple wind directions with multiple wind speeds scenarios and compare it with semi-submersible (Semi) platform-based wind farms, showing that layouts considering multiple floating platform types perform better.