This work develops and assesses static, closed-loop wind-farm flow-control strategies for load-constrained power optimization in a floating wind farm. Three farm-level strategies are considered: wake steering using turbine-specific nacelle-heading offsets, pitch-based induction control using discrete derating levels, and a hybrid yaw–induction strategy. A supervisory FLORIS engineering wake model computes the control setpoints by maximizing the predicted farm power. For induction and hybrid control, the power optimization is subject to a farm-level rotor-thrust constraint, which is used as an aerodynamic load-related proxy. The optimized setpoints are applied to a coupled FAST.Farm aero-hydro-servo-elastic model through independent ROSCO turbine controllers and a ZeroMQ communication interface. The resulting farm power, rotor thrust, structural loads, mooring loads, and spectral responses are then evaluated from the FAST.Farm simulations.</p> <p>The investigated farm consists of four IEA 15 MW reference wind turbines mounted on UMaine VolturnUS-S semi-submersible platforms. The strategies are tested under below-rated turbulent wind conditions and compared against greedy operation, in which each turbine independently follows its maximum-power-point control strategy. The FLORIS model is calibrated against FAST.Farm response data using turbine power and thrust lookup tables for the considered derating levels together with wake-model parameter tuning.</p> <p>The results show that all three strategies increase mean farm power relative to greedy operation, but with distinct power–load trade-offs. Within the investigated simulation matrix, hybrid control provides FAST.Farm-predicted farm-power gains ranging from 8.7 % to 19 %. Wake steering generally increases yaw-bearing damage-equivalent loads, whereas induction and hybrid control reduce yaw-bearing DELs and, to a lesser extent, blade-root moment DELs for most investigated conditions. Tower-base moment and fairlead-tension responses are less systematic and depend strongly on wind direction and coupled floating-platform–mooring dynamics. For the representative <em>U</em> = 9 m s<sup>-1</sup>, <em>WD</em> = -5° condition, spectral analysis shows that the controller-induced changes are concentrated in the rotor-harmonic and structural-frequency ranges and in the low-frequency platform–mooring region. Overall, the results demonstrate that load-constrained farm-power optimization can provide substantial power gains in floating wind farms, but that an aggregate rotor-thrust constraint alone does not prevent operating-condition-dependent structural and mooring-load penalties.