There is more wind with less turbulence offshore compared with an onshore case, which drives the development of the offshore wind farm worldwide. Since a huge amount of money is required for constructing an offshore wind farm, many types of research have been done on the optimization of the offshore wind farm with the purpose of either minimizing the cost of energy or maximizing the total energy production. There are several factors that have an impact on the performance of the wind farm, mainly energy production of wind farm which is highly decided by the wind condition of construction area and micro-siting of wind turbines (WTs), as well as initial investment which is influenced by both the placement of WTs and the electrical system design, especially the scheme of cable connection layout. In this paper, a review of the state-of-art researches related to the wind farm layout optimization as well as electrical system design including cable connection scheme optimization is presented. The most significant factors that should be considered in the offshore wind farm optimization work is highlighted after reviewing the latest works, and the future needs have been specified.

Doubly fed induction generators (DFIG) find extensive application in variable-speed wind power plants, providing notable advantages such as cost-effectiveness, operational flexibility across varying speeds, and enhanced power quality. This research focuses on the control of DFIGs employed in variable-speed wind turbine configurations. A suitable mathematical model is chosen for representative systems following a comprehensive review of contemporary research. Subsequent analysis reveals the instability of the open-loop time response of the system. To address this instability, the initial approach involves the implementation of the conventional model predictive controller (MPC). However, the outcomes indicate that this controller falls short of delivering satisfactory performance despite the enhanced stability. In the subsequent phase, efforts are made to mitigate the impact of wind input variability by utilizing the Kalman filter, given its effectiveness in handling high variability. Following this, a novel methodology is introduced, which combines nonlinear MPC with the Lyapunov function. This method is based on the nonlinear model of the system. By using the Lyapunov function in the nonlinear MPC structure, the stability of the designed controller is guaranteed. To validate the proposed control approach, the results are compared with PID based controller in MATLAB/Simulink. The simulation results showed that the output variables of the modeled DFIG system achieve stability within a reasonable timeframe applying the input.

Inter-Turn Short Circuit (ITSC) fault in stator winding is a common fault in Doubly-Fed Induction Generator (DFIG)-based Wind Turbines (WTs). Improper measures in the ITSC fault affect the safety of the faulty WT and the power output of the Wind Farm (WF). This paper combines derating WTs and the power optimization of the WF to diminish the fault effect. At the turbine level, switching the derating strategy and the ITSC Fault Ride-Through (FRT) strategy is adopted to ensure that WTs safely operate under fault. At the farm level, the Particle Swarm Optimization (PSO)-based active power dispatch strategy is used to address proper power references in all of the WTs. The simulation results demonstrate the effectiveness of the proposed method. Switching the derating strategy can increase the power limit of the faulty WT, and the ITSC FRT strategy can ensure that the WT operates without excessive faulty current. The PSO-based power optimization can improve the power of the WF to compensate for the power loss caused by the faulty WT. With the proposed method, the competitiveness and the operational capacity of offshore WFs can be upgraded.

Inter‐turn short‐circuit fault of the stator winding is one of the most common faults of asynchronous generators and often found in doubly‐fed wind turbines. The improper treatment methods will lead to unnecessary power loss or further damage to the insulation layer. To solve this problem, an optimal power dispatch strategy (OPDS) is proposed which combines the control at the turbine level and the optimisation at the farm level. At the turbine level, the faulty turbine is down‐regulated based on the principle that the fault current does not exceed the rated current. At the farm level, particle swarm optimisation is used to optimise the power references considering wake effects to compensate for the power loss caused by the downregulated turbine. The effectiveness of OPDS is illustrated by comparing with two usually used strategies, one takes proportional dispatch strategy (PDS) and directly shuts down the faulty turbine, the other takes PDS but ignores the fault. The results show that OPDS can minimise power loss under the premise of protecting the faulty turbine. The study contributes to reduce the maintenance costs of wind farms and improve the operational capability of the wind turbine under fault conditions.

The aerodynamic performance of wind turbine airfoils is crucial for the efficiency and reliability of wind energy systems, with leading-edge roughness significantly impacting blade performance. This study conducts numerical simulations on the DU 00-W-401 airfoil to investigate the effects of leading-edge roughness. Results reveal that the rough airfoil exhibits a distinctive “N”-shaped lift coefficient curve. The formation mechanism of this nonlinear lift curve is primarily attributed to the development of the trailing-edge separation vortex and variations in the adverse pressure gradient from the maximum thickness position to the trailing-edge confluence. The impact of different roughness heights is further investigated. It is discovered that when the roughness height is higher than 0.3 mm, the boundary layer can be considered fully turbulent, and the lift curve shows the “N” shape stably. When the roughness height is between 0.07 mm and 0.1 mm, a transitional state can be observed, with several saltation points in the lift curve. The main characteristics of different flow regimes based on different lift curve segments are summarized. This research enhances the understanding of the effects of leading-edge roughness on the aerodynamic performance of a thick wind turbine airfoil, and the simulation method for considering the effect of leading-edge roughness is practical to be applied on large-scale wind turbine blade to estimate the aerodynamic performance under rough leading-edge conditions, thereby supporting advancements in wind turbine technology and promoting the broader adoption of renewable energy.

For offshore wind farms, the power loss caused by the wake effect is large due to the large capacity of the wind turbine. At the same time, the operating environment of the offshore wind farm is very harsh, and the cost of maintenance is higher than that of the onshore wind farm. Therefore, it is worthwhile to study through reasonable control how to reduce the wake loss of the wind farm and minimize the losses caused by the fault. In this paper, the Particle Swarm Optimization (PSO) algorithm is used to optimize the active power dispatch of wind farms under generator cooling system faults. The optimization objectives include avoiding the further deterioration of the generator fault, reducing unnecessary power loss of the faulty wind turbine, tracking the power demand from the Transmission System Operator (TSO), and reducing the power fluctuation caused by the PSO algorithm. The proposed optimal power dispatch strategy was compared with the two generally-used fault-handling methods and the proportional dispatch strategy in simulation. The result shows that the proposed strategy can improve the power generation capacity of the wind farm and achieve an efficient trade-off between power generation and fault protection.