The power generated from wind is not synchronized to the electrical frequency of the power grid. Grid balancing services must be assured when the output from a wind farm is integrated into the electrical grid to avoid the risk of blackouts. Active Power Control (APC) methods are employed to provide grid balancing ancillary services such as frequency control. One objective of APC is to have the total power generated from a wind farm, track the power demand requirements obtained from the utility grid. To achieve this objective, the wind farm should be able to operate below their maximum power production capacity i.e, in derating mode. This implies that the turbines in the wind farm should also be derated. The presence of wakes in the wind farm results in the downstream turbines to experience reduced wind speed and increased turbulence.
The earlier works on APC for wind farms revealed the need for a closed-loop wind farm control strategy to combat the effect of wake turbulence. The presence of wakes posed several challenges on obtaining the estimate of the available power at every turbine on a time scale of seconds. Yet, some model-free algorithms were dependent on the estimation of available power at every turbine in the wind farm. This, leads us to the question, “Can a wind farm controller be developed to provide APC for waked wind farms, where the setpoint selection and distribution are made without estimating the available power at each turbine?” To explore the answer to this question, a single wind turbine power tracking control algorithm is developed as the first step. This tracking algorithm does not depend on the estimation of available power. The proposed algorithm makes the turbine operate on two different operating modes namely, the perfect tracking mode and greedy/boosting mode. The algorithms were developed in a way that they can be integrated with the existing torque and pitch controllers of the turbine. Following this, a closed-loop wind farm control strategy has been developed. The closed-loop wind farm controller takes the total power generated from the wind farm as the feedback signal. Based on the operating mode of the individual turbines, the wind farm controller coordinates and distributes the total power reference signal as individual power set-points to the respective wind turbines. The performance of the closed loop wind farm controller was evaluated for a 9-turbine case in SOWFA simulation for four different scenarios. The scenarios differed from each other based on the way the turbines in the wind farm are derated and the individual set points to the turbines are distributed by the wind farm controller. Simulation results showed that the scenario in which the upstream turbines are derated more than the downstream turbines, the tracking performance was better compared to the other scenarios. The damage equivalent loads experienced by the tower base of the individual turbines were also calculated and each of the scenario resulted in different loading patterns. Recommendations are also provided to extend this work and perform further research.