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This paper proposes a new application of the self-tuning least squares (STLS) estimation algorithm for understanding transient processes during a rejection experiment at a wind farm site in Denmark. The problems of simultaneous estimation of frequency and harmonic distortion in a wind farm are investigated. An adaptive and robust application of the STLS algorithm is proposed to estimate the unknown parameters during the dynamic changes due to forced islanding conditions. Equipped with a self-tuning procedure, the algorithm is resistant to noise which significantly improves its accuracy. The system frequency is considered as an unknown model parameter and estimated simultaneously with fundamental and harmonic components. The outcome is an estimation method which is not sensitive to variations of system frequency. To demonstrate the efficiency of the proposed algorithm, a number of computer simulated tests are also presented. Several interesting results can be observed during the rejection experiment: the large deviations of three phase voltages and currents, the changes of total harmonic distortion, and variations of power system frequency.