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Abstract
Time varying nature of the wind power is studied previously considering different time intervals from seconds to days. However for power quality problems such as flicker, a model which considers the extremely fast variations is essential. Here by using large number of actual records, a time-varying model is proposed which considers the extremely short-time variations of wind active and reactive powers. The wind farm is modelled as a current source with time varying amplitude and phase which change every 0.01 s. Autoregressive moving-average (ARMA) models are utilized to model the variations and ARMA coefficients are calculated for every record. Same to the actual behaviour, the proposed model is non-stationary as the ARMA order and coefficients are different at every run of the model. The proposed model is confirmed through utilizing several applications which need the power time series with extremely short sampling intervals. The following studies are performed by using the actual data and then the proposed model: power spectral density of active and reactive power variations, instantaneous flicker, short term flicker (Pst), estimating the Pst using the maximum value of the instantaneous flicker, estimation of cumulative Pst for multiple wind turbines, and the impact of SVC on flicker mitigation.
Highlights
In recent years, the importance of renewable energy sources has been increasing while the supply capability of fossil fuels began to decrease [1, 2]
The following studies are performed by using the actual data and the proposed model: power spectral density of active and reactive power variations, instantaneous flicker, short term flicker (Pst), estimating the Pst using the maximum value of the instantaneous flicker, estimation of cumulative Pst for multiple wind turbines, and the impact of SVC on flicker mitigation
Regardless using the results from the actual data or those extracted from the proposed model, results reveals that utilizing the forecasting of reactive power can significantly improve SVC performance in flicker mitigation
Summary
The importance of renewable energy sources has been increasing while the supply capability of fossil fuels began to decrease [1, 2]. The main contribution of the present paper can be summarized in proposing a practical model for squirrel cage induction generators wind farms based on a large number of actual data It is simple for implementation and can be used in power quality studies instead of actual records which always are not available. At every run of the proposed model, an ARMA model is selected randomly from the attained set of ARMA models and active and reactive powers time series are simulated based on the selected ARMA model They are used to attain the amplitude and phase (I and δ) of the current source by solving Equation (5) for every half cycle. The accuracy of the proposed model is evaluated through some applications which need the wind farm’s active and reactive powers data in extremely short time periods. The First category includes active and reactive powers of individual squirrel cage turbines with 150 records and the second category consists of 330 records belong to the substation connected to the squirrel cage turbines
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