Extremely short time modeling of wind power variations

Ali Asghar Bagheri, Haidar Samet

Abstract


One of the main challenges in the operation of wind farms is the time varying nature of output power. So far, many studies have been done for modeling the variations of wind farm output power. However the extremely fast variations of wind generation have not been considered in previous studies. The variations of active/reactive powers in the wind turbine and wind farms with sampling time equal to 0.01 s are studied and modeled in the present paper. For this purpose, a massive amount of actual records of voltage and current waveform data are collected from the Manjil wind farm in the north of Iran. Analyses of results show that the rate of change of active/reactive powers of the wind turbine and wind farm is very high. A stochastic model based on the auto-regressive moving-average (ARMA) process is proposed to model the fast variations of active/reactive powers of the wind turbine and wind farm. The presented model as a basic and simple model can be utilized in many applications such as SVC control system to compensate the reactive power and flicker suppression of wind plants.

Keywords


wind power modeling; wind power variations; time series; ARMA processes.

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v8i2.6924.g7391

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