Abstract
With the increased interest for co-location of wind and solar PV plants, the issues related to power fluctuations and their impact on production curtailment losses due to grid constraints gained additional importance. This paper investigates power fluctuations and the smoothing effect in wind farms utilising wavelet multi-scale analysis based on 1-second wind speed and wind power data measurements. Maximal overlap discrete wavelet transform (MODWT) is applied to decompose the wind power time series into several scales, each representing particular frequency band. Analysis of variance across multiple scales is provided for wind speed and power time series of a single and multiple wind turbine generators (WTGs). Additionally, multi-scale correlations are captured between a pair of WTGs on two sites. Smoothing effect has been analysed across different time scales in three operational wind farms of different sizes. The results imply that power fluctuations in large-scale wind farms can be accurately captured using 1-minute time resolution.
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