风电机组平滑效应和功率波动的小波多尺度分析

A. Meglic, R. Goic
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引用次数: 0

摘要

随着人们对风能和太阳能光伏发电厂合设地点的兴趣增加,与电力波动及其对电网限制造成的减产损失的影响有关的问题变得更加重要。基于1秒风速和风电数据测量,利用小波多尺度分析研究了风电场的功率波动和平滑效应。采用最大重叠离散小波变换(MODWT)将风电时间序列分解为多个尺度,每个尺度代表特定的频段。对单台和多台风力发电机组的风速和功率时间序列进行了多尺度方差分析。此外,在两个地点的一对wtg之间捕获了多尺度相关性。分析了三个不同规模的运行风电场在不同时间尺度上的平滑效应。结果表明,大型风电场的电力波动可以用1分钟的时间分辨率准确捕获。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wavelet Multi-Scale Analysis of Wind Turbines Smoothing Effect and Power Fluctuations
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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