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Big Data-based Harmonic Problem Research in Wind Farms

机译:风电场基于大数据的谐波问题研究

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More and more attention on the power quality of wind farms has been paid recent years, in which harmonic problem is one of the most concerned. On the other hand, power big data in wind farm generated all the time, and the volume is increasing continuously, which can be mined to extract some special or new information to solve current operating problem and adjust the running conditions of wind turbines. In this paper, a novel algorithm for power big data analysis has been put forward by a combined application of conventional harmonic analyzing method and typical clustering algorithm, which can be used to deal with the big data in wind farm to study harmonic problem. The measured big data of a 2MW DFIG wind turbine in operation have been used to verify the new algorithm, and some interesting conclusions of harmonics have been found at last.
机译:越来越多地关注风电场的电力质量近年来,其中谐波问题是最关心的问题。另一方面,在风电场中产生的电力大数据一直在一起,并且音量连续增加,可以采用,以提取一些特殊或新信息来解决当前的运行问题,并调整风力涡轮机的运行条件。本文通过常规谐波分析方法和典型聚类算法的组合应用,已经提出了一种新的电力大数据分析算法,其可用于处理风电场的大数据来研究谐波问题。在操作中,2MW DFIG风力涡轮机的测量大数据已被用于验证新算法,并持久地发现了一些有趣的谐波结论。

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