Big Data-based Harmonic Problem Research in Wind Farms
Song-Tao Yu, Da Xie, Yu-Pu Lu, Zu-Yi Zhao, Yan-Chi Zhang
Available Online December 2016.
- https://doi.org/10.2991/icwcsn-16.2017.105How to use a DOI?
- Keywords-Big Data; Wind Farms; Harmonics; Data Mining; Clustering.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Song-Tao Yu AU - Da Xie AU - Yu-Pu Lu AU - Zu-Yi Zhao AU - Yan-Chi Zhang PY - 2016/12 DA - 2016/12 TI - Big Data-based Harmonic Problem Research in Wind Farms BT - 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016) PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/icwcsn-16.2017.105 DO - https://doi.org/10.2991/icwcsn-16.2017.105 ID - Yu2016/12 ER -