scholarly journals Big Data-based Harmonic Problem Research in Wind Farms

Author(s):  
Song-Tao Yu ◽  
Da Xie ◽  
Yu-Pu Lu ◽  
Zu-Yi Zhao ◽  
Yan-Chi Zhang
Keyword(s):  
Big Data ◽  
2019 ◽  
Vol 8 (S1) ◽  
pp. 98-102
Author(s):  
N. V. Poorima ◽  
B. Srinivasan ◽  
S. Karthikeyan

The desire to cut back the price of energy from turbine generation has seen a rise within the analysis applied to the sphere of turbine condition observation. Wind turbine condition observation has the potential to cut back operation and maintenance prices through optimized maintenance programming and also the rejection of major breakdowns. To aid this analysis, increasing volumes of knowledge are being captured and keep. These massive volumes of knowledge could also be deemed ‘Big Data’, and need improved handling techniques so as to figure with the information with efficiency. It introduces a turbine condition observation system that has been put in in AN operational Vestas V47 turbine for the aim of developing algorithms to sight machine deterioration. The system’s ability to capture massive volumes of knowledge (approx.2TB per month) has LED to the need of victimization increased knowledge handling techniques. This paper can discuss these ‘Big Data’ techniques and recommend however they will ultimately be used for condition observation of multiple wind turbines or wind farms.


ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  

Find Out About 'Big Data' to Track Outcomes


2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.


2017 ◽  
Vol 225 (3) ◽  
pp. 287-288
Keyword(s):  

An associated conference will take place at ZPID – Leibniz Institute for Psychology Information in Trier, Germany, on June 7–9, 2018. For further details, see: http://bigdata2018.leibniz-psychology.org


PsycCRITIQUES ◽  
2014 ◽  
Vol 59 (2) ◽  
Author(s):  
David J. Pittenger
Keyword(s):  

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