DocumentCode :
174561
Title :
Multivariate regression models for prediction of wind speed
Author :
Arjun, N.N. ; Prema, V. ; Kumar, D. Krishna ; Prashanth, P. ; Preekshit, V. Sumantha ; Rao, K. Uma
Author_Institution :
R.V. Coll. of Eng., Bangalore, India
fYear :
2014
fDate :
26-28 Aug. 2014
Firstpage :
171
Lastpage :
176
Abstract :
As we progress in both time and technology, our energy needs are rising at an exponential level and hence we need to tap unconventional sources of energy more efficiently. Wind energy is one such source and this paper presents a method to predict the speed of wind, on which the wind energy generated, depends more efficiently and hence avoid both costly overproduction and underproduction. This can be achieved by statistical methods wherein data in large numbers are collected, analyzed for functional relationship using Multivariate regression models. The results obtained are then compared with the actual values available for validation.
Keywords :
regression analysis; wind power; data analytics; multivariate regression models; statistical methods; wind energy; wind speed prediction; Analytical models; Atmospheric modeling; Correlation; Data models; Humidity; Predictive models; Wind speed; Data Analytics; Modeling; Multivariate regression; Prediction; Wind Speed;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Science & Engineering (ICDSE), 2014 International Conference on
Conference_Location :
Kochi
Print_ISBN :
978-1-4799-6870-1
Type :
conf
DOI :
10.1109/ICDSE.2014.6974632
Filename :
6974632
Link To Document :
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