APPLICATION OF SLIDING WINDOW TECHNIQUE FOR PREDICTION OF WIND VELOCITY TIME SERIES

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

VAFAEIPOUR MAJID; RAHBARI OMID; ROSEN MARC A.; FAZELPOUR FARIVAR; ANSARIRAD POOYANDEH

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF ENERGY AND ENVIRONMENTAL ENGINEERING Year:2014 | Volume:5 | Issue:2 Page(s): 1-7

Download Full-Text

View:

413

Download:

194

Cites:

Information Journal Paper

Title

APPLICATION OF SLIDING WINDOW TECHNIQUE FOR PREDICTION OF WIND VELOCITY TIME SERIES

Author(s)

Keywords

WIND ENERGY

ANN

TIME SERIES PREDICTION

SLIDING WINDOW

MULTI-LAYER PERCEPTRON

RADIAL BASIS FUNCTION

TEHRAN

Abstract

The uncertainty caused by the discontinuous nature of WIND ENERGY affects the power grid. Hence, forecasting the behavior of this renewable resource is important for energy managers and electricity traders to overcome the risk of unpredictability and to provide reliability for the grid. The objective of this paper is to employ and compare the potential of various artificial neural network structures of MULTI-LAYER PERCEPTRON (MLP) and RADIAL BASIS FUNCTION for prediction of the wind velocity time series in TEHRAN, Iran. Structure analysis and performance evaluations of the established networks indicate that the MLP network with a 4-7-13-1 architecture is superior to others. The best networks were deployed to unseen data and were capable of predicting the velocity time series via using the SLIDING WINDOW technique successfully. Applying the statistical indices with the predicted and the actual test data resulted in acceptable RMSE, MSE and R2 values with 1.19, 1.43 and 0.85, respectively, for the best network.

Cites

NEUTRAL CURRENT COMPENSATION TECHNIQUES IN AUTONOMOUS WIND ENERGY SOURCES

References

No record.

Cite

APA: Copy

VAFAEIPOUR, MAJID, RAHBARI, OMID, ROSEN, MARC A., FAZELPOUR, FARIVAR, & ANSARIRAD, POOYANDEH. (2014). APPLICATION OF SLIDING WINDOW TECHNIQUE FOR PREDICTION OF WIND VELOCITY TIME SERIES. INTERNATIONAL JOURNAL OF ENERGY AND ENVIRONMENTAL ENGINEERING, 5(2), 1-7. SID. https://sid.ir/paper/327078/en

Vancouver: Copy

VAFAEIPOUR MAJID, RAHBARI OMID, ROSEN MARC A., FAZELPOUR FARIVAR, ANSARIRAD POOYANDEH. APPLICATION OF SLIDING WINDOW TECHNIQUE FOR PREDICTION OF WIND VELOCITY TIME SERIES. INTERNATIONAL JOURNAL OF ENERGY AND ENVIRONMENTAL ENGINEERING[Internet]. 2014;5(2):1-7. Available from: https://sid.ir/paper/327078/en

IEEE: Copy

MAJID VAFAEIPOUR, OMID RAHBARI, MARC A. ROSEN, FARIVAR FAZELPOUR, and POOYANDEH ANSARIRAD, “APPLICATION OF SLIDING WINDOW TECHNIQUE FOR PREDICTION OF WIND VELOCITY TIME SERIES,” INTERNATIONAL JOURNAL OF ENERGY AND ENVIRONMENTAL ENGINEERING, vol. 5, no. 2, pp. 1–7, 2014, [Online]. Available: https://sid.ir/paper/327078/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops