The Wind Speed Prediction Based on AR Model and BP Neural Network

Cong Lin Zhang

doi:10.4028/www.scientific.net/AMR.450-451.1593

Paper Titles

Research on Sustainable Development of Residence in Northwest China under the Urbanization Process
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Discussion on Properties and Microstructure of Geopolymer Concrete Containing Fly Ash and Recycled Aggregate
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Braced Tube Structures for Complex-Shaped Tall Buildings
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Analysis on Ecological Technology and Environment Impact Evaluation of Rammed Earth Residence
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The Wind Speed Prediction Based on AR Model and BP Neural Network
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Instance Analysis of Steel Reforced Concrete in Soil
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Measurement and the Distribution Law of In Situ Stresses at Deep Depth of Xingcun Coal Mine
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Past Analysis of Architecture Design Based on the Concept of Ecology
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Thinking the Green Strategies on Today’s Rural Architecture in China
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 450-451The Wind Speed Prediction Based on AR Model and BP...

The Wind Speed Prediction Based on AR Model and BP Neural Network

Abstract:

The output of the wind turbine has high randomness due to natural wind velocity. Whether the output can be predicted accurately or not is directly related to the feasibility of dispatching wind power in the power network. The key of wind farm output prediction is to predict the wind speed of wind farm site. This paper uses AR model and BP neural network to predict 24-hour wind speed, and proves the feasibility of these two predicted methods according to comparison with measured wind speed data. This paper has certain reference significance for improving the precision of wind speed prediction.

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Periodical:

Advanced Materials Research (Volumes 450-451)

Pages:

1593-1596

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.450-451.1593

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Online since:

January 2012

Authors:

Cong Lin Zhang

Keywords:

Autoregressive AR Model, BP Neural Network (BPNN), Comparative Analysis, Wind Speed Prediction

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