LAPSE:2020.0307
Published Article
LAPSE:2020.0307
Short-Term Wind Power Prediction Using GA-BP Neural Network Based on DBSCAN Algorithm Outlier Identification
Pei Zhang, Yanling Wang, Likai Liang, Xing Li, Qingtian Duan
March 25, 2020
Accurately predicting wind power plays a vital part in site selection, large-scale grid connection, and the safe and efficient operation of wind power generation equipment. In the stage of data pre-processing, density-based spatial clustering of applications with noise (DBSCAN) algorithm is used to identify the outliers in the wind power data and the collected wind speed data of a wind power plant in Shandong Province, and the linear regression method is used to correct the outliers to improve the prediction accuracy. Considering the important impact of wind speed on power, the average value, the maximum difference and the average change rate of daily wind speed of each historical day are used as the selection criteria to select similar days by using DBSCAN algorithm and Euclidean distance. The short-term wind power prediction is carried out by using the similar day data pre-processed and unprocessed, respectively, as the input of back propagation neural network optimized by genetic algorithm (GA-BP neural network). Analysis of the results proves the practicability and efficiency of the prediction model and the important role of outlier identification and correction in improving the accuracy of wind power prediction.
Keywords
DBSCAN algorithm, GA-BP neural network, linear regression method, outlier identification, short-term wind power prediction
Suggested Citation
Zhang P, Wang Y, Liang L, Li X, Duan Q. Short-Term Wind Power Prediction Using GA-BP Neural Network Based on DBSCAN Algorithm Outlier Identification. (2020). LAPSE:2020.0307
Author Affiliations
Zhang P: School of Mechanical, Electrical and Information Engineering, Shandong University (Weihai), Weihai 264209, China [ORCID]
Wang Y: School of Mechanical, Electrical and Information Engineering, Shandong University (Weihai), Weihai 264209, China
Liang L: School of Mechanical, Electrical and Information Engineering, Shandong University (Weihai), Weihai 264209, China
Li X: Shandong Hanlin Technology Co., Ltd., Jinan 250000, China
Duan Q: Shandong Hanlin Technology Co., Ltd., Jinan 250000, China
Journal Name
Processes
Volume
8
Issue
2
Article Number
E157
Year
2020
Publication Date
2020-01-27
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr8020157, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2020.0307
This Record
External Link

doi:10.3390/pr8020157
Publisher Version
Download
Files
[Download 1v1.pdf] (2.5 MB)
Mar 25, 2020
Main Article
License
CC BY 4.0
Meta
Record Statistics
Record Views
496
Version History
[v1] (Original Submission)
Mar 25, 2020
 
Verified by curator on
Mar 25, 2020
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2020.0307
 
Original Submitter
Calvin Tsay
Links to Related Works
Directly Related to This Work
Publisher Version