中文版 | English
Title

An Evolutionary Multiobjective Knee-Based Lower Upper Bound Estimation Method for Wind Speed Interval Forecast

Author
Corresponding AuthorWang, Rui
Publication Years
2022-10-01
DOI
Source Title
ISSN
1089-778X
EISSN
1941-0026
Volume26Issue:5Pages:1030-1042
Abstract
Due to the high variability and uncertainty of the wind speed, an interval forecast can provide more information for decision makers to achieve a better energy management compared to the traditional point forecast. In this article, a knee-based lower upper bound estimation method (K-LUBE) is proposed to construct wind speed prediction intervals (PIs). First, we analyze the underlying limitations of traditional direct interval forecast methods, i.e., their obtained PIs often fail to achieve a good balance between the interval width and the coverage probability. K-LUBE resolves the difficulty based on a multiobjective optimization framework in conjunction with a knee selection criterion. Specifically, a PI-NSGA-II multiobjective optimization algorithm is designed to obtain a set of Pareto-optimal solutions. A parameter transfer and a sample training strategies are developed to significantly improve the convergence speed of the optimization procedure. Then, the knee selection criterion is introduced to select the best tradeoff solution among the obtained solutions. In comparison with traditional methods, this method can always provide a reliable PI for decision makers. The procedure is automatic and requires no parameter to be specified in advance, making it more practical for use. The effectiveness of the proposed K-LUBE method is demonstrated through extensive comparisons with four traditional direct interval forecast methods and four classical benchmark models.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
Others
Funding Project
National Science Fund for Outstanding Young Scholars[62122093] ; National Natural Science Foundation of China[72071205] ; Ji-Hua Laboratory Scientific Project[X210101UZ210]
WOS Research Area
Computer Science
WOS Subject
Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS Accession No
WOS:000862385200020
Publisher
ESI Research Field
COMPUTER SCIENCE
Data Source
Web of Science
PDF urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9585061
Citation statistics
Cited Times [WOS]:4
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/405987
DepartmentDepartment of Computer Science and Engineering
Affiliation
1.Natl Univ Def Technol, Coll Syst Engn, Changsha 410073, Peoples R China
2.Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
3.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Guangdong Prov Key Lab Brain Inspired Intelligent, Shenzhen 518055, Peoples R China
Recommended Citation
GB/T 7714
Li, Kaiwen,Zhang, Tao,Wang, Rui,et al. An Evolutionary Multiobjective Knee-Based Lower Upper Bound Estimation Method for Wind Speed Interval Forecast[J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION,2022,26(5):1030-1042.
APA
Li, Kaiwen,Zhang, Tao,Wang, Rui,Wang, Ling,&Ishibuchi, Hisao.(2022).An Evolutionary Multiobjective Knee-Based Lower Upper Bound Estimation Method for Wind Speed Interval Forecast.IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION,26(5),1030-1042.
MLA
Li, Kaiwen,et al."An Evolutionary Multiobjective Knee-Based Lower Upper Bound Estimation Method for Wind Speed Interval Forecast".IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 26.5(2022):1030-1042.
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