Multi-step wind speed prediction based on LSSVM combined with ESMD and fractional-order beetle swarm optimization Article Swipe
Yuanchen Gao
,
Bin Wang
,
Fei Chen
,
Wenjing Zhang
,
Dong‐Dong Zhou
,
Fengjiao Wu
,
Diyi Chen
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.egyr.2023.05.034
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.egyr.2023.05.034
Accurate and stable wind speed prediction can alleviate the uncertain impacts of wind power generation caused by nonlinear characteristics of wind speed, and then improve the reliability of wind power. In this paper, a hybrid model for wind speed prediction based on mode decomposition, parameter optimization and basic prediction model is proposed. First, the extreme-point symmetric mode decomposition (ESMD) is employed to adaptively decompose the denoised wind speed time series into sub-sequences with different frequencies. Second, a fractional-order beetle swarm optimization (FO-BSO) for parameter optimization of the Least squares support vector machine (LSSVM) is proposed. Through benchmark functions and non-parametric statistical test, the advantages of the FO-BSO in accuracy, stability and convergence speed are verified. Subsequently, the ESMD-FO-BSO-LSSVM prediction model is established, and three groups of wind speed datasets with different sampling locations and sampling frequencies are selected for simulation experiments. The results show that the coefficient of determination of 1-step prediction of the proposed model in three datasets are 0.9856, 0.9713, 0.9940, which has 2.43%, 3.38%, 3.08% average promotion than that of 7 comparative models. And the accuracy and stability of ESMD-FO-BSO-LSSVM model in multi-step wind speed prediction have also achieved better performance than 7 competitors.
Related Topics
Concepts
Wind speed
Particle swarm optimization
Benchmark (surveying)
Wind power
Computer science
Stability (learning theory)
Control theory (sociology)
Parametric statistics
Convergence (economics)
Mathematical optimization
Mathematics
Algorithm
Statistics
Engineering
Artificial intelligence
Machine learning
Meteorology
Economic growth
Physics
Economics
Electrical engineering
Control (management)
Geodesy
Geography
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.egyr.2023.05.034
- OA Status
- gold
- Cited By
- 32
- References
- 65
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4379117770
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4379117770Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.egyr.2023.05.034Digital Object Identifier
- Title
-
Multi-step wind speed prediction based on LSSVM combined with ESMD and fractional-order beetle swarm optimizationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-06-02Full publication date if available
- Authors
-
Yuanchen Gao, Bin Wang, Fei Chen, Wenjing Zhang, Dong‐Dong Zhou, Fengjiao Wu, Diyi ChenList of authors in order
- Landing page
-
https://doi.org/10.1016/j.egyr.2023.05.034Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.egyr.2023.05.034Direct OA link when available
- Concepts
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Wind speed, Particle swarm optimization, Benchmark (surveying), Wind power, Computer science, Stability (learning theory), Control theory (sociology), Parametric statistics, Convergence (economics), Mathematical optimization, Mathematics, Algorithm, Statistics, Engineering, Artificial intelligence, Machine learning, Meteorology, Economic growth, Physics, Economics, Electrical engineering, Control (management), Geodesy, GeographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
32Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 13, 2024: 17, 2023: 2Per-year citation counts (last 5 years)
- References (count)
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65Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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