Wind and photovoltaic power prediction using a combined VMD-CNN-BiLSTM model Article Swipe
Junming Cao
,
Fei Tang
,
Luo Ji
,
Mengxi Li
,
Ke Duan
,
Qi Sun
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/3084/1/012076
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/3084/1/012076
The swift advancement of renewable energy necessitates precise forecasting of wind and photovoltaic power to ensure grid stability and effective energy management. Nonetheless, the data associated with wind and solar power is characterized by non-stationarity, noise interference, and complex temporal dynamics, which hinder the effectiveness of conventional forecasting techniques. To enhance prediction accuracy, this study integrates the effectiveness signal decomposition and denoising capabilities of Variational Mode Decomposition (VMD), the robust feature extraction potential of Convolutional Neural Networks (CNN), and the strong temporal memory capacity of Bidirectional Long Short-Term Memory networks (BiLSTM) to develop a high-accuracy combined VMD-CNN-BiLSTM forecasting model for wind and solar energy.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1742-6596/3084/1/012076
- OA Status
- diamond
- References
- 8
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4413662454Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1088/1742-6596/3084/1/012076Digital Object Identifier
- Title
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Wind and photovoltaic power prediction using a combined VMD-CNN-BiLSTM modelWork title
- Type
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articleOpenAlex work type
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-08-01Full publication date if available
- Authors
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Junming Cao, Fei Tang, Luo Ji, Mengxi Li, Ke Duan, Qi SunList of authors in order
- Landing page
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https://doi.org/10.1088/1742-6596/3084/1/012076Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1088/1742-6596/3084/1/012076Direct OA link when available
- Concepts
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Photovoltaic system, Power (physics), Wind power, Computer science, Environmental science, Engineering, Electrical engineering, Physics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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