Enhancing wind speed forecasting through synergy of machine learning, singular spectral analysis, and variational mode decomposition

Energy, Год журнала: 2024, Номер 292, С. 130493 - 130493

Опубликована: Янв. 27, 2024

Язык: Английский

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An advanced framework for net electricity consumption prediction: Incorporating novel machine learning models and optimization algorithms

Energy, Год журнала: 2024, Номер 296, С. 131259 - 131259

Опубликована: Апрель 9, 2024

Язык: Английский

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Prediction of wind and PV power by fusing the multi-stage feature extraction and a PSO-BiLSTM model

Energy, Год журнала: 2024, Номер 298, С. 131345 - 131345

Опубликована: Апрель 17, 2024

Язык: Английский

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Wind power forecasting method of large-scale wind turbine clusters based on DBSCAN clustering and an enhanced hunter-prey optimization algorithm

Energy Conversion and Management, Год журнала: 2024, Номер 307, С. 118341 - 118341

Опубликована: Март 28, 2024

Язык: Английский

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Electric vehicle charging load forecasting considering weather impact

Applied Energy, Год журнала: 2025, Номер 383, С. 125337 - 125337

Опубликована: Янв. 20, 2025

Язык: Английский

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Multi-step electric vehicles charging loads forecasting: An autoformer variant with feature extraction, frequency enhancement, and error correction blocks

Applied Energy, Год журнала: 2024, Номер 376, С. 124308 - 124308

Опубликована: Авг. 27, 2024

Язык: Английский

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A reconstruction-based secondary decomposition-ensemble framework for wind power forecasting

Energy, Год журнала: 2024, Номер 308, С. 132895 - 132895

Опубликована: Авг. 19, 2024

Язык: Английский

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A wind power forecasting model based on data decomposition and cross-attention mechanism with cosine similarity

Electric Power Systems Research, Год журнала: 2024, Номер 229, С. 110156 - 110156

Опубликована: Янв. 22, 2024

Язык: Английский

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Review of AI-Based Wind Prediction within Recent Three Years: 2021–2023

Energies, Год журнала: 2024, Номер 17(6), С. 1270 - 1270

Опубликована: Март 7, 2024

Wind prediction has consistently been in the spotlight as a crucial element achieving efficient wind power generation and reducing operational costs. In recent years, with rapid advancement of artificial intelligence (AI) technology, its application field made significant strides. Focusing on process AI-based modeling, this paper provides comprehensive summary discussion key techniques models data preprocessing, feature extraction, relationship learning, parameter optimization. Building upon this, three major challenges are identified prediction: uncertainty data, incompleteness complexity learning. response to these challenges, targeted suggestions proposed for future research directions, aiming promote effective AI technology address issues therein.

Язык: Английский

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A comparative study of principal component analysis and kernel principal component analysis for photogrammetric shape-based turbine blade damage analysis

Engineering Structures, Год журнала: 2024, Номер 318, С. 118712 - 118712

Опубликована: Июль 31, 2024

Язык: Английский

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