Application of three Transformer neural networks for short-term photovoltaic power prediction: A case study DOI Creative Commons
Jiahao Wu,

Yongkai Zhao,

Ruihan Zhang

et al.

Solar Compass, Journal Year: 2024, Volume and Issue: 12, P. 100089 - 100089

Published: Sept. 17, 2024

Language: Английский

A novel DWTimesNet-based short-term multi-step wind power forecasting model using feature selection and auto-tuning methods DOI
Chu Zhang, Yuhan Wang,

Yongyan Fu

et al.

Energy Conversion and Management, Journal Year: 2024, Volume and Issue: 301, P. 118045 - 118045

Published: Jan. 5, 2024

Language: Английский

Citations

23
Ultra-short-term wind power probabilistic forecasting based on an evolutionary non-crossing multi-output quantile regression deep neural network DOI

Jianhua Zhu,

Yaoyao He, Xiaodong Yang

et al.

Energy Conversion and Management, Journal Year: 2024, Volume and Issue: 301, P. 118062 - 118062

Published: Jan. 13, 2024

Language: Английский

Citations

22
A hybrid prediction model of improved bidirectional long short-term memory network for cooling load based on PCANet and attention mechanism DOI
Xiuying Yan,

Xingxing Ji,

Qinglong Meng

et al.

Energy, Journal Year: 2024, Volume and Issue: 292, P. 130388 - 130388

Published: Jan. 23, 2024

Language: Английский

Citations

11
SSPENet: Semi-supervised prototype enhancement network for rolling bearing fault diagnosis under limited labeled samples DOI

Xuejian Yao,

Xingchi Lu,

Quan Jiang

et al.

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 61, P. 102560 - 102560

Published: April 24, 2024

Language: Английский

Citations

11
Wind and Solar Power Generation Forecasting Based on Hybrid CNN-ABiLSTM, CNN-Transformer-MLP Models DOI
Tasarruf Bashir,

Huifang Wang,

Mustafa Tahir

et al.

Renewable Energy, Journal Year: 2024, Volume and Issue: unknown, P. 122055 - 122055

Published: Nov. 1, 2024

Language: Английский

Citations

9
Combined Ultra-Short-Term Photovoltaic Power Prediction Based on CEEMDAN Decomposition and RIME Optimized AM-TCN-BiLSTM DOI

Daixuan Zhou,

Yujin Liu,

Xu Wang

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134847 - 134847

Published: Feb. 1, 2025

Language: Английский

Citations

1
Parallel TimesNet-BiLSTM model for ultra-short-term photovoltaic power forecasting using STL decomposition and auto-tuning DOI

Jianqiang Gong,

Zhiguo Qu, Zhiyu Zhu

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135286 - 135286

Published: Feb. 1, 2025

Language: Английский

Citations

1
Ultra-short-term wind power forecasting based on personalized robust federated learning with spatial collaboration DOI
Yongning Zhao, Shiji Pan, Yuan Zhao

et al.

Energy, Journal Year: 2023, Volume and Issue: 288, P. 129847 - 129847

Published: Dec. 1, 2023

Language: Английский

Citations

19
Optimization and scheduling scheme of park-integrated energy system based on multi-objective Beluga Whale Algorithm DOI Creative Commons
Hongbin Sun,

Qing Cui,

Jingya Wen

et al.

Energy Reports, Journal Year: 2024, Volume and Issue: 11, P. 6186 - 6198

Published: June 1, 2024

To improve the consumption rate of renewable energy and ensure stability power heat supply within industrial park, a park-integrated system (PIES), which incorporates electric heating equipment, storage devices, multiple micro sources, is established. Based on established PIES, price-based demand response (PDR) mechanism introduced to establish multi-objective optimization scheduling model with two time scales: day-ahead intra-day scheduling, aiming minimize impact main grid flexibility operation real-time scheduling. With objectives minimizing operating costs maximizing environmental benefits for hybrid algorithm named Non-Dominated Sorting Beluga Whale Optimization (NSBWO), combines Genetic Algorithm II (NSGA-II) (BWO) proposed solve problem model. Simultaneously, an adaptive penalty function in handle constraint problems additional term wind solar curtailment included constraints sustainable energy. The NSBWO exhibits more robust search capabilities faster convergence speed than NSGA-II MOPSO algorithm. Simulation results show that can achieve low-carbon economic both long-term short-term scales consumption. Due its flexibility, has lower

Language: Английский

Citations

6
Multimodal deep learning water level forecasting model for multiscale drought alert in Feiyun River basin DOI
Rui Dai, Wanliang Wang, Zhang Ren-gong

et al.

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 244, P. 122951 - 122951

Published: Dec. 15, 2023

Language: Английский

Citations

13