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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Short term wind power prediction for regional wind farms based on spatial-temporal characteristic distribution
Guangzheng Yu, Chengquan Liu, Bo Tang, et al.
Renewable Energy (2022) Vol. 199, pp. 599-612
Closed Access | Times Cited: 72

Showing 1-25 of 72 citing articles:

Contribution of renewable energy (hydro, wind, solar and biomass) to decarbonization and transformation of the electricity generation sector for sustainable development
Lizica Simona Paraschiv, Spiru Paraschiv
Energy Reports (2023) Vol. 9, pp. 535-544
Open Access | Times Cited: 93
A short-term wind power forecasting method based on multivariate signal decomposition and variable selection
Ting Yang, Zhenning Yang, Fei Li, et al.
Applied Energy (2024) Vol. 360, pp. 122759-122759
Closed Access | Times Cited: 25
A short-term power prediction method for wind farm cluster based on the fusion of multi-source spatiotemporal feature information
Mao Yang, Chao Han, Wei Zhang, et al.
Energy (2024) Vol. 294, pp. 130770-130770
Closed Access | Times Cited: 16
Spatiotemporal wind power forecasting approach based on multi-factor extraction method and an indirect strategy
Shaolong Sun, Zongjuan Du, Kun Jin, et al.
Applied Energy (2023) Vol. 350, pp. 121749-121749
Closed Access | Times Cited: 33
A Review of Modern Wind Power Generation Forecasting Technologies
Wen-Chang Tsai, Chih-Ming Hong, Chia‐Sheng Tu, et al.
Sustainability (2023) Vol. 15, Iss. 14, pp. 10757-10757
Open Access | Times Cited: 23
An online transfer learning model for wind turbine power prediction based on spatial feature construction and system-wide update
Ling Liu, Jujie Wang, Jianping Li, et al.
Applied Energy (2023) Vol. 340, pp. 121049-121049
Closed Access | Times Cited: 21
A novel model for ultra-short term wind power prediction based on Vision Transformer
Ling Xiang, Xiaomengting Fu, Qingtao Yao, et al.
Energy (2024) Vol. 294, pp. 130854-130854
Closed Access | Times Cited: 13
Wind power forecasting method of large-scale wind turbine clusters based on DBSCAN clustering and an enhanced hunter-prey optimization algorithm
Guolian Hou, Junjie Wang, Yuzhen Fan
Energy Conversion and Management (2024) Vol. 307, pp. 118341-118341
Closed Access | Times Cited: 13
Short-Term Power Forecasting of Wind Farm Cluster Based on Global Information Adaptive Perceptual Graph Convolution Network
Mao Yang, Chaoyi Ju, Y. Huang, et al.
IEEE Transactions on Sustainable Energy (2024) Vol. 15, Iss. 3, pp. 2063-2076
Closed Access | Times Cited: 11
Prediction of regional wind power generation using a multi-objective optimized deep learning model with temporal pattern attention
Wenhe Chen, Hanting Zhou, Longsheng Cheng, et al.
Energy (2023) Vol. 278, pp. 127942-127942
Closed Access | Times Cited: 20
A new intelligent hybrid forecasting method for power load considering uncertainty
Guo‐Feng Fan, Ying-Ying Han, Jingjing Wang, et al.
Knowledge-Based Systems (2023) Vol. 280, pp. 111034-111034
Closed Access | Times Cited: 19
Thermoelectric optimization of integrated energy system considering wind-photovoltaic uncertainty, two-stage power-to-gas and ladder-type carbon trading
Jianwei Gao, Qichen Meng, Jiangtao Liu, et al.
Renewable Energy (2023) Vol. 221, pp. 119806-119806
Closed Access | Times Cited: 18
A hybrid PV cluster power prediction model using BLS with GMCC and error correction via RVM considering an improved statistical upscaling technique
Lihong Qiu, Wentao Ma, Xiaoyang Feng, et al.
Applied Energy (2024) Vol. 359, pp. 122719-122719
Closed Access | Times Cited: 5
An ultra-short-term wind power prediction method based on spatial-temporal attention graph convolutional model
Yunlong Lv, Qin Hu, Hang Xu, et al.
Energy (2024) Vol. 293, pp. 130751-130751
Closed Access | Times Cited: 5
Data-Driven Decision-Making for SCUC: An Improved Deep Learning Approach Based on Sample Coding and Seq2Seq Technique
Nan Yang, Juncong Hao, Zhengmao Li, et al.
Protection and Control of Modern Power Systems (2025) Vol. 10, Iss. 2, pp. 13-24
Open Access
Day-ahead wind farm cluster power prediction based on trend categorization and spatial information integration model
Mao Yang, Yang Jiang, Chuanyu Xu, et al.
Applied Energy (2025) Vol. 388, pp. 125580-125580
Closed Access
A novel multi-gradient evolutionary deep learning approach for few-shot wind power prediction using time-series GAN
Anbo Meng, Hai‐Tao Zhang, Hao Yin, et al.
Energy (2023) Vol. 283, pp. 129139-129139
Closed Access | Times Cited: 14
Spatio-temporal correlation for simultaneous ultra-short-term wind speed prediction at multiple locations
Bowen Yan, Ruifang Shen, Ke Li, et al.
Energy (2023) Vol. 284, pp. 128418-128418
Closed Access | Times Cited: 12
A new distributed decomposition–reconstruction–ensemble learning paradigm for short-term wind power prediction
Xixuan Zhao, Bingzhen Sun, Ruibin Geng
Journal of Cleaner Production (2023) Vol. 423, pp. 138676-138676
Closed Access | Times Cited: 12
Wind power forecasting using a GRU attention model for efficient energy management systems
Lakhdar Nadjib Boucetta, Youssouf Amrane, Saliha Arezki
Electrical Engineering (2024)
Closed Access | Times Cited: 4
A novel spatio-temporal wind speed forecasting method based on the microscale meteorological model and a hybrid deep learning model
Dongqin Zhang, Gang Hu, Jie Song, et al.
Energy (2023) Vol. 288, pp. 129823-129823
Closed Access | Times Cited: 11
Recent advances in data-driven prediction for wind power
Yaxin Liu, Yunjing Wang, Qingtian Wang, et al.
Frontiers in Energy Research (2023) Vol. 11
Open Access | Times Cited: 10
Electricity–gas multi-agent planning method considering users’ comprehensive energy consumption behavior
Wentao Liu, Baorong Zhou, Mingyu Ou, et al.
Frontiers in Energy Research (2024) Vol. 11
Open Access | Times Cited: 3
Ultra-short-term wind power forecasting techniques: comparative analysis and future trends
Guangzheng Yu, Lingxu Shen, Qi Dong, et al.
Frontiers in Energy Research (2024) Vol. 11
Open Access | Times Cited: 3
Ultra-short-term wind power forecasting based on feature weight analysis and cluster dynamic division
Chen Chang, Yuyu Meng, Jiuyuan Huo, et al.
Journal of Renewable and Sustainable Energy (2024) Vol. 16, Iss. 2
Closed Access | Times Cited: 3
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