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OpenAlex Citation Counts

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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:

A guideline to solar forecasting research practice: Reproducible, operational, probabilistic or physically-based, ensemble, and skill (ROPES)
Dazhi Yang
Journal of Renewable and Sustainable Energy (2019) Vol. 11, Iss. 2
Closed Access | Times Cited: 122

Showing 1-25 of 122 citing articles:

Energy Forecasting: A Review and Outlook
Tao Hong, Pierre Pinson, Yi Wang, et al.
IEEE Open Access Journal of Power and Energy (2020) Vol. 7, pp. 376-388
Open Access | Times Cited: 414
Extensive comparison of physical models for photovoltaic power forecasting
Martin János Mayer, Gyula Gróf
Applied Energy (2020) Vol. 283, pp. 116239-116239
Open Access | Times Cited: 260
Comparison of machine learning methods for photovoltaic power forecasting based on numerical weather prediction
Dávid Markovics, Martin János Mayer
Renewable and Sustainable Energy Reviews (2022) Vol. 161, pp. 112364-112364
Open Access | Times Cited: 229
Verification of deterministic solar forecasts
Dazhi Yang, Stefano Alessandrini, J. Antonanzas, et al.
Solar Energy (2020) Vol. 210, pp. 20-37
Open Access | Times Cited: 193
A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality
Dazhi Yang, Meng Wan, Christian A. Gueymard, et al.
Renewable and Sustainable Energy Reviews (2022) Vol. 161, pp. 112348-112348
Closed Access | Times Cited: 179
Photovoltaic power forecasting: A hybrid deep learning model incorporating transfer learning strategy
Yugui Tang, Kuo Yang, Shujing Zhang, et al.
Renewable and Sustainable Energy Reviews (2022) Vol. 162, pp. 112473-112473
Closed Access | Times Cited: 88
Convolutional neural networks for intra-hour solar forecasting based on sky image sequences
Cong Feng, Jie Zhang, Wenqi Zhang, et al.
Applied Energy (2022) Vol. 310, pp. 118438-118438
Open Access | Times Cited: 87
Benefits of physical and machine learning hybridization for photovoltaic power forecasting
Martin János Mayer
Renewable and Sustainable Energy Reviews (2022) Vol. 168, pp. 112772-112772
Open Access | Times Cited: 81
LOWESS smoothing and Random Forest based GRU model: A short-term photovoltaic power generation forecasting method
Yeming Dai, Yanxin Wang, Mingming Leng, et al.
Energy (2022) Vol. 256, pp. 124661-124661
Closed Access | Times Cited: 75
Trends and gaps in photovoltaic power forecasting with machine learning
Alba Alcañiz, Daniel Grzebyk, Hesan Ziar, et al.
Energy Reports (2022) Vol. 9, pp. 447-471
Open Access | Times Cited: 74
A Concise Overview on Solar Resource Assessment and Forecasting
Dazhi Yang, Meng Wan, Xiangao Xia
Advances in Atmospheric Sciences (2022) Vol. 39, Iss. 8, pp. 1239-1251
Open Access | Times Cited: 73
Transfer learning strategies for solar power forecasting under data scarcity
Elissaios Sarmas, Nikos Dimitropoulos, Vangelis Marinakis, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 72
Short-term photovoltaic power forecasting using meta-learning and numerical weather prediction independent Long Short-Term Memory models
Elissaios Sarmas, Evangelos Spiliotis, Efstathios Stamatopoulos, et al.
Renewable Energy (2023) Vol. 216, pp. 118997-118997
Open Access | Times Cited: 66
Advances in solar forecasting: Computer vision with deep learning
Quentin Paletta, Guillermo Terrén-Serrano, Yuhao Nie, et al.
Advances in Applied Energy (2023) Vol. 11, pp. 100150-100150
Open Access | Times Cited: 42
SolarNet: A sky image-based deep convolutional neural network for intra-hour solar forecasting
Cong Feng, Jie Zhang
Solar Energy (2020) Vol. 204, pp. 71-78
Open Access | Times Cited: 124
Deep Learning Based Multistep Solar Forecasting for PV Ramp-Rate Control Using Sky Images
Haoran Wen, Yang Du, Xiaoyang Chen, et al.
IEEE Transactions on Industrial Informatics (2020) Vol. 17, Iss. 2, pp. 1397-1406
Closed Access | Times Cited: 122
Choice of clear-sky model in solar forecasting
Dazhi Yang
Journal of Renewable and Sustainable Energy (2020) Vol. 12, Iss. 2
Closed Access | Times Cited: 105
A Survey of Computational Intelligence Techniques for Wind Power Uncertainty Quantification in Smart Grids
Hao Quan, Abbas Khosravi, Dazhi Yang, et al.
IEEE Transactions on Neural Networks and Learning Systems (2019) Vol. 31, Iss. 11, pp. 4582-4599
Closed Access | Times Cited: 96
Operational day-ahead solar power forecasting for aggregated PV systems with a varying spatial distribution
Lennard Visser, Tarek AlSkaif, Wilfried van Sark
Renewable Energy (2021) Vol. 183, pp. 267-282
Open Access | Times Cited: 91
A comprehensive review and analysis of solar forecasting techniques
Pardeep Singla, Manoj Duhan, Sumit Saroha
Frontiers in Energy (2021) Vol. 16, Iss. 2, pp. 187-223
Closed Access | Times Cited: 90
Review of power system impacts at high PV penetration Part II: Potential solutions and the way forward
Dhivya Sampath Kumar, Oktoviano Gandhi, Carlos D. Rodríguez‐Gallegos, et al.
Solar Energy (2020) Vol. 210, pp. 202-221
Closed Access | Times Cited: 81
A holistic review on energy forecasting using big data and deep learning models
Jayanthi Devaraj, Rajvikram Madurai Elavarasan, GM Shafiullah, et al.
International Journal of Energy Research (2021) Vol. 45, Iss. 9, pp. 13489-13530
Open Access | Times Cited: 80
Post-processing in solar forecasting: Ten overarching thinking tools
Dazhi Yang, Dennis van der Meer
Renewable and Sustainable Energy Reviews (2021) Vol. 140, pp. 110735-110735
Closed Access | Times Cited: 78
PV Power Prediction, Using CNN-LSTM Hybrid Neural Network Model. Case of Study: Temixco-Morelos, México
Mario Tovar, Miguel Robles, Felipe Rashid
Energies (2020) Vol. 13, Iss. 24, pp. 6512-6512
Open Access | Times Cited: 71
A deep learning based hybrid method for hourly solar radiation forecasting
Chun Sing Lai, Cankun Zhong, Keda Pan, et al.
Expert Systems with Applications (2021) Vol. 177, pp. 114941-114941
Closed Access | Times Cited: 67
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