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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:

Improving Renewable Energy Forecasting With a Grid of Numerical Weather Predictions
José Andrade, Ricardo J. Bessa
IEEE Transactions on Sustainable Energy (2017) Vol. 8, Iss. 4, pp. 1571-1580
Open Access | Times Cited: 247

Showing 1-25 of 247 citing articles:

A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids
Sheraz Aslam, Herodotos Herodotou, Syed Muhammad Mohsin, et al.
Renewable and Sustainable Energy Reviews (2021) Vol. 144, pp. 110992-110992
Closed Access | Times Cited: 397
A review and discussion of decomposition-based hybrid models for wind energy forecasting applications
Zheng Qian, Yan Pei, Hamidreza Zareipour, et al.
Applied Energy (2018) Vol. 235, pp. 939-953
Closed Access | Times Cited: 332
Grid integrated renewable DG systems: A review of power quality challenges and state‐of‐the‐art mitigation techniques
Mohit Bajaj, Amit Kumar Singh
International Journal of Energy Research (2019) Vol. 44, Iss. 1, pp. 26-69
Open Access | Times Cited: 256
The future of forecasting for renewable energy
C. Sweeney, Ricardo J. Bessa, Jethro Browell, et al.
Wiley Interdisciplinary Reviews Energy and Environment (2019) Vol. 9, Iss. 2
Open Access | Times Cited: 215
Improved solar photovoltaic energy generation forecast using deep learning-based ensemble stacking approach
Waqas Khan, Shalika Walker, Wim Zeiler
Energy (2021) Vol. 240, pp. 122812-122812
Open Access | Times Cited: 210
Energy consumption forecasting based on Elman neural networks with evolutive optimization
L. G. B. Ruiz, R. Rueda, Manuel Pegalájar Cuéllar, et al.
Expert Systems with Applications (2017) Vol. 92, pp. 380-389
Closed Access | Times Cited: 181
A Survey of Machine Learning Models in Renewable Energy Predictions
Jung-Pin Lai, Yu-Ming Chang, Chieh-Huang Chen, et al.
Applied Sciences (2020) Vol. 10, Iss. 17, pp. 5975-5975
Open Access | Times Cited: 153
Retracted: Weather forecasting and prediction using hybrid C5.0 machine learning algorithm
Sudhan M.B, Anitha Thavasimuthu, M. Aruna, et al.
International Journal of Communication Systems (2021) Vol. 34, Iss. 10
Closed Access | Times Cited: 140
Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges
Peng Lu, Lin Ye, Yongning Zhao, et al.
Applied Energy (2021) Vol. 301, pp. 117446-117446
Closed Access | Times Cited: 131
An interpretable probabilistic model for short-term solar power forecasting using natural gradient boosting
Georgios Mitrentsis, Hendrik Lens
Applied Energy (2022) Vol. 309, pp. 118473-118473
Open Access | Times Cited: 100
Uncovering wind power forecasting uncertainty sources and their propagation through the whole modelling chain
Jie Yan, Corinna Möhrlen, Tuhfe Göçmen, et al.
Renewable and Sustainable Energy Reviews (2022) Vol. 165, pp. 112519-112519
Open Access | Times Cited: 72
Hybrid energy system integration and management for solar energy: A review
Tolulope Olumuyiwa Falope, Liyun Lao, Dawid P. Hanak, et al.
Energy Conversion and Management X (2024) Vol. 21, pp. 100527-100527
Open Access | Times Cited: 48
A novel hybrid model based on Empirical Mode Decomposition and Echo State Network for wind power forecasting
Uğur Yüzgeç, Emrah Dokur, MEHMET EMİN BALCI
Energy (2024) Vol. 300, pp. 131546-131546
Closed Access | Times Cited: 17
Exploring Key Weather Factors From Analytical Modeling Toward Improved Solar Power Forecasting
Jianxiao Wang, Haiwang Zhong, Xiaowen Lai, et al.
IEEE Transactions on Smart Grid (2017) Vol. 10, Iss. 2, pp. 1417-1427
Closed Access | Times Cited: 157
Forecasting energy consumption and wind power generation using deep echo state network
Huanling Hu, Lin Wang, Sheng-Xiang Lv
Renewable Energy (2020) Vol. 154, pp. 598-613
Closed Access | Times Cited: 126
Wind speed and wind direction forecasting using echo state network with nonlinear functions
Mohammad Amin Chitsazan, M. Sami Fadali, A.M. Trzynadlowski
Renewable Energy (2018) Vol. 131, pp. 879-889
Closed Access | Times Cited: 124
Modeling carbon emission trajectory of China, US and India
Qiang Wang, Shuyu Li, Zhanna Pisarenko
Journal of Cleaner Production (2020) Vol. 258, pp. 120723-120723
Closed Access | Times Cited: 115
The current state of Distributed Renewable Generation, challenges of interconnection and opportunities for energy conversion based DC microgrids
Shahid Ullah, Ahmed M. A. Haidar, P.R.P. Hoole, et al.
Journal of Cleaner Production (2020) Vol. 273, pp. 122777-122777
Closed Access | Times Cited: 112
Wind speed forecasting based on Quantile Regression Minimal Gated Memory Network and Kernel Density Estimation
Zhendong Zhang, Hui Qin, Yongqi Liu, et al.
Energy Conversion and Management (2019) Vol. 196, pp. 1395-1409
Closed Access | Times Cited: 110
A Two-Step Approach to Solar Power Generation Prediction Based on Weather Data Using Machine Learning
Seul Gi Kim, Jae‐Yoon Jung, Min Kyu Sim
Sustainability (2019) Vol. 11, Iss. 5, pp. 1501-1501
Open Access | Times Cited: 104
Distributed Event-Triggered Secondary Control for Economic Dispatch and Frequency Restoration Control of Droop-Controlled AC Microgrids
Zhongwen Li, Zhiping Cheng, Jing Liang, et al.
IEEE Transactions on Sustainable Energy (2019) Vol. 11, Iss. 3, pp. 1938-1950
Closed Access | Times Cited: 104
Probabilistic Wind-Power Forecasting Using Weather Ensemble Models
Yuan‐Kang Wu, Po-En Su, Ting-Yi Wu, et al.
IEEE Transactions on Industry Applications (2018) Vol. 54, Iss. 6, pp. 5609-5620
Closed Access | Times Cited: 101
Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry
Ricardo J. Bessa, Corinna Möhrlen, Vanessa Fundel, et al.
Energies (2017) Vol. 10, Iss. 9, pp. 1402-1402
Open Access | Times Cited: 100
Short-Term Forecasting of Photovoltaic Solar Power Production Using Variational Auto-Encoder Driven Deep Learning Approach
Abdelkader Dairi, Fouzi Harrou, Ying Sun, et al.
Applied Sciences (2020) Vol. 10, Iss. 23, pp. 8400-8400
Open Access | Times Cited: 98
Unsupervised Clustering-Based Short-Term Solar Forecasting
Cong Feng, Mingjian Cui, Bri‐Mathias Hodge, et al.
IEEE Transactions on Sustainable Energy (2018) Vol. 10, Iss. 4, pp. 2174-2185
Open Access | Times Cited: 97
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