Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 solar forecasting using Deep Learning and Portfolio Theory integration
Marcello Anderson F. B. Lima, Paulo César Marques de Carvalho, Luis M. Fernández‐Ramírez, et al.
Energy (2020) Vol. 195, pp. 117016-117016
Open Access | Times Cited: 90

Showing 1-25 of 90 citing articles:

Deep learning neural networks for short-term photovoltaic power forecasting
A. Mellit, Alessandro Pavan, Vanni Lughi
Renewable Energy (2021) Vol. 172, pp. 276-288
Closed Access | Times Cited: 245
Fundamentals and business model for resource aggregator of demand response in electricity markets
Xiaoxing Lu, Kangping Li, Hanchen Xu, et al.
Energy (2020) Vol. 204, pp. 117885-117885
Closed Access | Times Cited: 235
A review and taxonomy of wind and solar energy forecasting methods based on deep learning
Ghadah Alkhayat, Rashid Mehmood
Energy and AI (2021) Vol. 4, pp. 100060-100060
Open Access | Times Cited: 206
Frequency-Domain Decomposition and Deep Learning Based Solar PV Power Ultra-Short-Term Forecasting Model
Jichuan Yan, Lin Hu, Zhao Zhen, et al.
IEEE Transactions on Industry Applications (2021) Vol. 57, Iss. 4, pp. 3282-3295
Closed Access | Times Cited: 114
SolarNet: A hybrid reliable model based on convolutional neural network and variational mode decomposition for hourly photovoltaic power forecasting
Deniz Korkmaz
Applied Energy (2021) Vol. 300, pp. 117410-117410
Closed Access | Times Cited: 110
Ridge regression ensemble of machine learning models applied to solar and wind forecasting in Brazil and Spain
Tatiane Carolyne Carneiro, Paulo Alexandre Costa Rocha, Paulo César Marques de Carvalho, et al.
Applied Energy (2022) Vol. 314, pp. 118936-118936
Closed Access | Times Cited: 90
Short-Term Solar Power Predicting Model Based on Multi-Step CNN Stacked LSTM Technique
Neethu Elizabeth Michael, Manohar Mishra, Shazia Hasan, et al.
Energies (2022) Vol. 15, Iss. 6, pp. 2150-2150
Open Access | Times Cited: 77
Multi-timescale photovoltaic power forecasting using an improved Stacking ensemble algorithm based LSTM-Informer model
Yisheng Cao, Gang Liu, Dong–Hua Luo, et al.
Energy (2023) Vol. 283, pp. 128669-128669
Closed Access | Times Cited: 75
Energy digitalization: Main categories, applications, merits, and barriers
A.G. Olabi, Mohammad Ali Abdelkareem, Hussam Jouhara
Energy (2023) Vol. 271, pp. 126899-126899
Closed Access | Times Cited: 53
A review of the applications of artificial intelligence in renewable energy systems: An approach-based study
Mersad Shoaei, Younes Noorollahi, Ahmad Hajinezhad, et al.
Energy Conversion and Management (2024) Vol. 306, pp. 118207-118207
Closed Access | Times Cited: 53
Multi-scale solar radiation and photovoltaic power forecasting with machine learning algorithms in urban environment: A state-of-the-art review
Jia Tian, Ryozo Ooka, Doyun Lee
Journal of Cleaner Production (2023) Vol. 426, pp. 139040-139040
Closed Access | Times Cited: 51
Machine Learning-Based Forecasting of Temperature and Solar Irradiance for Photovoltaic Systems
Wassila Tercha, Sid Ahmed Tadjer, Fathia Chekired, et al.
Energies (2024) Vol. 17, Iss. 5, pp. 1124-1124
Open Access | Times Cited: 19
Efficient solar power generation forecasting for greenhouses: A hybrid deep learning approach
Divyadharshini Venkateswaran, Yongyun Cho
Alexandria Engineering Journal (2024) Vol. 91, pp. 222-236
Open Access | Times Cited: 18
Advanced Automated Machine Learning Framework for Photovoltaic Power Output Prediction Using Environmental Parameters and SHAP Interpretability
Muhammad Paend Bakht, Mohd Norzali Haji Mohd, B. S. K. K. Ibrahim, et al.
Results in Engineering (2025), pp. 103838-103838
Open Access | Times Cited: 3
Deep learning in electrical utility industry: A comprehensive review of a decade of research
Manohar Mishra, Janmenjoy Nayak, Bighnaraj Naik, et al.
Engineering Applications of Artificial Intelligence (2020) Vol. 96, pp. 104000-104000
Closed Access | Times Cited: 97
Solar irradiance forecasting based on direct explainable neural network
Huaizhi Wang, Cai Ren, Bin Zhou, et al.
Energy Conversion and Management (2020) Vol. 226, pp. 113487-113487
Closed Access | Times Cited: 88
Neuro-fuzzy resource forecast in site suitability assessment for wind and solar energy: A mini review
Paul A. Adedeji, Stephen A. Akinlabi, Nkosinathi Madushele, et al.
Journal of Cleaner Production (2020) Vol. 269, pp. 122104-122104
Closed Access | Times Cited: 81
Comparison of machine learning and deep learning algorithms for hourly global/diffuse solar radiation predictions
Olusola Bamisile, Ariyo Oluwasanmi, Chukwuebuka Joseph Ejiyi, et al.
International Journal of Energy Research (2021) Vol. 46, Iss. 8, pp. 10052-10073
Open Access | Times Cited: 79
Evolutionary artificial neural networks for accurate solar radiation prediction
David Guijo-Rubio, Antonio Manuel Durán-Rosal, Pedro Antonio Gutiérrez, et al.
Energy (2020) Vol. 210, pp. 118374-118374
Closed Access | Times Cited: 76
Review on Photovoltaic Power and Solar Resource Forecasting: Current Status and Trends
Tatiane Carolyne Carneiro, Paulo César Marques de Carvalho, Heron Alves dos Santos, et al.
Journal of Solar Energy Engineering (2021) Vol. 144, Iss. 1
Closed Access | Times Cited: 58
Computationally expedient Photovoltaic power Forecasting: A LSTM ensemble method augmented with adaptive weighting and data segmentation technique
Razin Ahmed, Victor Sreeram, Roberto Togneri, et al.
Energy Conversion and Management (2022) Vol. 258, pp. 115563-115563
Closed Access | Times Cited: 57
Systematic Review on Impact of Different Irradiance Forecasting Techniques for Solar Energy Prediction
Konduru Sudharshan, C. Naveen, Pradeep Vishnuram, et al.
Energies (2022) Vol. 15, Iss. 17, pp. 6267-6267
Open Access | Times Cited: 41
Short-Term Solar Irradiance Forecasting Using Deep Learning Techniques: A Comprehensive Case Study
Salwan Tajjour, Shyam Singh Chandel, Majed A. Alotaibi, et al.
IEEE Access (2023) Vol. 11, pp. 119851-119861
Open Access | Times Cited: 24
A cross-sectional survey of deterministic PV power forecasting: Progress and limitations in current approaches
Andreea Săbăduş, Robert Blaga, Sergiu-Mihai Hategan, et al.
Renewable Energy (2024) Vol. 226, pp. 120385-120385
Closed Access | Times Cited: 14
Optimization of electricity generation and assessment of provincial grid emission factors from 2020 to 2060 in China
Min Jia, Zhe Zhang, Li Zhang, et al.
Applied Energy (2024) Vol. 373, pp. 123838-123838
Closed Access | Times Cited: 9
Page 1 - Next Page

Scroll to top