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:

Short-term solar power forecasting: Investigating the ability of deep learning models to capture low-level utility-scale Photovoltaic system behaviour
Armand A. du Plessis, J.M. Strauss, Arnold Rix
Applied Energy (2021) Vol. 285, pp. 116395-116395
Closed Access | Times Cited: 63

Showing 1-25 of 63 citing articles:

Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the context of smart grid paradigm
Tanveer Ahmad, Rafał Madoński, Dongdong Zhang, et al.
Renewable and Sustainable Energy Reviews (2022) Vol. 160, pp. 112128-112128
Closed Access | Times Cited: 343
State-of-the-art review on energy and load forecasting in microgrids using artificial neural networks, machine learning, and deep learning techniques
Raniyah Wazirali, Elnaz Yaghoubi, Mohammed Shadi S. Abujazar, et al.
Electric Power Systems Research (2023) Vol. 225, pp. 109792-109792
Closed Access | Times Cited: 110
A hybrid attention-based deep learning approach for wind power prediction
Zhengjing Ma, Gang Mei
Applied Energy (2022) Vol. 323, pp. 119608-119608
Closed Access | Times Cited: 96
Machine learning for forecasting a photovoltaic (PV) generation system
Connor Scott, Mominul Ahsan, Alhussein Albarbar
Energy (2023) Vol. 278, pp. 127807-127807
Open Access | Times Cited: 67
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
Photovoltaic systems operation and maintenance: A review and future directions
Hind Abdulla, Andrei Sleptchenko, Ammar Nayfeh
Renewable and Sustainable Energy Reviews (2024) Vol. 195, pp. 114342-114342
Open Access | Times Cited: 25
A State-of-Art-Review on Machine-Learning Based Methods for PV
Giuseppe Marco Tina, Cristina Ventura, Sergio Ferlito, et al.
Applied Sciences (2021) Vol. 11, Iss. 16, pp. 7550-7550
Open Access | Times Cited: 76
Reinforcement learning-based scheduling strategy for energy storage in microgrid
Kunshu Zhou, Kaile Zhou, Shanlin Yang
Journal of Energy Storage (2022) Vol. 51, pp. 104379-104379
Closed Access | Times Cited: 40
Memory long and short term time series network for ultra-short-term photovoltaic power forecasting
Congzhi Huang, Mengyuan Yang
Energy (2023) Vol. 279, pp. 127961-127961
Closed Access | Times Cited: 38
Day-ahead regional solar power forecasting with hierarchical temporal convolutional neural networks using historical power generation and weather data
Maneesha Perera, Julian de Hoog, Kasun Bandara, et al.
Applied Energy (2024) Vol. 361, pp. 122971-122971
Open Access | Times Cited: 13
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: 13
Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review
Mohamed Massaoudi, Inès Chihi, Haitham Abu‐Rub, et al.
IEEE Access (2021) Vol. 9, pp. 136593-136615
Open Access | Times Cited: 50
Multi-resolution, multi-horizon distributed solar PV power forecasting with forecast combinations
Maneesha Perera, Julian de Hoog, Kasun Bandara, et al.
Expert Systems with Applications (2022) Vol. 205, pp. 117690-117690
Open Access | Times Cited: 30
Two-Stage Hybrid Deep Learning With Strong Adaptability for Detailed Day-Ahead Photovoltaic Power Forecasting
Jianjing Li, Chenghui Zhang, Bo Sun
IEEE Transactions on Sustainable Energy (2022) Vol. 14, Iss. 1, pp. 193-205
Closed Access | Times Cited: 30
Weighted fully-connected regression networks for one-day-ahead hourly photovoltaic power forecasting
Linfei Yin, Xinghui Cao, Dongduan Liu
Applied Energy (2022) Vol. 332, pp. 120527-120527
Closed Access | Times Cited: 29
Multitasking recurrent neural network for photovoltaic power generation prediction
Hui Song, Nameer Al Khafaf, Ammar Mansoor Kamoona, et al.
Energy Reports (2023) Vol. 9, pp. 369-376
Open Access | Times Cited: 21
An enhanced CNN-LSTM based multi-stage framework for PV and load short-term forecasting: DSO scenarios
Mohammad Ahmad A. Al-Ja’Afreh, Geev Mokryani, Bilal Amjad
Energy Reports (2023) Vol. 10, pp. 1387-1408
Open Access | Times Cited: 21
Quantile-transformed multi-attention residual framework (QT-MARF) for medium-term PV and wind power prediction
Adeel Feroz Mirza, Zhaokun Shu, Muhammad Usman, et al.
Renewable Energy (2023) Vol. 220, pp. 119604-119604
Closed Access | Times Cited: 19
Artificial Intelligence and Mathematical Models of Power Grids Driven by Renewable Energy Sources: A Survey
Sabarathinam Srinivasan, Suresh Kumarasamy, Zacharias Andreadakis, et al.
Energies (2023) Vol. 16, Iss. 14, pp. 5383-5383
Open Access | Times Cited: 17
Forecasting solar energy production in Spain: A comparison of univariate and multivariate models at the national level
Tomás Cabello-López, Manuel Carranza-García, José C. Riquelme, et al.
Applied Energy (2023) Vol. 350, pp. 121645-121645
Open Access | Times Cited: 17
Machine Learning Approaches to Predict Electricity Production from Renewable Energy Sources
Adam Krechowicz, Maria Krechowicz, Katarzyna Poczęta
Energies (2022) Vol. 15, Iss. 23, pp. 9146-9146
Open Access | Times Cited: 26
Long-term power forecasting using FRNN and PCA models for calculating output parameters in solar photovoltaic generation
Hussein A. Kazem, Jabar H. Yousif, Miqdam T. Chaichan, et al.
Heliyon (2022) Vol. 8, Iss. 1, pp. e08803-e08803
Open Access | Times Cited: 22
Artificial Intelligence for Hosting Capacity Analysis: A Systematic Literature Review
Md Tariqul Islam, M. J. Hossain
Energies (2023) Vol. 16, Iss. 4, pp. 1864-1864
Open Access | Times Cited: 14
ANN-LSTM Based Tool For Photovoltaic Power Forecasting.
Younes Zahraoui, Tarmo Korõtko, Saad Mekhilef, et al.
(2024), pp. 1-6
Closed Access | Times Cited: 5
The Performance Effect of Seasonality Feature in Solar Photovoltaic Power Prediction Using Machine Learning
Ghalia Nassreddine, Amal El Arid, Mohamad Nassereddine, et al.
Lecture notes in electrical engineering (2025), pp. 167-183
Closed Access
Page 1 - Next Page

Scroll to top