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:

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: 234

Showing 1-25 of 234 citing articles:

Accurate one step and multistep forecasting of very short-term PV power using LSTM-TCN model
Tariq Limouni, Reda Yaagoubi, K. Bouziane, et al.
Renewable Energy (2023) Vol. 205, pp. 1010-1024
Closed Access | Times Cited: 150
A deep LSTM network for the Spanish electricity consumption forecasting
J. F. Torres, Francisco Martínez–Álvarez, Alicia Troncoso
Neural Computing and Applications (2022) Vol. 34, Iss. 13, pp. 10533-10545
Open Access | Times Cited: 87
Accurate solar PV power prediction interval method based on frequency-domain decomposition and LSTM model
Lining Wang, Mingxuan Mao, Jili Xie, et al.
Energy (2022) Vol. 262, pp. 125592-125592
Closed Access | Times Cited: 83
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
Metaheuristic-Based Hyperparameter Tuning for Recurrent Deep Learning: Application to the Prediction of Solar Energy Generation
Cătălin Stoean, Miodrag Živković, Aleksandra Bozovic, et al.
Axioms (2023) Vol. 12, Iss. 3, pp. 266-266
Open Access | Times Cited: 58
A hybrid deep learning model with an optimal strategy based on improved VMD and transformer for short-term photovoltaic power forecasting
Xinyu Wang, Wenping Ma
Energy (2024) Vol. 295, pp. 131071-131071
Closed Access | Times Cited: 24
Short-term PV power prediction based on meteorological similarity days and SSA-BiLSTM
Yikang Li, Wei Huang, Keying Lou, et al.
Systems and Soft Computing (2024) Vol. 6, pp. 200084-200084
Open Access | Times Cited: 17
Multi-step photovoltaic power forecasting using transformer and recurrent neural networks
Jimin Kim, Josue Obregon, Hoonseok Park, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 200, pp. 114479-114479
Closed Access | Times Cited: 16
Combining transfer learning and constrained long short-term memory for power generation forecasting of newly-constructed photovoltaic plants
Xing Luo, Dongxiao Zhang, Xu Zhu
Renewable Energy (2021) Vol. 185, pp. 1062-1077
Open Access | Times Cited: 61
Photovoltaic systems and sustainable communities: New social models for ecological transition. The impact of incentive policies in profitability analyses
Idiano D’Adamo, Marco Mammetti, Dario Ottaviani, et al.
Renewable Energy (2022) Vol. 202, pp. 1291-1304
Open Access | Times Cited: 61
Short-term photovoltaic power forecasting based on signal decomposition and machine learning optimization
Yilin Zhou, Jianzhou Wang, Zhiwu Li, et al.
Energy Conversion and Management (2022) Vol. 267, pp. 115944-115944
Closed Access | Times Cited: 58
Outlet water temperature prediction of energy pile based on spatial-temporal feature extraction through CNN–LSTM hybrid model
Weiyi Zhang, Haiyang Zhou, Xiaohua Bao, et al.
Energy (2022) Vol. 264, pp. 126190-126190
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: 55
Application of Temporal Fusion Transformer for Day-Ahead PV Power Forecasting
Miguel López Santos, Xela García‐Santiago, Fernando Echevarría Camarero, et al.
Energies (2022) Vol. 15, Iss. 14, pp. 5232-5232
Open Access | Times Cited: 54
Towards efficient and effective renewable energy prediction via deep learning
Zulfiqar Ahmad Khan, Tanveer Hussain, Ijaz Ul Haq, et al.
Energy Reports (2022) Vol. 8, pp. 10230-10243
Open Access | Times Cited: 51
Deep neural network for forecasting of photovoltaic power based on wavelet packet decomposition with similar day analysis
Xiangjie Liu, Yuanyan Liu, Xiaobing Kong, et al.
Energy (2023) Vol. 271, pp. 126963-126963
Closed Access | Times Cited: 39
A hybrid photovoltaic/wind power prediction model based on Time2Vec, WDCNN and BiLSTM
Donghan Geng, Bo Wang, Qi Gao
Energy Conversion and Management (2023) Vol. 291, pp. 117342-117342
Closed Access | Times Cited: 39
An integrated framework of gated recurrent unit based on improved sine cosine algorithm for photovoltaic power forecasting
Huixin Ma, Chu Zhang, Peng Tian, et al.
Energy (2022) Vol. 256, pp. 124650-124650
Closed Access | Times Cited: 38
Review on the Application of Photovoltaic Forecasting Using Machine Learning for Very Short- to Long-Term Forecasting
Putri Nor Liyana Mohamad Radzi, Muhammad Naveed Akhter, Saad Mekhilef, et al.
Sustainability (2023) Vol. 15, Iss. 4, pp. 2942-2942
Open Access | Times Cited: 33
Improving PV power plant forecast accuracy: A hybrid deep learning approach compared across short, medium, and long-term horizons
Delnia Sadeghi, Aminabbas Golshanfard, Shahab Eslami, et al.
Renewable energy focus (2023) Vol. 45, pp. 242-258
Closed Access | Times Cited: 32
Historical PV-output characteristic extraction based weather-type classification strategy and its forecasting method for the day-ahead prediction of PV output
Lingwei Zheng, Ran Su, Xinyu Sun, et al.
Energy (2023) Vol. 271, pp. 127009-127009
Closed Access | Times Cited: 25
Ultra-short-term multi-step probability interval prediction of photovoltaic power: A framework with time-series-segment feature analysis
Lei Zhang, Ye He, Hongbin Wu, et al.
Solar Energy (2023) Vol. 260, pp. 71-82
Closed Access | Times Cited: 22
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
Forecasting Solar Photovoltaic Power Production: A Comprehensive Review and Innovative Data-Driven Modeling Framework
Sameer Al‐Dahidi, Manoharan Madhiarasan, Loiy Al‐Ghussain, et al.
Energies (2024) Vol. 17, Iss. 16, pp. 4145-4145
Open Access | Times Cited: 13
Artificial Neural Networks for Photovoltaic Power Forecasting: A Review of Five Promising Models
Rafiq Asghar, Francesco Riganti Fulginei, Michele Quercio, et al.
IEEE Access (2024) Vol. 12, pp. 90461-90485
Open Access | Times Cited: 11
Page 1 - Next Page

Scroll to top