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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 review of behind-the-meter solar forecasting
Burcin Cakir Erdener, Cong Feng, Kate Doubleday, et al.
Renewable and Sustainable Energy Reviews (2022) Vol. 160, pp. 112224-112224
Open Access | Times Cited: 47

Showing 1-25 of 47 citing articles:

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: 44
Dynamic directed graph convolution network based ultra‐short‐term forecasting method of distributed photovoltaic power to enhance the resilience and flexibility of distribution network
Yuqing Wang, Wenjie Fu, Xudong Zhang, et al.
IET Generation Transmission & Distribution (2023) Vol. 18, Iss. 2, pp. 337-352
Open Access | Times Cited: 34
Advances and prospects on estimating solar photovoltaic installation capacity and potential based on satellite and aerial images
Hongzhi Mao, Xie Chen, Yongqiang Luo, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 179, pp. 113276-113276
Open Access | Times Cited: 29
The value of solar forecasts and the cost of their errors: A review
Oktoviano Gandhi, Wenjie Zhang, Dhivya Sampath Kumar, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 189, pp. 113915-113915
Closed Access | Times Cited: 26
A regional solar forecasting approach using generative adversarial networks with solar irradiance maps
Haoran Wen, Yang Du, Xiaoyang Chen, et al.
Renewable Energy (2023) Vol. 216, pp. 119043-119043
Open Access | Times Cited: 23
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: 16
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: 16
Solar Radiation Forecasting: A Systematic Meta-Review of Current Methods and Emerging Trends
Ewa Chodakowska, Joanicjusz Nazarko, Łukasz Nazarko, et al.
Energies (2024) Vol. 17, Iss. 13, pp. 3156-3156
Open Access | Times Cited: 12
Ultra-short-term distributed PV power forecasting for virtual power plant considering data-scarce scenarios
Yuqing Wang, Wenjie Fu, Junlong Wang, et al.
Applied Energy (2024) Vol. 373, pp. 123890-123890
Closed Access | Times Cited: 8
Machine learning for modern power distribution systems: Progress and perspectives
Marija Marković, Matthew Bossart, Bri‐Mathias Hodge
Journal of Renewable and Sustainable Energy (2023) Vol. 15, Iss. 3
Open Access | Times Cited: 15
Short-term net load forecast in distribution networks with PV penetration behind the meter
Alberto Falces, Candido Capellan-Villacian, Montserrat Mendoza-Villena, et al.
Energy Reports (2023) Vol. 9, pp. 115-122
Open Access | Times Cited: 14
Nonintrusive Load Disaggregation Based on Attention Neural Networks
Shunfu Lin, Jiayu Yang, Yi Li, et al.
International Transactions on Electrical Energy Systems (2025) Vol. 2025, Iss. 1
Open Access
Quantifying spatio-temporal carbon intensity within a city using large-scale smart meter data: Unveiling the impact of behind-the-meter generation
Soma Sugano, Yu Fujimoto, Yuto Ihara, et al.
Applied Energy (2025) Vol. 383, pp. 125373-125373
Open Access
Load Identification with Photovoltaic Distributed Generation and a Novel Public High-Frequency Dataset
Everton Luiz de Aguiar, Ricardo Bernardi, André Eugênio Lazzaretti, et al.
Journal of Control Automation and Electrical Systems (2025)
Open Access
Swin transformer-based transferable PV forecasting for new PV sites with insufficient PV generation data
Shijie Xu, Hui Ma, Chandima Ekanayake, et al.
Renewable Energy (2025), pp. 122824-122824
Closed Access
Parametric Forecast of Solar Energy over Time by Applying Machine Learning Techniques: Systematic Review
Fernando Venâncio Mucomole, Carlos Silva, Lourenço Lázaro Magaia
Energies (2025) Vol. 18, Iss. 6, pp. 1460-1460
Open Access
Short-term photovoltaic power prediction based on CEEMDAN-PE and BiLSTM neural network
Jian-Wei Liang, Liying Yin, Yanli Xin, et al.
Electric Power Systems Research (2025) Vol. 246, pp. 111706-111706
Closed Access
Load forecasting model considering dynamic coupling relationships using structured dynamic-inner latent variables and broad learning system
Ziwen Gu, Yatao Shen, Zijian Wang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108180-108180
Closed Access | Times Cited: 3
A Comprehensive Review of Behind-the-Meter Distributed Energy Resources Load Forecasting: Models, Challenges, and Emerging Technologies
Aydin Zaboli, Swetha Rani Kasimalla, Kuchan Park, et al.
Energies (2024) Vol. 17, Iss. 11, pp. 2534-2534
Open Access | Times Cited: 3
A Hybrid Dual Stream ProbSparse Self-Attention Network for spatial–temporal photovoltaic power forecasting
Jingyin Pei, Yunxuan Dong, Peiting Guo, et al.
Energy (2024) Vol. 305, pp. 132152-132152
Closed Access | Times Cited: 3
Detecting Photovoltaic Installations in Diverse Landscapes Using Open Multi-Source Remote Sensing Data
Jinyue Wang, Jing Liu, Longhui Li
Remote Sensing (2022) Vol. 14, Iss. 24, pp. 6296-6296
Open Access | Times Cited: 12
Deep hybrid neural net (DHN-Net) for minute-level day-ahead solar and wind power forecast in a decarbonized power system
Olusola Bamisile, Dongsheng Cai, Humphrey Adun, et al.
Energy Reports (2023) Vol. 9, pp. 1163-1172
Open Access | Times Cited: 7
Short‐term prediction of behind‐the‐meter PV power based on attention‐LSTM and transfer learning
Jinjiang Zhang, L. Jeff Hong, Shamsuddeen Nyako Ibrahim, et al.
IET Renewable Power Generation (2023) Vol. 18, Iss. 3, pp. 321-330
Open Access | Times Cited: 7
Distributed-regional photovoltaic power generation prediction with limited data: A robust autoregressive transfer learning method
Wanting Zheng, Hao Xiao, Wei Pei
Applied Energy (2024) Vol. 380, pp. 125058-125058
Closed Access | Times Cited: 2
Self-supervised learning method for consumer-level behind-the-meter PV estimation
Chao Charles Liu, Hongkun Chen, Jing Shi, et al.
Applied Energy (2022) Vol. 326, pp. 119961-119961
Closed Access | Times Cited: 11
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