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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:

Probabilistic Residential Load Forecasting Based on Micrometeorological Data and Customer Consumption Pattern
Lilin Cheng, Haixiang Zang, Yan Xu, et al.
IEEE Transactions on Power Systems (2021) Vol. 36, Iss. 4, pp. 3762-3775
Closed Access | Times Cited: 51

Showing 1-25 of 51 citing articles:

Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects
Mohamed Massaoudi, Haitham Abu‐Rub, Shady S. Refaat, et al.
IEEE Access (2021) Vol. 9, pp. 54558-54578
Open Access | Times Cited: 132
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: 84
A Transformer-based multimodal-learning framework using sky images for ultra-short-term solar irradiance forecasting
Jingxuan Liu, Haixiang Zang, Lilin Cheng, et al.
Applied Energy (2023) Vol. 342, pp. 121160-121160
Closed Access | Times Cited: 65
A comprehensive review on deep learning approaches for short-term load forecasting
Yavuz Eren, İbrahim Beklan Küçükdemiral
Renewable and Sustainable Energy Reviews (2023) Vol. 189, pp. 114031-114031
Open Access | Times Cited: 65
A hybrid framework for short term load forecasting with a navel feature engineering and adaptive grasshopper optimization in smart grid
M. Zulfiqar, Muhammad Kamran, Muhammad Babar Rasheed, et al.
Applied Energy (2023) Vol. 338, pp. 120829-120829
Open Access | Times Cited: 22
Dynamic Temporal Dependency Model for Multiple Steps Ahead Short-Term Load Forecasting of Power System
Bozhen Jiang, Hongyuan Yang, Yidi Wang, et al.
IEEE Transactions on Industry Applications (2024) Vol. 60, Iss. 4, pp. 5244-5254
Closed Access | Times Cited: 12
A Multitask Integrated Deep-Learning Probabilistic Prediction for Load Forecasting
Jianzhou Wang, Kang Wang, Zhiwu Li, et al.
IEEE Transactions on Power Systems (2023) Vol. 39, Iss. 1, pp. 1240-1250
Closed Access | Times Cited: 17
Multi-type load forecasting model based on random forest and density clustering with the influence of noise and load patterns
Song Deng, Xia Dong, Tao Li, et al.
Energy (2024) Vol. 307, pp. 132635-132635
Closed Access | Times Cited: 7
Enhancing multivariate, multi-step residential load forecasting with spatiotemporal graph attention-enabled transformer
Pengfei Zhao, Weihao Hu, Di Cao, et al.
International Journal of Electrical Power & Energy Systems (2024) Vol. 160, pp. 110074-110074
Open Access | Times Cited: 5
Mismatch analysis of rooftop photovoltaics supply and farmhouse load: Data dimensionality reduction and explicable load pattern mining via hybrid deep learning
Ding Gao, Yuan Zhi, Xing Rong, et al.
Applied Energy (2024) Vol. 377, pp. 124520-124520
Closed Access | Times Cited: 5
An Integrated Stacking Ensemble Model for Natural Gas Purchase Prediction Incorporating Multiple Features
Junjie Wang, Lei Jiang, Le Zhang, et al.
Applied Sciences (2025) Vol. 15, Iss. 2, pp. 778-778
Open Access
A Novel Hybrid Method for Short-Term Probabilistic Load Forecasting in Distribution Networks
Bingzhi Wang, Mahdi Mazhari, C. Y. Chung
IEEE Transactions on Smart Grid (2022) Vol. 13, Iss. 5, pp. 3650-3661
Closed Access | Times Cited: 19
A Load Forecasting Framework Considering Hybrid Ensemble Deep Learning With Two-Stage Load Decomposition
Sisi Zhou, Yong Li, Yixiu Guo, et al.
IEEE Transactions on Industry Applications (2024) Vol. 60, Iss. 3, pp. 4568-4582
Closed Access | Times Cited: 4
Characterizing residential load patterns on multi-time scales utilizing LSTM autoencoder and electricity consumption data
Wei Yang, Xin‐Hao Li, Chao Chen, et al.
Sustainable Cities and Society (2022) Vol. 84, pp. 104007-104007
Closed Access | Times Cited: 18
MSGCN-ISTL: A multi-scaled self-attention-enhanced graph convolutional network with improved STL decomposition for probabilistic load forecasting
Yilei Qiu, Zhou He, Wenyu Zhang, et al.
Expert Systems with Applications (2023) Vol. 238, pp. 121737-121737
Closed Access | Times Cited: 9
The predictive management in campus heating system based on deep reinforcement learning and probabilistic heat demands forecasting
Minghao Chen, Zhiyuan Xie, Yi Sun‡, et al.
Applied Energy (2023) Vol. 350, pp. 121710-121710
Closed Access | Times Cited: 8
Consumption Scenario-Based Probabilistic Load Forecasting of Single Household
Zhong Xia, Hui Ma, Tapan Kumar Saha, et al.
IEEE Transactions on Smart Grid (2021) Vol. 13, Iss. 2, pp. 1075-1087
Closed Access | Times Cited: 19
Accurate Solar Pv Power Prediction Interval Method Based on Frequency-Domain Decomposition and Lstm Model
Lining Wang, Mingxuan Mao, Jili Xie, et al.
SSRN Electronic Journal (2022)
Closed Access | Times Cited: 13
Advancements in Household Load Forecasting: Deep Learning Model with Hyperparameter Optimization
Hamdi A. Al-Jamimi, Galal M. BinMakhashen, Muhammed Y. Worku, et al.
Electronics (2023) Vol. 12, Iss. 24, pp. 4909-4909
Open Access | Times Cited: 7
TADNet: Temporal Attention Decomposition Networks for Probabilistic Energy Forecasting
Jiarui Ye, Bo Zhao, Derong Liu, et al.
IEEE Transactions on Power Systems (2024) Vol. 39, Iss. 6, pp. 7190-7202
Closed Access | Times Cited: 2
Case study of a landslide continuous probability rainfall threshold analysis based on the prediction interval principle
Yu Huang, Cuizhu Zhao, Xiaoyan Jin, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 6
Residential Load Forecasting: An Online-Offline Deep Kernel Learning Method
Yuanzheng Li, Fu-Shen Zhang, Yun Liu, et al.
IEEE Transactions on Power Systems (2023) Vol. 39, Iss. 2, pp. 4264-4278
Closed Access | Times Cited: 5
A residential load forecasting method for multi-attribute adversarial learning considering multi-source uncertainties
Yongxin Su, Qiyao He, Jie Chen, et al.
International Journal of Electrical Power & Energy Systems (2023) Vol. 154, pp. 109421-109421
Open Access | Times Cited: 5
Stacking strategy-assisted random forest algorithm and its application
Kun Wang, Jinggeng Gao, Hu Li, et al.
AIP Advances (2023) Vol. 13, Iss. 3
Open Access | Times Cited: 3
Novel Single Group-Based Indirect Customer Baseline Load Calculation Method for Residential Demand Response
Hyun-Yong Lee, Hyunseok Jang, Seung-Hun Oh, et al.
IEEE Access (2021) Vol. 9, pp. 140881-140895
Open Access | Times Cited: 6
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