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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.

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Showing 1-25 of 161 citing articles:

Review on probabilistic forecasting of photovoltaic power production and electricity consumption
Dennis van der Meer, Joakim Widén, Joakim Munkhammar
Renewable and Sustainable Energy Reviews (2017) Vol. 81, pp. 1484-1512
Closed Access | Times Cited: 380
Prediction of short-term PV power output and uncertainty analysis
Luyao Liu, Yi Zhao, Dongliang Chang, et al.
Applied Energy (2018) Vol. 228, pp. 700-711
Closed Access | Times Cited: 238
Physical energy and data-driven models in building energy prediction: A review
Yongbao Chen, Mingyue Guo, Zhisen Chen, et al.
Energy Reports (2022) Vol. 8, pp. 2656-2671
Open Access | Times Cited: 192
Short term load forecasting based on phase space reconstruction algorithm and bi-square kernel regression model
Guo‐Feng Fan, Li‐Ling Peng, Wei‐Chiang Hong
Applied Energy (2018) Vol. 224, pp. 13-33
Closed Access | Times Cited: 173
Risk dependence of CoVaR and structural change between oil prices and exchange rates: A time-varying copula model
Qiang Ji, Liu Bing-yue, Ying Fan
Energy Economics (2018) Vol. 77, pp. 80-92
Closed Access | Times Cited: 161
Modeling and Forecasting Short-Term Power Load With Copula Model and Deep Belief Network
Tinghui Ouyang, Yusen He, Huajin Li, et al.
IEEE Transactions on Emerging Topics in Computational Intelligence (2019) Vol. 3, Iss. 2, pp. 127-136
Open Access | Times Cited: 156
A hybrid load forecasting model based on support vector machine with intelligent methods for feature selection and parameter optimization
Yeming Dai, Pei Zhao
Applied Energy (2020) Vol. 279, pp. 115332-115332
Closed Access | Times Cited: 141
A novel ensemble probabilistic forecasting system for uncertainty in wind speed
Jianzhou Wang, Shuai Wang, Bo Zeng, et al.
Applied Energy (2022) Vol. 313, pp. 118796-118796
Closed Access | Times Cited: 77
The volatility of global energy uncertainty: Renewable alternatives
Cem Işık, Bekhzod Kuziboev, Serdar Ongan, et al.
Energy (2024) Vol. 297, pp. 131250-131250
Closed Access | Times Cited: 43
Power load probability density forecasting using Gaussian process quantile regression
Yandong Yang, Shufang Li, Wenqi Li, et al.
Applied Energy (2017) Vol. 213, pp. 499-509
Closed Access | Times Cited: 167
Probability density forecasting of wind power using quantile regression neural network and kernel density estimation
Yaoyao He, Haiyan Li
Energy Conversion and Management (2018) Vol. 164, pp. 374-384
Closed Access | Times Cited: 158
Electricity consumption probability density forecasting method based on LASSO-Quantile Regression Neural Network
Yaoyao He, Qin Yang, Shuo Wang, et al.
Applied Energy (2018) Vol. 233-234, pp. 565-575
Open Access | Times Cited: 139
Probabilistic forecasting of electricity consumption, photovoltaic power generation and net demand of an individual building using Gaussian Processes
Dennis van der Meer, Mahmoud Shepero, Andreas Svensson, et al.
Applied Energy (2018) Vol. 213, pp. 195-207
Closed Access | Times Cited: 137
An Efficient Approach to Power System Uncertainty Analysis With High-Dimensional Dependencies
Yi Wang, Ning Zhang, Chongqing Kang, et al.
IEEE Transactions on Power Systems (2017) Vol. 33, Iss. 3, pp. 2984-2994
Open Access | Times Cited: 132
Residential probabilistic load forecasting: A method using Gaussian process designed for electric load data
Mahmoud Shepero, Dennis van der Meer, Joakim Munkhammar, et al.
Applied Energy (2018) Vol. 218, pp. 159-172
Closed Access | Times Cited: 104
Probabilistic Framework with Bayesian Optimization for Predicting Typhoon-Induced Dynamic Responses of a Long-Span Bridge
Yiming Zhang, Hao Wang, Jianxiao Mao, et al.
Journal of Structural Engineering (2020) Vol. 147, Iss. 1
Closed Access | Times Cited: 100
Mixed kernel based extreme learning machine for electric load forecasting
Yanhua Chen, Marius Kloft, Yi Yang, et al.
Neurocomputing (2018) Vol. 312, pp. 90-106
Closed Access | Times Cited: 97
Sequential grid approach based support vector regression for short-term electric load forecasting
Youlong Yang, Jinxing Che, Chengzhi Deng, et al.
Applied Energy (2019) Vol. 238, pp. 1010-1021
Closed Access | Times Cited: 94
Parallel and reliable probabilistic load forecasting via quantile regression forest and quantile determination
Wenjie Zhang, Hao Quan, Dipti Srinivasan
Energy (2018) Vol. 160, pp. 810-819
Closed Access | Times Cited: 93
Short term electricity demand forecasting using partially linear additive quantile regression with an application to the unit commitment problem
Moshoko Emily Lebotsa, Caston Sigauke, Alphonce Bere, et al.
Applied Energy (2018) Vol. 222, pp. 104-118
Open Access | Times Cited: 89
Short-Term Power Load Forecasting Method Based on Improved Exponential Smoothing Grey Model
Jianwei Mi, Libin Fan, Xuechao Duan, et al.
Mathematical Problems in Engineering (2018) Vol. 2018, pp. 1-11
Open Access | Times Cited: 87
A New Hybrid Model for Short-Term Electricity Load Forecasting
Md. Rashedul Haq, Zhen Ni
IEEE Access (2019) Vol. 7, pp. 125413-125423
Open Access | Times Cited: 85
Improved quantile convolutional neural network with two-stage training for daily-ahead probabilistic forecasting of photovoltaic power
Qian Huang, Shanyang Wei
Energy Conversion and Management (2020) Vol. 220, pp. 113085-113085
Closed Access | Times Cited: 73
Uncertainty analysis of wind power probability density forecasting based on cubic spline interpolation and support vector quantile regression
Yaoyao He, Haiyan Li, Shuo Wang, et al.
Neurocomputing (2020) Vol. 430, pp. 121-137
Open Access | Times Cited: 69
Probabilistic Charging Power Forecast of EVCS: Reinforcement Learning Assisted Deep Learning Approach
Yuanzheng Li, Shangyang He, Yang Li, et al.
IEEE Transactions on Intelligent Vehicles (2022) Vol. 8, Iss. 1, pp. 344-357
Open Access | Times Cited: 65
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