Author

Tao Hong

University of North Carolina at Charlotte - Cited by 8,150 - Load forecasting - energy forecasting - forecasting - energy analytics - demand forecasting

Biography

Dr. Tao Hong  is an Associate professor in the department of Load forecasting University of North Carolina at Charlotte United States . His study interests major on Load forecasting. Currently , Dr. Tao Hong  is the author/editors/reviewer in several international journals. He published 5 articles in many journals and the articles are informative and got good citations.
Title
Cited by
Year
Review of smart meter data analytics: Applications, methodologies, and challenges
Y Wang, Q Chen, T Hong, C KangIEEE Transactions on Smart Grid 10 (3), 3125 - 3148, 2019201
979
2019
Probabilistic load forecasting via Quantile Regression Averaging on sister forecasts
B Liu, J Nowotarski, T Hong, R WeronIEEE Transactions on Smart Grid 8 (2), 730 - 737, 2017201
315
2017
Energy forecasting: A review and outlook
T Hong, P Pinson, Y Wang, R Weron, D Yang, H ZareipourIEEE Open Access Journal of Power and Energy 7, 376-388, 2020202
272
2020
Combining Probabilistic Load Forecasts
Y Wang, N Zhang, Y Tan, T Hong, DS Kirschen, C KangIEEE Transactions on Smart Grid 10 (4), 3664 - 3674, 2019201
182
2019
Global energy forecasting competition 2017: Hierarchical probabilistic load forecasting
T Hong, J Xie, J BlackInternational Journal of Forecasting 35 (4), 1389-1399, 2019201
141
2019
Verification of deterministic solar forecasts
D Yang, S Alessandrini, J Antonanzas, F Antonanzas-Torres, V Badescu, ...Solar Energy 210, 20-37, 2020202
136
2020
Benchmarking robustness of load forecasting models under data integrity attacks
J Luo, T Hong, SC FangInternational Journal of Forecasting 34 (1), 89-104, 2018201
121
2018
Temperature Scenario Generation for Probabilistic Load Forecasting
J Xie, T HongIEEE Transactions on Smart Grid 9 (3), 1680-1687, 2018201
103
2018
On Normality Assumption in Residual Simulation for Probabilistic Load Forecasting
J Xie, T Hong, T Laing, C KangIEEE Transactions on Smart Grid 8 (3), 1046 - 1053, 2017201
96
2017
Relative humidity for load forecasting models
J Xie, Y Chen, T Hong, TD LaingIEEE Transactions on Smart Grid 9 (1), 191-198, 2018201
92
2018
Real-time anomaly detection for very short-term load forecasting
LUO Jian, H Tao, YUE MengJournal of Modern Power Systems and Clean Energy 6 (2), 235-243, 2018201
73
2018
Big data analytics for future electricity grids
M Kezunovic, P Pinson, Z Obradovic, S Grijalva, T Hong, R BessaElectric Power Systems Research 189, 106788, 2020202
59
2020
Multivariate Quantile Regression for Short-Term Probabilistic Load Forecasting
A Bracale, P Caramia, P De Falco, T HongIEEE Transactions on Power Systems, 2020202
58
2020
A copula-based Bayesian method for probabilistic solar power forecasting
H Panamtash, Q Zhou, T Hong, Z Qu, KO DavisSolar Energy 196, 336-345, 2020202
55
2020
A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality
D Yang, W Wang, CA Gueymard, T Hong, J Kleissl, J Huang, MJ Perez, ...Renewable and Sustainable Energy Reviews 161, 112348, 2022202
51
2022
A semi-heterogeneous approach to combining crude oil price forecasts
J Wang, X Li, T Hong, S WangInformation Sciences 460, 279-292, 2018201
51
2018
Robust Regression Models for Load Forecasting
J Luo, T Hong, SC FangIEEE Transactions on Smart Grid 10 (5), 5397 - 5404, 2019201
47
2019
A multi-granularity heterogeneous combination approach to crude oil price forecasting
J Wang, H Zhou, T Hong, X Li, S WangEnergy Economics 91, 104790, 2020202
37
2020