Follow
Hao Quan (权浩)
Title
Cited by
Cited by
Year
Short-term load and wind power forecasting using neural network-based prediction intervals
H Quan, D Srinivasan, A Khosravi
IEEE Transactions on Neural Networks and Learning Systems 25 (2), 303-315, 2014
6592014
An improved quantile regression neural network for probabilistic load forecasting
W Zhang, H Quan, D Srinivasan
IEEE Transactions on Smart Grid 10 (4), 4425-4434, 2018
1892018
A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources
H Quan, D Srinivasan, AM Khambadkone, A Khosravi
Applied energy 152, 71-82, 2015
1832015
Uncertainty handling using neural network-based prediction intervals for electrical load forecasting
H Quan, D Srinivasan, A Khosravi
Energy 73, 916-925, 2014
1592014
Incorporating wind power forecast uncertainties into stochastic unit commitment using neural network-based prediction intervals
H Quan, D Srinivasan, A Khosravi
IEEE transactions on neural networks and learning systems 26 (9), 2123-2135, 2014
1222014
Particle swarm optimization for construction of neural network-based prediction intervals
H Quan, D Srinivasan, A Khosravi
Neurocomputing 127, 172-180, 2014
1172014
Parallel and reliable probabilistic load forecasting via quantile regression forest and quantile determination
W Zhang, H Quan, D Srinivasan
Energy 160, 810-819, 2018
932018
A survey of computational intelligence techniques for wind power uncertainty quantification in smart grids
H Quan, A Khosravi, D Yang, D Srinivasan
IEEE transactions on neural networks and learning systems 31 (11), 4582-4599, 2019
882019
Reconciling solar forecasts: Geographical hierarchy
D Yang, H Quan, VR Disfani, L Liu
Solar Energy 146, 276-286, 2017
752017
Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: A comparative study
H Quan, D Srinivasan, A Khosravi
Energy 103, 735-745, 2016
692016
Reconciling solar forecasts: Temporal hierarchy
D Yang, H Quan, VR Disfani, CD Rodríguez-Gallegos
Solar Energy 158, 332-346, 2017
662017
Improving probabilistic load forecasting using quantile regression NN with skip connections
W Zhang, H Quan, O Gandhi, R Rajagopal, CW Tan, D Srinivasan
IEEE Transactions on Smart Grid 11 (6), 5442-5450, 2020
592020
A multi-agent based integrated volt-var optimization engine for fast vehicle-to-grid reactive power dispatch and electric vehicle coordination
W Zhang, O Gandhi, H Quan, CD Rodríguez-Gallegos, D Srinivasan
Applied energy 229, 96-110, 2018
492018
Deep-learning-based probabilistic estimation of solar PV soiling loss
W Zhang, S Liu, O Gandhi, CD Rodríguez-Gallegos, H Quan, ...
IEEE Transactions on Sustainable Energy 12 (4), 2436-2444, 2021
312021
Quality control for solar irradiance data
D Yang, GM Yagli, H Quan
2018 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 208-213, 2018
282018
Construction of neural network-based prediction intervals using particle swarm optimization
H Quan, D Srinivasan, A Khosravi
The 2012 International Joint Conference on Neural Networks (IJCNN), 1-7, 2012
272012
Probabilistic solar irradiance transposition models
H Quan, D Yang
Renewable and Sustainable Energy Reviews 125, 109814, 2020
262020
Construction of neural network-based prediction intervals for short-term electrical load forecasting
H Quan, D Srinivasan, A Khosravi, S Nahavandi, D Creighton
2013 IEEE Computational Intelligence Applications in Smart Grid (CIASG), 66-72, 2013
182013
An ensemble machine learning based approach for constructing probabilistic PV generation forecasting
W Zhang, H Quan, O Gandhi, CD Rodríguez-Gallegos, A Sharma, ...
2017 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), 1-6, 2017
172017
Outlier detection and data filling based on KNN and LOF for power transformer operation data classification
D Zou, Y Xiang, T Zhou, Q Peng, W Dai, Z Hong, Y Shi, S Wang, J Yin, ...
Energy Reports 9, 698-711, 2023
92023
The system can't perform the operation now. Try again later.
Articles 1–20