| 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 | 412 | 2014 |
| 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 | 128 | 2015 |
| Uncertainty handling using neural network-based prediction intervals for electrical load forecasting H Quan, D Srinivasan, A Khosravi Energy 73, 916-925, 2014 | 96 | 2014 |
| 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 | 74 | 2014 |
| Particle swarm optimization for construction of neural network-based prediction intervals H Quan, D Srinivasan, A Khosravi Neurocomputing 127, 172-180, 2014 | 65 | 2014 |
| 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 | 44 | 2018 |
| Reconciling solar forecasts: Geographical hierarchy D Yang, H Quan, VR Disfani, L Liu Solar Energy 146, 276-286, 2017 | 42 | 2017 |
| 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 | 36 | 2016 |
| Reconciling solar forecasts: Temporal hierarchy D Yang, H Quan, VR Disfani, CD Rodríguez-Gallegos Solar Energy 158, 332-346, 2017 | 34 | 2017 |
| Parallel and reliable probabilistic load forecasting via quantile regression forest and quantile determination W Zhang, H Quan, D Srinivasan Energy 160, 810-819, 2018 | 31 | 2018 |
| 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 | 23 | 2012 |
| 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 | 19 | 2018 |
| 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 | 13 | 2017 |
| 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 | 13 | 2013 |
| 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 | 12 | 2019 |
| Quality control for solar irradiance data D Yang, GM Yagli, H Quan 2018 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 208-213, 2018 | 8 | 2018 |
| Probabilistic solar irradiance transposition models H Quan, D Yang Renewable and Sustainable Energy Reviews 125, 109814, 2020 | 6 | 2020 |
| A stochastic power flow study to investigate the effects of renewable energy integration H Quan, D Yang, AM Khambadkone, D Srinivasan 2018 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 19-24, 2018 | 3 | 2018 |
| Prediction Interval Construction for Electric Load and Wind Power via Machine Learning W Zhang, H Quan, D Srinivasan 2018 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 716-721, 2018 | 2 | 2018 |
| Reliable Photovoltaic Generation Forecasting via Quantile Determination W Zhang, H Quan, O Gandhi, D Srinivasan 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies …, 2019 | 1 | 2019 |
Dipti SrinivasanIEEE Fellow; Professor, National University ofAdresse e-mail validée de nus.edu.sg
