| Model-free renewable scenario generation using generative adversarial networks Y Chen, Y Wang, D Kirschen, B Zhang IEEE Transactions on Power Systems 33 (3), 3265 - 3275, 2018 | 591 | 2018 |
| Near-optimal method for siting and sizing of distributed storage in a transmission network H Pandžić, Y Wang, T Qiu, Y Dvorkin, DS Kirschen IEEE Transactions on Power Systems 30 (5), 2288-2300, 2015 | 363 | 2015 |
| Stochastic multistage coplanning of transmission expansion and energy storage T Qiu, B Xu, Y Wang, Y Dvorkin, DS Kirschen IEEE Transactions on Power Systems 32 (1), 643-651, 2017 | 242 | 2017 |
| Optimal energy storage siting and sizing: A WECC case study R Fernández-Blanco, Y Dvorkin, B Xu, Y Wang, DS Kirschen IEEE Transactions on Sustainable Energy 8 (2), 733-743, 2017 | 209 | 2017 |
| Toward cost-efficient and reliable unit commitment under uncertainty H Pandžić, Y Dvorkin, T Qiu, Y Wang, DS Kirschen IEEE Transactions on Power Systems 31 (2), 970-982, 2016 | 195 | 2016 |
| Scalable planning for energy storage in energy and reserve markets B Xu, Y Wang, Y Dvorkin, R Fernández-Blanco, CA Silva-Monroy, ... IEEE Transactions on Power Systems 32 (6), 4515 - 4527, 2017 | 153 | 2017 |
| Look-ahead bidding strategy for energy storage Y Wang, Y Dvorkin, R Fernández-Blanco, B Xu, T Qiu, DS Kirschen IEEE Transactions on Sustainable Energy 8 (3), 1106-1117, 2017 | 149 | 2017 |
| Co-planning of investments in transmission and merchant energy storage Y Dvorkin, R Fernandez-Blanco, Y Wang, B Xu, DS Kirschen, H Pandžić, ... IEEE Transactions on Power Systems 33 (1), 245-256, 2018 | 134 | 2018 |
| Comparison of scenario reduction techniques for the stochastic unit commitment Y Dvorkin, Y Wang, H Pandzic, D Kirschen 2014 IEEE PES General Meeting| Conference & Exposition, 1-5, 2014 | 124 | 2014 |
| Conditional Residual Modeling for Probabilistic Load Forecasting Y Wang, Q Chen, N Zhang, Y Wang IEEE Transactions on Power Systems 33 (6), 7327-7330, 2018 | 106 | 2018 |
| Scenario reduction with submodular optimization Y Wang, Y Liu, DS Kirschen IEEE Transactions on Power Systems 32 (3), 2479-2480, 2017 | 100 | 2017 |
| Two-stage WECC Composite Load Modeling: A Double Deep Q-Learning Networks Approach X Wang, Y Wang, D Shi, J Wang, Z Wang IEEE Transactions on Smart Grid, 2020 | 79 | 2020 |
| Mathematical representation of the WECC composite load model Z Ma, J Xie, Z Wang, Y Wang, R Diao, D Shi arXiv preprint arXiv:1902.08866, 2019 | 47 | 2019 |
| Short-term Load Forecasting at Different Aggregation Levels with Predictability Analysis Y Peng, Y Wang, X Lu, H Li, D Shi, Z Wang, J Li 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), 2019 | 45 | 2019 |
| Efficient scenario generation of multiple renewable power plants considering spatial and temporal correlations C Tang, Y Wang, J Xu, Y Sun, B Zhang Applied Energy 221, 348-357, 2018 | 44 | 2018 |
| Robust Time-Varying Synthesis Load Modeling in Distribution Networks Considering Voltage Disturbances M Cui, J Wang, Y Wang, R Diao, D Shi IEEE Transactions on Power Systems 34 (6), 4438-4450, 2019 | 42 | 2019 |
| Effect of time resolution on unit commitment decisions in systems with high wind penetration H Pandžić, Y Dvorkin, Y Wang, T Qiu, DS Kirschen 2014 IEEE PES General Meeting| Conference & Exposition, 1-5, 2014 | 41 | 2014 |
| Unit commitment under uncertainty–GAMS models H Pandzic, Y Dvorkin, T Qiu, Y Wang, DS Kirschen Library of the Renewable Energy Analysis Lab (REAL), University of …, 2015 | 40* | 2015 |
| Real-Time Energy Disaggregation at Substations With Behind-the-Meter Solar Generation W Li, M Yi, M Wang, Y Wang, D Shi, Z Wang IEEE Transactions on Power Systems 36 (3), 2023-2034, 2020 | 36 | 2020 |
| Imitation and Transfer Q-Learning-Based Parameter Identification for Composite Load Modeling J Xie, Z Ma, K Dehghanpour, Z Wang, Y Wang, R Diao, D Shi IEEE Transactions on Smart Grid 12 (2), 1674-1684, 2020 | 35 | 2020 |
Daniel KirschenDonald W. and Ruth Mary Close Professor of Electrical and Computer EngineeringVerified email at uw.edu
