| An IoT-based Thermal Model Learning Framework for Smart Buildings X Zhang, M Pipattanasomporn, T Chen, S Rahman IEEE Internet of Things Journal, 2019 | 111 | 2019 |
| An Edge-Cloud Integrated Solution for Buildings Demand Response Using Reinforcement Learning X Zhang, D Biagioni, M Cai, P Graf, S Rahman IEEE Transactions on Smart Grid, 2020 | 82 | 2020 |
| Power system parameter attack for financial profits in electricity markets H Xu, Y Lin, X Zhang, F Wang IEEE Transactions on Smart Grid 11 (4), 3438-3446, 2020 | 70 | 2020 |
| Deploying IoT devices to make buildings smart: Performance evaluation and deployment experience X Zhang, R Adhikari, M Pipattanasomporn, M Kuzlu, S Rahman Internet of Things (WF-IoT), 2016 IEEE 3rd World Forum on, 530-535, 2016 | 48 | 2016 |
| Learning-accelerated ADMM for distributed DC optimal power flow D Biagioni, P Graf, X Zhang, AS Zamzam, K Baker, J King IEEE Control Systems Letters 6, 1-6, 2020 | 43 | 2020 |
| Identification of key transmission lines in power grid using modified k-core decomposition X Zhang, F Liu, R Yao, X Zhang, S Mei, Z Zhang, X Li Electric Power and Energy Conversion Systems (EPECS), 2013 3rd International …, 2013 | 35 | 2013 |
| A self-learning algorithm for coordinated control of rooftop units in small-and medium-sized commercial buildings X Zhang, M Pipattanasomporn, S Rahman Applied energy 205, 1034-1049, 2017 | 29 | 2017 |
| Ten questions concerning reinforcement learning for building energy management Z Nagy, G Henze, S Dey, J Arroyo, L Helsen, X Zhang, B Chen, ... Building and Environment 241, 110435, 2023 | 25 | 2023 |
| Arbitrage of Energy Storage in Electricity Markets with Deep Reinforcement Learning H Xu, X Li, X Zhang, J Zhang arXiv preprint arXiv:1904.12232, 2019 | 24 | 2019 |
| Transferable Reinforcement Learning for Smart Homes X Zhang, X Jin, C Tripp, D Biagioni, P Graf, H Jiang Proceedings of the 1st International Workshop on Reinforcement Learning for …, 2020 | 22 | 2020 |
| Powergridworld: A framework for multi-agent reinforcement learning in power systems D Biagioni, X Zhang, D Wald, D Vaidhynathan, R Chintala, J King, ... Proceedings of the Thirteenth ACM International Conference on Future Energy …, 2022 | 15 | 2022 |
| Reinforcement learning building control approach harnessing imitation learning S Dey, T Marzullo, X Zhang, G Henze Energy and AI 14, 100255, 2023 | 14 | 2023 |
| Two-stage reinforcement learning policy search for grid-interactive building control X Zhang, Y Chen, A Bernstein, R Chintala, P Graf, X Jin, D Biagioni IEEE Transactions on Smart Grid 13 (3), 1976-1987, 2022 | 14 | 2022 |
| Grid-interactive multi-zone building control using reinforcement learning with global-local policy search X Zhang, R Chintala, A Bernstein, P Graf, X Jin 2021 American Control Conference (ACC), 4155-4162, 2021 | 12 | 2021 |
| A power disaggregation approach to identify power-temperature models of HVAC units X Zhang, M Cai, M Pipattanasomporn, S Rahman 2018 IEEE international smart cities conference (ISC2), 1-6, 2018 | 11 | 2018 |
| Curriculum-based Reinforcement Learning for Distribution System Critical Load Restoration X Zhang, AT Eseye, B Knueven, W Liu, M Reynolds, W Jones IEEE Transactions on Power Systems, 2022 | 10 | 2022 |
| A data-driven approach for coordinating air conditioning units in buildings during demand response events X Zhang Virginia Tech, 2019 | 10 | 2019 |
| Restoring distribution system under renewable uncertainty using reinforcement learning X Zhang, AT Eseye, B Knueven, W Jones 2020 IEEE International Conference on Communications, Control, and Computing …, 2020 | 9 | 2020 |
| Conceptual framework for a multi-building peak load management system X Zhang, M Pipattanasomporn, M Kuzlu, S Rahman PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2016 …, 2016 | 8 | 2016 |
| Challenges and opportunities of machine learning control in building operations L Zhang, Z Chen, X Zhang, A Pertzborn, X Jin Building Simulation 16 (6), 831-852, 2023 | 7 | 2023 |
David BiagioniProofpointVerified email at proofpoint.com
