| Intelligent multi-zone residential HVAC control strategy based on deep reinforcement learning F Li, Y Du Deep Learning for Power System Applications: Case Studies Linking Artificial …, 2023 | 185 | 2023 |
| A hybrid building thermal modeling approach for predicting temperatures in typical, detached, two-story houses B Cui, C Fan, J Munk, N Mao, F Xiao, J Dong, T Kuruganti Applied energy 236, 101-116, 2019 | 94 | 2019 |
| A scalable and distributed algorithm for managing residential demand response programs using alternating direction method of multipliers (ADMM) X Kou, F Li, J Dong, M Starke, J Munk, Y Xue, M Olama, H Zandi IEEE Transactions on Smart Grid 11 (6), 4871-4882, 2020 | 67 | 2020 |
| Multi-task deep reinforcement learning for intelligent multi-zone residential HVAC control Y Du, F Li, J Munk, K Kurte, O Kotevska, K Amasyali, H Zandi Electric Power Systems Research 192, 106959, 2021 | 55 | 2021 |
| Alternative Refrigerant Evaluation for High-Ambient Temperature Environments: R-22 and R-410A Alternatives for Mini-Split Air Conditioners O Abdelaziz, JD Munk, SS Shrestha, RL Linkous, W Goetzler, M Guernsey, ... Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States). Building …, 2015 | 47 | 2015 |
| Exergy analysis of a two-stage ground source heat pump with a vertical bore for residential space conditioning under simulated occupancy MR Ally, JD Munk, VD Baxter, AC Gehl Applied Energy 155, 502-514, 2015 | 46 | 2015 |
| Effect of occupant behavior and air-conditioner controls on humidity in typical and high-efficiency homes J Winkler, J Munk, J Woods Energy and Buildings 165, 364-378, 2018 | 37 | 2018 |
| Evaluating the adaptability of reinforcement learning based HVAC control for residential houses K Kurte, J Munk, O Kotevska, K Amasyali, R Smith, E McKee, Y Du, B Cui, ... Sustainability 12 (18), 7727, 2020 | 33 | 2020 |
| Aggregation and data driven identification of building thermal dynamic model and unmeasured disturbance Z Guo, AR Coffman, J Munk, P Im, T Kuruganti, P Barooah Energy and Buildings 231, 110500, 2021 | 28 | 2021 |
| Cooling season full and part load performance evaluation of variable refrigerant flow (VRF) system using an occupancy simulated research building P Im, M Mini, JD Munk, J Lee | 28 | 2016 |
| Exergy and energy analysis of a ground-source heat pump for domestic water heating under simulated occupancy conditions MR Ally, JD Munk, VD Baxter, AC Gehl International journal of refrigeration 36 (5), 1417-1430, 2013 | 27 | 2013 |
| Exergy analysis and operational efficiency of a horizontal ground-source heat pump system operated in a low-energy test house under simulated occupancy conditions MR Ally, JD Munk, VD Baxter, AC Gehl International Journal of Refrigeration 35 (4), 1092-1103, 2012 | 26 | 2012 |
| Virtual storage capability of residential buildings for sustainable smart city via model-based predictive control J Joe, J Dong, J Munk, T Kuruganti, B Cui Sustainable Cities and Society 64, 102491, 2021 | 21 | 2021 |
| Building thermal model development of typical house in US for virtual storage control of aggregated building loads based on limited available information B Cui, J Munk, R Jackson, D Fugate, M Starke Proceedings of ECOS, 2017 | 21 | 2017 |
| Deep reinforcement learning for autonomous water heater control K Amasyali, J Munk, K Kurte, T Kuruganti, H Zandi Buildings 11 (11), 548, 2021 | 19 | 2021 |
| Agent-based system for transactive control of smart residential neighborhoods M Starke, J Munk, H Zandi, T Kuruganti, H Buckberry, J Hall, J Leverette 2019 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2019 | 17 | 2019 |
| Real-time MPC for residential building water heater systems to support the electric grid M Starke, J Munk, H Zandi, T Kuruganti, H Buckberry, J Hall, J Leverette 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies …, 2020 | 16 | 2020 |
| Demonstration of intelligent HVAC load management with deep reinforcement learning: real-world experience of machine learning in demand control Y Du, F Li, K Kurte, J Munk, H Zandi IEEE Power and Energy Magazine 20 (3), 42-53, 2022 | 15 | 2022 |
| Methodology for interpretable reinforcement learning model for HVAC energy control O Kotevska, J Munk, K Kurte, Y Du, K Amasyali, RW Smith, H Zandi 2020 IEEE International Conference on Big Data (Big Data), 1555-1564, 2020 | 15 | 2020 |
| Rl-hems: Reinforcement learning based home energy management system for hvac energy optimization O Kotevska, K Kurte, J Munk, T Johnston, E Mckee, K Perumalla, H Zandi Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States), 2020 | 15 | 2020 |
