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| 1 | Optimal design and operation of a thermal storage system for a chilled water plant serving pharmaceutical buildings 显示文摘 | Gregor P Henze Bernd Biffar Dietmar Kohn Martin P Becker | 2008 | Energy and Buildings2008，40，： | 1 |
| 2 | Guidelines for improved performance of ice storage systems显示文摘 | Gregor P Henze Moncef Krarti Michael J B | 2003 | Energy and Buildings2003，35，2： | 1 |
| 3 | Ten questions concerning integrating smart buildings into the smart grid显示文摘Recent advances in information and communications technology(ICT) have initiated development of a smart electrical grid and smart buildings. Buildings consume a large portion of the total electricity production worldwide, and to fully develop a smart grid they must be integrated with that grid. Buildings can now be'prosumers'on the grid(both producers and consumers), and the continued growth of distributed renewable energy generation is raising new challenges in terms of grid stability over various time scales. Buildings can contribute to grid stability by managing their overall electrical demand in response to current conditions. Facility managers must balance demand response requests by grid operators with energy needed to maintain smooth building operations.For example, maintaining thermal comfort within an occupied building requires energy and, thus an optimized solution balancing energy use with indoor environmental quality(adequate thermal comfort, lighting, etc.) is needed. Successful integration of buildings and their systems with the grid also requires interoperable data exchange. However, the adoption and integration of newer control and communication technologies into buildings can be problematic with older legacy HVAC and building control systems.Public policy and economic structures have not kept up with the technical developments that have given rise to the budding smart grid, and further developments are needed in both technical and non-technical areas. | Thomas M.Lawrence MarieClaude Boudreau Lieve Helsen Gregor Henze Javad Mohammadpour Doug Noonan Dieter Patteeuw Shanti Pless Richard T.Watson 侯恩哲 | 2016 | 建筑节能2016，44，11： | 1 |
| 4 | Guidelines for improved performance of ice storage systems显示文摘 | GREGOR P HENZE MONCEF KRARTI MICHAEL J B | 2003 | Energy and Buildings2003，35，2： | 1 |
| 5 | Guidelines for improved performance of ice storage systems显示文摘 | GREGOR P HENZE MONCEF KRARTI MICHAEL J BRANDEMUEHL | 2003 | Energy and Building2003，35，： | 1 |
| 6 | Impact of adaptive comfort criteria and heat waves on optimal building thermal mass control 显示文摘 | Henze Gregor P Pfafferott Jens Herkel Sebastian | 2007 | Energy and Buildings2007，39，2： | 1 |
| 7 | Guidelines for Improved Performance of Ice Storage Systems显示文摘 | Gregor P Henze Moncef Krarti | 2003 | Energy and Buildings2003，35，2： | 1 |
| 8 | Guidelines for improved performance of ice storage systems显示文摘 | Gregor P. Henze Moncef Krarti Michael J. Brandemuehl | 2002 | Energy & Buildings2002，，2： | 1 |
| 9 | Reinforcement learning building control approach harnessing imitation learning显示文摘Reinforcement learning(RL)has shown significant success in sequential decision making in fields like autonomous vehicles,robotics,marketing and gaming industries.This success has attracted the attention to the RL control approach for building energy systems which are becoming complicated due to the need to optimize for multiple,potentially conflicting,goals like occupant comfort,energy use and grid interactivity.However,for real world applications,RL has several drawbacks like requiring large training data and time,and unstable control behavior during the early exploration process making it infeasible for an application directly to building control tasks.To address these issues,an imitation learning approach is utilized herein where the RL agents starts with a policy transferred from accepted rule based policies and heuristic policies.This approach is successful in reducing the training time,preventing the unstable early exploration behavior and improving upon an accepted rule-based policy-all of these make RL a more practical control approach for real world applications in the domain of building controls. | Sourav Dey Thibault Marzullo Xiangyu Zhang Gregor Henze | 2023 | Energy and AI2023，14，4： | 0 |
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