Managing Variable Transmittance Windowpanes byModel-Based Autonomous Control
Managing Variable Transmittance Windowpanes byModel-Based Autonomous Control
摘要
The use of digitally activated, variable transmittance materials and artificial intelligence methods to building control will enhance the performance of buildings, and programmable components will change the traditional modes of architectural design, manufacturing and construction. In the presented key study, the architectural form and functionality of windows are revisited with a view to integrate current advances in material science, control systems engineering and human-computer interaction. The features of a building facade, involving a matrix of programmable windows that enables precise control of daylight, view and privacy in the interior of a house are discussed. Managing the variable transmittance materials of the facade by an autonomous high-level control system allows the optimization of the house performance based on real time data and the schedule of the inhabitants. Using constraint violations as a measure of success, the autonomous control of the house outperforms any existing deterministic control models.
参考文献16
-
1E.S. Lee, D.L. Di Bartolomeo, J.H. Klems, M. Yazdanian, S.E. Selkowitz, Monitored energy performance or electrochromic windows for daylighting and visual comfort, in: ASHRAE Summer Meeting, Quebec City, Canada, 2006, pp. 122-146.
-
2T. Hausler, U. Fischer, M. Rottmann, K.H. Heckner, Solar optical properties and daylight potential of electrochromic windows, in: International Lighting and Colour Conference, Capetown, 2003, pp. 102-106.
-
3S. Selkowitz, O. Aschehougd, E.S. Lee, Advanced interactive facades-Critical elements for future buildings?, in: U.S. Green Building Council's GreenBuild International Conference and Expo, USA, 2003, http://www.energy.ca.gov/2006publications/CEC-500-2006-052/CEC-500-2006-052-AT17.pdf (accessed Jan. 1, 2013).
-
4J. Mardaljevic, L. Heschong, E.S. Lee, Daylight metrics and energy savings, Lighting Research and Technology 41 (3) (2009) 261-283.
-
5A.E.D Mady, G.M. Provan, C. Ryan, K.N. Brown, Stochastic model predictive controller for the integration of building use, in: Proceedings of Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI-11), Special Track on Computational Sustainability and AI, USA, 2011, pp. 1371-1376.
-
6J.Z. Kolter, J Ferreira, A large-scale study on predicting and contextualizing building energy usage, in: Proceedings of Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI-12), Special Track on Computational Sustainability and AI, USA, 2011, pp. 1340-1356.
-
7H. Li, B.C. Williams, Hybrid planning with temporally extended goals for sustainable ocean observing, in: Proceedings of Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI-11), Special Track on Computational Sustainability and AI, USA, 2011, pp. 1365-1370.
-
8M. Ono, B.C. Williams, An efficient motion planning algorithm for stochastic dynamic systems with constraints on probability of failure, in: Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI-08), USA, 2008, pp. 1376-1382.
-
9T. Leaute, B.C. Williams, Coordinating agile systems through the model-based execution of temporal plans, in: Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI), USA, 2005, pp. 114-120.
-
10S. Kotsopoulos, G. Cara, W. Graybill, F. Casalegno, The Dynamic Facade Pattem Grammar, Environment and Planning B: Planning and Design, USA, 2012. (in print).
-
1张荣兴.浅谈建筑结构振动控制[J].黑龙江科技信息,2010(22):290-290.
-
2丁宗梁,陈芮,甘明,丁志娟.车站大厅阶梯形不规则网架设计研究[J].建筑结构学报,1996,17(5):44-55. 被引量:2
-
3郑高.人工智能方法在电梯交通模式识别中的应用[J].湖南农机,2014(2):48-49. 被引量:1
-
4杨波,王汉斌.多传感器管控理论与研究[J].中国科技信息,2017,0(6):92-93.
-
5中勤实业的玻璃基板卡匣进入TFT-LCD厂生产线[J].中国电子商情,2008(8):77-77.
-
6杨群.DCS控制系统工程的改造与完善[J].水泥,2008(7):60-61.
-
7许海龙.建筑结构振动控制概述[J].山西建筑,2009,35(9):92-93.
-
8邱树恒,罗必圣,冯阳阳,刘守吉.水玻璃基混凝土养护剂的制备与应用研究[J].混凝土,2012(10):139-143. 被引量:6
-
9GPRS技术在MRTLC智能照明控制系统中的应用[J].智能建筑电气技术,2010(5):126-126.
-
10郑海英,刘剑,陈智年.电梯群控系统的控制算法[J].中国电梯,2004,15(15):26-30. 被引量:1