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Lighting Systems And Users Interactions In Classrooms And Laboratory Rooms, Camila Novais, Roberta Souza, Andrea Pereira
Lighting Systems And Users Interactions In Classrooms And Laboratory Rooms, Camila Novais, Roberta Souza, Andrea Pereira
International Building Physics Conference 2018
In Brazil, there has been an increase in the use of certifications designed to assess and improve building performance. Despite these advances, there is still little knowledge concerning the buildings’ post-occupancy. Thus, the present work aimed to evaluate the occupants’ behaviour regarding the use of lighting and internal shading devices. Classrooms and laboratories at UFMG Architecture and Design School were used as case study. The main objective was to analyse how a cycle of influences works: how occupants influence energy consumption and act in relation to the buildings systems, as well as how the building and the internal systems influence …
House: Building Energy Efficiency Understanding Through An Enabled Boundary Object, Deborah Adkins, Peter R.N. Childs
House: Building Energy Efficiency Understanding Through An Enabled Boundary Object, Deborah Adkins, Peter R.N. Childs
International Building Physics Conference 2018
We report the results of an empirical study on an enabled application’s ability to act as a boundary object and build understanding of energy efficiency solutions. Combining digital and tangible technology with radio-frequency identification (RFID) tags, we have created an interactive, digitally enabled device and application called HOUSE (Home User and Stakeholder Environment). The HOUSE tool and application have been designed and developed to support interaction and collaboration in the exploration of domestic energy efficiency solutions. HOUSE allows users to associate information with physical representations, and to explore this information through manipulation of enabled objects. The interactive application consists of …
A Deep Reinforcement Learning Method For Model-Based Optimal Control Of Hvac Systems, Zhiang Zhang, Chenlu Zhang, Khee Poh Lam
A Deep Reinforcement Learning Method For Model-Based Optimal Control Of Hvac Systems, Zhiang Zhang, Chenlu Zhang, Khee Poh Lam
International Building Physics Conference 2018
Model-based optimal control (MOC) methods have strong potential to improve the energy efficiency of heating, ventilation and air conditioning (HVAC) system. However, most existing MOC methods require a low-order building model, which significantly limits the practicability of such methods. This study develops a novel model-based optimal control method for HVAC supervisory-level control based on the recently-proposed deep reinforcement learning (DRL) framework. The control method can directly use whole building energy model, a widely used flexible building modelling method, as the model and train an optimal control policy using DRL. By integrating deep learning models, the proposed control method can directly …
Pareto Optimality Analysis For Evaluating The Tradeoff Between Visual Comfort And Energy Efficiency, Maryam Hamidpour, Vincent Blouin
Pareto Optimality Analysis For Evaluating The Tradeoff Between Visual Comfort And Energy Efficiency, Maryam Hamidpour, Vincent Blouin
International Building Physics Conference 2018
Architectural designs are increasingly driven by both sustainability and health, which requires evaluating the tradeoff between visual comfort and energy consumption. Lack of daylight leads to poor visual comfort and health issues but reduces heat gains, while excessive daylight may lead to over-illumination, glare, and high heat gains. Identifying the tradeoff between multiple criteria is an intricate process that requires skill and experience, especially when dealing with complex phenomena such as visual comfort. In order to facilitate this process, this paper provides two contributions: (1) the description of a new single-valued visual comfort measure, and (2) the application of the …