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Global warming and the urban heat island effect have led to the deterioration of the outdoor thermal environment and the rise of building cooling demand, calling for urban design with high environmental quality. However, little has been changed in the practice of urban street design. This paper bridges this gap by developing a framework of parametric simulation for design guidance of urban streets with an advanced urban canopy model that can simulate the interactive indoor-outdoor environment. Case studies are conducted at the neighborhood scale for six cities to improve outdoor thermal comfort and building energy efficiency in summer. The influence of street and building design parameters has been investigated based on 31104 simulations. Results reveal the conflict between optimizing outdoor thermal comfort and optimizing building energy efficiency. In the majority of the investigated cities, window-to-wall ratio, window type, and street orientation are the most influential parameters. Strategies by adjusting these parameters can significantly improve outdoor thermal comfort, as quantified by thermal stress hours, at a cost of increasing the building cooling load. Planting bigger and denser roadside trees always moderately reduces the thermal stress hours and building cooling load. These results demonstrate the potential of this framework to identify the design trade-offs between thermal comfort and building energy efficiency. The framework can be extended to various cities to help designers and policymakers at the early design stage. • A framework to explore early design guidance for urban streets is developed. • A total of 31104 design scenarios are performed for six cities in southern China. • Window-to-wall ratio, window type, and street orientation are most influential factors. • Pareto optimal solutions for outdoor thermal comfort and building energy are revealed. [ABSTRACT FROM AUTHOR]

For the better operation of air-conditioning systems and the improvement of office building thermal environment, internal heat loads resulting from occupants, equipment, and lightings need to be accurately quantified because they are main components of space cooling loads. However, existing methods are hard to describe the complicated variation characteristics of internal cooling loads and time lag effect of conversion processes between electric energy and internal cooling loads, leading to limited application and unstable accuracy. To tackle this problem, in this study, transfer function models for instantaneous internal cooling loads were firstly established. Second, an experiment was conducted based on a chamber with good insulation. Third, experimental data and radiant time factors were employed in model discretization, parameter identification, and order decrease steps to acquire unknown parameters and develop models as second-order and third-order discrete transfer functions. Fourth, a simulation was conducted to validate the models, and a mean absolute percentage error of 8.08% was attained. Finally, a comparison between proposed and previously developed methods was carried out to evaluate model performance. The proposed models achieved a maximum internal cooling loads reduction of 75.57%, and the maximum time lag resulting from the heat storage characteristics of indoor thermal masses was approximately 30 min. With two easily accessible input parameters, the proposed models exhibited promising applicability and feasibility during the real-time operation of buildings. This paper provides a theoretical basis for accurately obtaining instantaneous internal cooling loads and thus is meaningful in improving building thermal environment and enhancing comfort levels. • Transfer function models for acquiring instantaneous internal cooling load were developed. • With two accessible input parameters, proposed models were applicable to the operation of office buildings. • Compared with previous methods, a maximum decrease in errors of 75.57% was obtained after adopting the proposed models. • This study facilitated the description of time lag effect of conversion processes between electric energy and internal cooling loads. [ABSTRACT FROM AUTHOR]

In this paper, the application of smart glazing systems as shading devices is evaluated for US residential buildings. Specifically, static and dynamic overhangs are considered using smart glazing that can change their tint state to reduce the heating and cooling thermal loads for prototypical housing units in high-rise apartment buildings. The tint settings as well as the overhang tilt angles are specified on hourly, daily, and monthly basis depending on the window orientation and the time of the year to minimize the annual energy demand for the housing units. The performance of smart glazed overhang systems is compared to both static and dynamic shading devices made-up of conventional opaque materials. In addition, the impacts of various design and climatic conditions are considered to assess the energy performance of the smart glazed overhangs. The results of the analysis indicate that the annual energy consumption for existing housing units with conventional windows located in Boulder, CO, can be reduced by over 7% for static smart glazed overhangs and by over 22% for dynamic smart glazed overhangs. These savings are even higher with larger windows and wider differentials between optical properties between clear and dark states. The smart glazed overhangs allow the use of low-cost smart glazing as a retrofit measure for existing buildings. Moreover, the smart glazed overhangs allow the specification of large windows for new constructions with limited energy penalties. • The energy performance of smart glazed overhangs is investigated for housing units. • Optimal controls are used to maximize the energy efficiency of the smart shades. • Switching of smart shades can be optimized on hourly, daily, or monthly basis. • Smart shades reduce energy demand up to 22% compared to unshaded clear low-E glazing. [ABSTRACT FROM AUTHOR]