Dynamic building facades offer untapped potential for reducing building energy consumption and emissions. However, there is currently a lack of suitable technologies for bespoke components for new and retrofit applications. In previous work, we developed a 3D printed polymer facade component that selectively acts as a thermal conductor or insulator depending on outdoor and indoor conditions. Our experiments demonstrate that the element can achieve effective thermal conductivities as low as 0.03 W/mK and as high as 28 W/mK in insulating and conducting modes. In this work, we assess the potential impact of this technology on reducing heating and cooling energy demand. We conducted a parametric analysis of ten physical characteristics of the facade component. Then, we simulated the façade component employed in 270 building typologies and climate combinations. Our results indicate annual energy reduction of up to 80 kWh/m2 (heating) and 15 kWh/m2 (cooling) for building typology-climate combinations that can benefit the most from this technology.

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A novel approach is presented to 3D print vacuum–tight polymer components using liquid crystal polymers (LCPs). Vacuum–tight components are essential for gas storage and passive heat transfer, but traditional polymer 3D printing methods often suffer from poor interfaces between layers and high free volume, compromising vacuum integrity. By harnessing the unique properties of LCPs, including low free volume and low melt viscosity, highly ordered domains are achieved through nematic alignment of polymer chains. Critical gas–barrier properties are demonstrated, even in thin, single–print line–walled samples ranging from 0.8 to 1.6 mm. A 200 mm evacuated thermosiphon is successfully printed, which exhibits a thermal resistance of up to 2.18 K/W and an effective thermal conductivity of up to 28 W/mK at 60 °C. These values represent a significant increase compared to the base LCP material. Furthermore, the geometric freedom, enabled by 3D printing through the fabrication of complex–shaped thermosiphons, is showcased. The authors study highlights the potential of LCPs as high–performance materials for 3D printing vacuum–tight components with intricate geometries, opening new avenues for functional design. An application of integrating 3D printed thermosiphons as selective heat transfer components in building envelopes is presented, contributing to greenhouse gas emissions mitigation in the construction sector.

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Input uncertainty is one of the major obstacles urban building energy models (UBEM) must tackle. The aim of this paper was to quantify the effects of two of the main sources of stochastic uncertainty, namely building occupants and urban microclimate, on electrical and thermal supply system sizing at the district scale. In order to analyze the effects of the former, three different methods of occupant modeling were implemented in a UBEM. The effects of the urban heat island on system sizing were studied through the use of measured temperature data from a weather station in the case study district compared to measured data from a national weather station. The methods developed were used to assess the sizing and costs of centralized and decentralized technologies for a case study in central Zurich, Switzerland. The choice of occupant modeling approach was found to affect the district’s total annualized costs for space heating and cooling by ±5%, whereas for the costs of electricity the variation was ±8%. Regarding outdoor temperature, the effects on the heating demands proved be negligible, however the costs of the cooling alternatives were found to vary by about 4% at the district scale due to the effect of urban climate, for individual buildings this deviation was as high as 40%.@en

Lake water district cooling systems have been shown to reduce greenhouse gas emissions in several cases, including projects in heating-dominated climates. Due to the highly cooling-intensive functions in the Hochschulquartier area in Zurich, Switzerland, a district-scale free cooling network based on lake water has been proposed, but its feasibility has yet to be demonstrated.

This paper presents the methodology for thermal network simulation developed for the City Energy Analyst (CEA), an open-source software for energy demand simulation and system operation modeling and optimization. This methodology was then applied to simulate the free cooling system’s operation for four scenarios of urban development for the area featuring different functional mixes. The results were then compared to decentralized vapor compression chillers in order to analyze the network’s feasibility from an economic and environmental perspective.

The simulation results showed that the district cooling network would reduce the electricity demand for cooling in the area by about 60% compared to the use of standard vapor compression chillers. This improvement in performance was however achieved at the expense of much higher annualized costs due to the large investment associated with building the network. Thus, the proposed free cooling network might require further economic incentives for its construction.@en

District-scale building energy models can be a powerful tool for the integration of renewable energy sources and efficiency measures in urban areas. One key limitation of these models, however, has been their rather simplified treatment of building occupants. Since it is their activities which create the needs for energy in an area, an improved analysis of the effects of occupants on demand at the district scale is needed.

This paper presents a novel population-based approach (PopAp) inspired by agent-based transportation models, in which a population of occupants was defined based on class and employee registers and each was given an individual daily schedule. This approach was then used to assess the effect of occupant presence modeling on district-scale energy demand simulations by comparing the data-centric PopAp method to standard-based deterministic and stochastic approaches.

The maximum number of occupants in the area was found to be 33% higher for the deterministic model compared to the data-centric PopAp results, a deviation that was especially pronounced in education buildings. The results for space heating, space cooling and electricity demand for lighting and appliances show that while the mean deviation between models on a yearly basis is within 10% for all demands, on an hourly scale the deviation for space cooling and electricity exceeded 15%. Given the importance of the hourly scale for peak demand prediction for technology sizing, more detailed occupant modeling approaches should be considered when planning energy systems.@en

Rapid urbanization and densification processes are changing microclimatic environments in cities around the world. Even though previous studies have demonstrated the impact of urban microclimate on space cooling and heating demand, modeling tools employed to support the design process largely overlook microclimatic conditions in assessing building energy performance, making use of data from weather stations often located in rural areas. This paper presents a computational approach for the quantitative analysis of building energy demand at the district scale, including interdependent factors such as local air temperature, relative humidity and wind speed, diversity in building geometry and materials. The method, which couples the microclimate model ENVI-met and the district-scale energy simulation tool City Energy Analyst, is applied to a case study in Zurich, Switzerland, in order to analyze the energy performance of the area on a hot summer day. The study contributes to advance a coupling approach between a microclimate simulation and an energy tool at the district scale. The results showed that the coupled assessment approach can deal with complex interactions between geometry, building materials and energy systems. The consideration of local microclimatic conditions led to a 5% increase in the space cooling demand on the selected day, while the simulated peak cooling load for each building was 8% higher on average. The variation in the space cooling demand was found to be mainly due to an increase in latent cooling demand. Moreover, the coupling method allowed a detailed analysis of energy demand variation at the building level showing that, when considering the local climate patterns, the space cooling demand of the individual buildings varied between −5% and +14% on the selected day. The proposed method represents a next step to reflect the mutual interactions between buildings and microclimate in urban districts and aims at supporting decision-making in the design process.@en

District-scale energy demand models are powerful tools to understand complex urban areas, however these models generally use average weather data from rural locations, thus overlooking the effects of the urban context on the local climate. In order to analyze the effects of urban microclimate on space cooling demand, this paper uses microclimate simulation results from ENVI-met as inputs to a district-scale energy demand model, the City Energy Analyst (CEA), to assess the performance of a proposed masterplan for a new residential district in Almere, the Netherlands.

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Urban Building Energy Models are powerful tools for estimating future states of energy consumption and energy generation in buildings. Due to the complexity of these systems, large amounts of data are required, which are often incomplete or unavailable. Through the implementation of building archetypes, models such as the City Energy Analyst minimize the amount of input data. However, these simplifications inherently increase the uncertainty of the expected results.

This paper presents a sensitivity analysis of architectural properties (window-to-wall ratio, occupant density and envelope leakiness), thermal properties (U-values, G-values, thermal mass and emissivity of building surfaces), operating parameters (set point temperatures and ventilation rates) and internal loads (heat gains due to occupancy, appliance use and lighting). For this, the study combines a two-step process of sensitivity analysis with Saltelli's extension of the Sobol method and the City Energy Analyst. The methodology is applied to a case study area in central Zurich, Switzerland, comprising 284 buildings with predominantly educational, hospital and residential uses.

The results showed that the cooling demand in the area was very strongly influenced by the set point temperature, with other variables having a relatively minor influence. For the heating case a larger number of variables were needed in order to explain variations in demand, primarily the thermal properties of the envelope and air exchange rates of the buildings. This was generally true for all occupancy types, shapes, sizes and locations, showing the importance of accurate estimates of these parameters in urban building energy modeling. On a broader sense, the results contribute to the development of urban energy simulations that are both practical and accurate.@en