With the increasing stock of ageing infrastructure and resource constraints in Singapore, related risks and carbon emissions can be mitigated through long-term resilience planning, automated building inspection, and effective maintenance. Sustainable actions are needed to maintain Singapore's ageing infrastructure. Hence, a state-of-the-art control and management system is required in the form of smart city digital tools. We introduce an Urban Digital Twin (UDT)—GHG App for decision-makers in Singapore's operational building greenhouse gas (GHG) emission mitigation and decarbonisation initiatives. Based on multiple-criteria decision analysis (MCDA), a Potential for Intervention (PFI) map was created to rejuvenate the building system. Decision-makers can use this map to prioritise the rejuvenation of low-carbon building systems in the built environment. A heat map of the PFI results highlights which buildings need urgent rejuvenation based on critical parameters. The GHG App utilises this method to generate maps and enables users to modify parameter weights based on their priorities, automatically updating the map. Users can plan an intervention for buildings with higher PFI values once the map is generated. The GHG App provides interactive data visualisation of 119,872 features representing Singapore's built environment, including the context size of 6,785 existing residential buildings modelled and used to demonstrate the analysis results. Our research findings can contribute to the development of standards for accounting for operational GHG emissions, setting emission limits, and planning decarbonisation in the built environment sector.@en

In a global context of increasing flexibility in the way workplaces and the districts in which they are located are used, there is a need for occupant-driven approaches to plan urban energy systems. Several authors have suggested the use of agent-based models (ABM) of building occupants in urban building energy simulations due to their ability to reproduce emergent behaviors from individual agents’ actions. However, few works in the literature take full advantage of the ABM paradigm, accounting for both occupant presence and energy-relevant behaviors at the district scale. In this work, we propose a methodology to develop a data-driven, agent-based model of building occupants’ activities and thermal comfort in an urban district. Our methodology combines the use of campus-scale Wi-Fi data to derive feasible occupant activity and location plans, along with thermal preference profiles derived from a longitudinal field study where off-the-shelf, non-intrusive sensors were used to capture the right-here-right-now thermal preference of 35 participants in the same case study district. Our model is then used to explore how different district operation strategies could affect building energy performance in the context of increased workspace flexibility. Our results show that by providing a diversity of building operation conditions, with different buildings having different set point temperatures, occupants’ thermal comfort hours could be improved by an average of about 10% with little effect on district energy performance. Meanwhile, a 6%–15% average decrease in space cooling energy use intensity was observed when implementing occupant-driven ventilation and setpoint controls, regardless of location choice scenario.

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The widespread availability of open datasets in cities is transforming the way urban energy systems are planned, simulated, and visualized. In this paper, a cross-scale approach is pursued to better understand the reciprocal effects between building energy performance, the urban climate, and urban dwellers’ indoor and outdoor thermal comfort. On the one hand, monthly building electricity and gas demand data at the parcel level was collected, along with hourly weather station data at the urban scale. On the other hand, a longitudinal experiment was carried out in which 22 participants wore smartwatches for 4–6 weeks and filled out hourly micro surveys on their activities, location, and thermal comfort. In addition to survey responses, the smartwatches collected participants’ physiological data and location throughout the period of the study. The project was conducted in Seoul, South Korea, the highest-ranked Asian country in open data readiness, implementation, and impact. This paper reports on the data collection effort and provides some preliminary analysis of the results. The work carried out is expected to help develop methodologies for the convergence of district-scale and occupant-scale data in urban areas. A number of expected applications are proposed, including urban-scale studies on the impact of urban form on the local climate and building energy performance, district-to-building-scale building energy simulations accounting for occupant thermal comfort-related behaviors, and district-scale analyses of occupants’ outdoor thermal comfort and its relationship with location and wayfinding in urban areas.@en

The widespread availability of open datasets in urban areas is transforming how urban energy systems are planned, simulated, and visualized. Urban energy models, however, require an understanding of urban dwellers, as their activities create the demands for energy in buildings. In this paper, we explore using campus-scale Wi-Fi data to identify typical occupant activity patterns as an input to an agent-based model of building occupants at the district scale. The data is taken from a Singaporean university's Wi-Fi network at high resolution. Each record comprises a timestamp, a device identifier, the location of the device within the campus, and the access point to which it is connected. The Wi-Fi dataset contains 120 different buildings on campus and 10,300 anonymized individual devices. Activities are then assigned to each location on campus according to the building use type. In order to test the methodology, the activity plans of 27,604 undergraduate students, 8,304 graduate students, and 12,018 employees were simulated over a workweek. The results show the model's ability to produce plausible activity plans but could be improved by implementing sampling rules and expanding the source dataset to include off-peak dates. Nevertheless, using such an agent-based modeling approach at the district scale appears to be a promising methodology to assess the impacts of different planning strategies on occupant behavior and district energy demand.@en

Smart city initiatives have been a driving force for city-level dataset collection and the development of data-driven applications that benefit effective city management. There is a need to demonstrate use cases for effective city management using the available dataset. Urban Digital Twin (UDT) is a 3D city model that can integrate multi-disciplines and improve systems operability on a digital platform. However, UDTs are developed within organisations, and there is only limited availability of authoritative open 3D datasets to explore the potential of UDT concepts. This paper reports a methodology for creating a UDT platform for visualising and querying city energy data. We demonstrate a bottom-up approach to constructing an integrated 3D city dataset and create a query system for rapid access and navigation of the 3D city dataset through a visualisation platform using Cesium Ion. Various use cases are explored based on the dataset, such as building material stock management, energy demand simulation, electric vehicles (EV) demand and flexibility, and estimation of greenhouse gas (GHG) emissions. These use cases can help decision-makers and stakeholders involved in city planning and management. Furthermore, it provides a guideline for developers willing to create UDT applications for smart city initiatives.@en

Before 2020, the way occupants utilized the built environment had been changing slowly towards scenarios in which occupants have more choice and flexibility in where and how they work. The global COVID-19 pandemic accelerated this phenomenon rapidly through lockdowns and hybrid work arrangements. Many occupants and employers are considering keeping some of these flexibility-based strategies due to their benefits and cost impacts.

This paper explores how demand-driven control strategies in the built environment might support the transition to increased workplace flexibility by simulating various scenarios related to the operational technologies and policies of a real-world campus using a district-scale City Energy Analyst (CEA) model that is calibrated with measured energy demand data and occupancy profiles extracted from WiFi data. These scenarios demonstrate the energy impact of ramping building operations up and down more rapidly and effectively to the flex-based work strategies that may solidify. The scenarios show a 5–15% decrease in space cooling demand due to occupant absenteeism of 25–75% if centralized building system operation is in place, but as high as 17–63% if occupancy-driven building controls are implemented. The paper discusses technologies and strategies that are important in this paradigm shift of operations.@en

This work proposes the use of a data-driven, agent-based model of building occupants’ activities and thermal comfort in an urban university campus in order to assess how district operation strategies can be leveraged to support the transition to flexible work arrangements. The results show that when users are given the flexibility to pursue more comfortable workspaces, they are still comfortable only 58% of the time.@en

This paper presents a digital twin of a university campus in Singapore as a demonstrator for a digital-twin enabled approach to district energy resilience. This paper focuses mainly on the development of the building energy and occupancy models in the digital twin, which are complemented by a user interface for real-time data visualization and scenario assessment. The building energy demand model of the case study area was calibrated using measured hourly cooling and electricity data collected in the case study area. Occupant presence was estimated using WiFi connection counts, and a simple regression model was developed to assign electricity loads as a function of occupant presence and time of day. The digital twin’s scenario assessment capabilities were explored through scenarios on the long-term effects of climate change and of the increase of remote working and studying as a result of the COVID-19 pandemic. Four different “work-from-home” cases were considered, and three different building operation strategies were assumed for each case. The results show that a decrease in building occupancy post-COVID-19 would lead to minimal space cooling savings in the case study area unless building operation was proactively adjusted to adapt to the new needs of the campus.@en

District-scale energy demand models can be powerful tools for understanding interactions in complex urban areas and optimising energy systems in new developments. The process of coupling characteristics of urban environments with simulation software to achieve accurate results is nascent. We developed a digital twin through a web map application for a 170ha district-scale university campus as a pilot. The impact on the built environment is simulated with pandemic (COVID-19) and climate change scenarios. The former can be observed through varying occupancy rates and average cooling loads in the buildings during the lockdown period. The digital twin dashboard was built with visualisations of the 3D campus, real-time data from sensors, energy demand simulation results from the City Energy Analyst (CEA) tool, and occupancy rates from WiFi data. The ongoing work focuses on formulating a resilience assessment metric to measure the robustness of buildings to these disruptions. This district-scale digital twin demonstration can help in facilities management and planning applications. The results show that the digital twin approach can support decarbonising initiatives for cities.@en

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

In the implementation of Energy Transition Strategies within urban (re)development projects, processes of spatial negotiation between functional needs (for buildings and transportation infrastructure) and energy solutions able to meet the energy performative targets have been observed. In a large number of urban transformation cases, spatial planning and design decisions are independent trajectories to which the energy optimization adapts, based on the idea that technological measures for reducing the energy consumption and for clean energy production can be adapted or integrated in a second stage at the building scale. Furthermore, competitive dynamics for the use of space, in particular in interventions of redevelopment within dense urban environments, contribute to exacerbate the conflict between the idea/principles for energy transitions and its spatial configuration.
The paper investigates the practice of energy transition in a Swiss case where the ambitious National Energy Strategies confront these obstacles in managing the implementation phase. The decision makers involved in the project of the Hochschulquartier (HQ), the new University Campus in Zurich, have been interviewed to understand how energy and spatial decision are taken and coordinated at the micro and macro level, and to understand the main constrains. The results show that the practice of spatial-energy integrated decisions needs new forms of coordination, decision structure and procedure, as well as a new role for designers.@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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SPACERGY builds upon the need for planning authorities to develop new models to implement energy transition strategies in the urban environment, departing from the exploitation or reciprocity between space and energy systems. Several policies have been made by each EU nation, but effective and practical tools to guide the urban transformations towards a carbon-neutral future present several challenges. The first challenge is to confront long term changes in envisioning how a specific socio-cultural context can respond to the application of solutions for energy efficiency. Secondly, the engagement of communities in bottom-up approaches mainly includes the sphere of urban planning that underestimates the importance of relating spatial transformations with the energy performances generated in the urban environment. The third challenge regards the tools used for the assessment of the energy performance and the necessity of enlarging the scale in which energy demand is analyzed, from the scale of the building to that of the district. In this context, the project explores the role of mobility, spatial morphologies, infrastructural elements and local community participation in regards to the smart use of local resources. The project addresses a knowledge gap in relation to interactions and synergies between spatial programming, energy and mobility systems planning and stakeholder involvement necessary to improve models of development and governance of urban transformations.

Based on detailed spatial morphology and energy use modeling, SPACERGY develops new toolsets and guidelines necessary to advance the implementation of energy-efficient urban districts. New toolsets are tested in three urban areas under development in the cities of Zurich, Almere, and Bergen, acting as living laboratories for real-time research and action in collaboration with local stakeholders. The results of this research project support planners and decision-makers to facilitate the transition of their communities to more efficient, livable and thus prosperous urban environments.
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In the design practice simulation methods are already widely used to support the understanding of energy performance and to help designers in reducing energy demand during the design process. However, energy simulation tools are largely limited to the individual building level, and urban microclimate conditions and
variations in local wind, solar radiation, and air temperature patterns in which buildings express their energy performance are largely overlooked. In order to include microclimatic data in the computation of space cooling and heating consumption and enlarge the scale of analysis from single buildings to district scale, a new simulation method has been developed. The proposed coupling procedure links the microclimate software ENVI-met and the City Energy Analyst energy simulation tool and it is employed in the energy assessment of a urban re-development project in the city of Zurich, Switzerland. The results show that, considering microclimatic boundary conditions, the average hourly energy loads vary for daytime and night-time peaks and moreover a variation can be noticed in terms of total space heating and cooling consumption on the hottest and coldest day of a typical year.@en

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

Comparisons of buildings in similar climates built in accordance with different regional construction practices and building rating systems can provide useful insights in sustainable design practices. The objectives of this study were: (1) to perform energy related life cycle assessments of a typical LEED-H (Leadership in Energy and Environmental Design for Homes) single-family home in New Jersey (US), and a typical Minergie-P single-family home in Chur, Switzerland; and (2) to assess the effect of rating systems and construction practices on the buildings’ environmental impacts. Inventory data was obtained from the Ecoinvent 2.2 database with a replacement of the Western European electricity mix with the US or New Jersey electricity mix for the New Jersey home. The Swiss building performed better regarding non-renewable energy consumption, Global Warming Potential and Acidification Potential mainly due to the geothermal heat pump and the Swiss electricity mix while there was less of a difference regarding Ozone Layer Depletion Potential and Eutrophication Potential. The influence of electricity sources exceeded the effects of longer building life time or the removal of the Swiss basement. Regional building practices, local codes and environmental policies should take the electricity mix into account because it is so important.@en