Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis

Chen, Yixing; Hong, Tianzhen; Piette, Mary Ann

doi:10.1016/j.apenergy.2017.07.128

Cited by 292 publications

(101 citation statements)

References 25 publications

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“…Modelling urban morphology can be divided into three main approaches based on studying; possible configurations [159]; real-site configurations [160]; or both [152], [161]. Through applying any of these approaches, several studies have investigated the relationship between urban morphology and the energy demand and supply of buildings in urban areas, each considering some influencing parameters of urban morphology in terms of energy demand [162], [163] and wind assessment for ventilation [164].…”

Section: Section 43: Energy Demand and Supplymentioning

confidence: 99%

A review of assessment methods for the urban environment and its energy sustainability to guarantee climate adaptation of future cities

Mauree

Naboni

Coccolo

et al. 2019

Renewable and Sustainable Energy Reviews

167

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Reviewed assessment methods for the urban environment • Critically analysed papers working on urban climate and energy demand, outdoor thermal comfort and the urban energy systems. • Demonstrated the links between the processes • An integrated workflow is proposed for assessment of the urban environment. AbstractThe current climate change is calling for a drastic reduction of energy demand as well as of greenhouse gases. Besides this, cities also need to adapt to face the challenges related to climate change. Cities, with their complex urban texture and fabric, can be represented as a diverse ecosystem that does not have a clear and defined boundary. Multiple software tools that have been developed, in recent years, for assessment of urban climate, building energy demand, the outdoor thermal comfort and the energy systems. In this review, we, however, noted that these tools often address only one or two of these urban planning aspects. There is nonetheless an intricate link between them. For instance, the outdoor comfort assessment has shown that there is a strong link between biometeorology and architecture and urban climate. Additionally, to address the challenges of the energy transition, there will be a convergence of the energy needs in the future with an energy nexus regrouping the energy demand of urban areas. It is also highlighted that the uncertainty related to future climatic data makes urban adaptation and mitigation strategies complex to implement and to design given the lack of a comprehensive framework. We thus conclude by suggesting the need for a holistic interface to take into account this multi-dimensional problem. With the help of such a platform, a positive loop in urban design can be initiated leading to the development of low carbon cities and/or with the use of blue and green infrastructure to have a positive impact on the mitigation and adaptation strategies.

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Section: Section 43: Energy Demand and Supplymentioning

confidence: 99%

A review of assessment methods for the urban environment and its energy sustainability to guarantee climate adaptation of future cities

Mauree

Naboni

Coccolo

et al. 2019

Renewable and Sustainable Energy Reviews

167

View full text Add to dashboard Cite

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“…The City Building Energy Saver (CityBES) by Hong et al [89] is a tool for retrofit analysis of small and mediumsized office and retail buildings. Chen et al [88,87,96] present case studies using CityBES in downtown San Francisco. EnergyPlus models are created from data on building footprint, age, type, gross floor area, and number of stories, using the Commercial Building Energy Saver Toolkit (CBES) [97].…”

Section: Deterministic Space-based Approaches Without Diversitymentioning

confidence: 99%

A review on occupant behavior in urban building energy models

Happle

Fonseca

Schlueter

2018

Energy and Buildings

171

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Urban building energy models aspire to become key planning tools for the holistic optimization of buildings, urban design, and energy systems in neighborhoods and districts. The energy demand of buildings is largely influenced by the behavior of the occupants. The insufficient consideration of occupant behavior is one of the causes to the "performance gap" in buildings -the difference between the simulated and the actually observed energy consumption. On the urban-scale impacts of different occupant behavior modeling approaches onto the various purposes of urban building energy models are still largely unknown. Research shows that the inappropriate choice of occupant behavior model could result in oversized district energy systems, leading to over-investment and low operational efficiency. This work therefore reviews urban building energy models in terms of their occupant behavior modeling approaches. Three categories of approaches are established and discussed: (1) deterministic space-based approaches, (2) stochastic space-based approaches, and (3) stochastic person-based approaches. They are further assessed in terms of their strategy to consider diversity in occupant behavior. Stochastic models, especially stochastic person-based models, seem to be superior to deterministic models. However, there are no stochastic models available yet that can be used for case studies of mixed-districts, comprising buildings of various occupancy types. In the reviewed urban-scale approaches, only single-use residential or office districts are modeled with stochastic techniques. However, people interact with various buildings on a daily basis. Their activities relate to their presence in different spaces at the urban-scale and to their use of appliances in those spaces. Their individual levels of comfort and behavioral patterns govern the control actions towards building systems. Therefore, a novel activity-based multi-agent approach for urban occupant behavior modeling is proposed as alternative to current approaches.Keywords: urban building energy model, energy-related occupant behavior, occupancy, occupant behavior model IntroductionUrban areas house more than half of the global population and cities are responsible for more than 70% of the global carbon dioxide emissions. At the same time, cities are crucial actors in the transition towards sustainable energy Email address: happle@arch.ethz.ch (Gabriel Happle)

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“…As seen in equation (16), N char correlates to traffic inflow q in and traffic outflow q out , as exemplified in previous equations (11). In the transportation system shown in equation (17), traffic inflow q in and traffic outflow q out , along with average velocity U ave , road velocity U, travel time t w/Com , are determined by the transportation parameters such as road capacity C t , design road velocity U s ; energy factors such as the locational marginal price L M P and electrical control signals Sig E ; as well as communication factors such as throughput Q c and time delay Del, as exemplified in previous equations (8)- (12).…”

Section: B Block Layer Modelmentioning

confidence: 99%

An Open Source Modeling Framework for Interdependent Energy-Transportation-Communication Infrastructure in Smart and Connected Communities

Hinkelman

et al. 2019

IEEE Access

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Infrastructure in future smart and connected communities is envisioned as an aggregate of public services, including the energy, transportation and communication systems, all intertwined with each other. The intrinsic interdependency among these systems may exert underlying influence on both design and operation of the heterogeneous infrastructures. However, few prior studies have tapped into the interdependency among the three systems in order to quantify their potential impacts during standard operation. In response to this, this paper proposes an open source, flexible, integrated modeling framework suitable for designing coupled energy, transportation, and communication systems and for assessing the impact of their interdependencies. First, a novel multi-level, multi-layer, multi-agent approach is proposed to enable flexible modeling of the interconnected energy, transportation, and communication systems. Then, for the framework's proof-of-concept, preliminary component and system-level models for different systems are designed and implemented using Modelica, an equation-based object-oriented modeling language. Finally, three case studies of gradually increasing complexity are presented (energy, energy + transportation, energy + transportation + communication) to evaluate the interdependencies among the three systems. Quantitative analyses show that the deviation of the average velocity on the road can be 10.5% and the deviation of the power draw from the grid can be 7% with or without considering the transportation and communication system at the peak commute time, indicating the presence of notable interdependencies. The proposed modeling framework also has the potential to be further extended for various modeling purposes and use cases, such as dynamic modeling and optimization, resilience analysis, and integrated decision making in future connected communities.

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Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis

Cited by 292 publications

References 25 publications

A review of assessment methods for the urban environment and its energy sustainability to guarantee climate adaptation of future cities

A review of assessment methods for the urban environment and its energy sustainability to guarantee climate adaptation of future cities

A review on occupant behavior in urban building energy models

An Open Source Modeling Framework for Interdependent Energy-Transportation-Communication Infrastructure in Smart and Connected Communities

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