Novel validated method for GIS based automated dynamic urban building energy simulations

Nageler, Peter Josef; Zahrer, Gregor; Heimrath, Richard; Mach, Thomas; Mauthner, Franz; Leusbrock, Ingo; Schranzhofer, Hermann; Hochenauer, Christoph

doi:10.1016/j.energy.2017.07.151

Cited by 77 publications

(40 citation statements)

References 38 publications

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“…Geographic Information System (GIS) tools are fundamental for the creation of USEM models, to collect, manage and organize geographical data in order to evaluate the strengths and weaknesses of a territory [11]. GIS tools can also be used to create an atlas where data can be represented and the energy distribution, or other indicators, such as the energy consumptions, types of users, and the characteristics of the built environment, can be visualized on maps.…”

Section: Research Gapmentioning

confidence: 99%

An Urban Energy Atlas and Engineering Model for Resilient Cities

Mutani¹,

Todeschi²

2019

IJHT

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Increasing energy efficiency in buildings is a crucial topic, especially in those EU countries where almost 50% of the final energy consumption is used for space heating and cooling, of which 80% is used for buildings. This study presents a model and a tool that can be used to evaluate energy consumption and to identify retrofitting strategies and renewable energy sources with the aim of reaching energy and climate targets in order to improve energy security, competitiveness and sustainability in a territory. In a previous research, a 'top-down engineering' model was applied for a number of 1 km 2 districts in the city of Turin (IT) to evaluate the residual potential of buildings that could be connected to the district heating network. In this work, the energy-use model has been improved by considering applications to urban areas of different dimensions, and an urban energy atlas for the Turin building stock has been defined with the support of a Geographical Information System. The model has been validated by comparing the results of an energy balance calculation with energy consumption data of three consecutive heating seasons over an area of about 40 km 2 in which 500,000 inhabitants live.

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Section: Research Gapmentioning

confidence: 99%

An Urban Energy Atlas and Engineering Model for Resilient Cities

Mutani¹,

Todeschi²

2019

IJHT

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“…The tool of Nageler et al [91] produces 2.5D IDA ICE building models based on an archetype database according to building type and age. One building is represented by maximum three vertical layered thermal zones.…”

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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“…The existence of mixed-use buildings is recognized by Nageler et al (2017) in their dynamic heat demand model of a small town in Austria. The work derives the activities within buildings from data on land use, which may cover several land parcels, and the building's geometry, but mixed-use buildings are assumed only to be present in the town centre.…”

Section: Previous Workmentioning

confidence: 99%

Modelling a whole building stock: domestic, non-domestic and mixed use

Evans

Liddiard

Steadman

2017

Building Research & Information

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Work on energy use in buildingsin university research, professional practice and governmenthas tended to draw a broad distinction between 'the domestic stock' and 'the non-domestic stock'. A further tendency has been to focus attention on types of non-domestic buildings devoted to single uses (e.g. offices, shops or hospitals). This paper reports an empirical research programme in which the complete building stock in large areas of England and Wales is comprehensively represented in great detail, using a new method and model called 3DStock. The model breaks down activities by floor level and within each floor of every building. The results show that the extent of mixing of uses is much greater than has previously been acknowledged, especially towards the centres and in the older parts of towns and cities. These mixed-activity buildings are sometimes relatively simple combinations of domestic and nondomestic, e.g. urban retail with flats above, while others are complex mixtures of different nondomestic activities. The model can be used to investigate how these complex relationships influence energy use. It is argued that, at the larger scale, explicit account needs to be taken of the mixing of uses in future stock models for research and policy-making.

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Novel validated method for GIS based automated dynamic urban building energy simulations

Cited by 77 publications

References 38 publications

An Urban Energy Atlas and Engineering Model for Resilient Cities

An Urban Energy Atlas and Engineering Model for Resilient Cities

A review on occupant behavior in urban building energy models

Modelling a whole building stock: domestic, non-domestic and mixed use

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