gis-based district building energy modelling. usman ali.pdf · introduction the world has witnessed...

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INTRODUCTION The world has witnessed a major population shift to urban areas over the past few decades. METHODOLOGY GIS-Based District Building Energy Modelling Usman Ali ([email protected]) 1 , Eleni Mangina 2 , James O'Donnell 1 1 School of Mechanical & Materials Engineering, Energy Institute, University College Dublin, Ireland 2 School of Computer Science and Informatics , University College Dublin, Ireland RESULTS C ONCLUSIONS The research conducted is identifies a generalized methodology for GIS-based district energy modelling using bottom up approach. The modelling results help in the identification of energy efficient areas from the inefficient ones in the district. Furthermore, GIS-based modelling will aid the local authorities or city planners to identify priority areas for implementing energy efficiency measures and further improve sustainable energy policy decisions. The future work might also include the 3D-based GIS modelling using CityGML. A CKNOWLEDGEMENT This publication has emanated from research conducted with the financial support of Science Foundation Ireland under the SFI Strategic Partnership Programme Grant Number SFI/15/SPP/E3125. The opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Science Foundation Ireland. 54% 2014 2025 2050 66% Buildings play a significant role in driving the urban demand and supply of energy. Research conducted in the urban buildings sector indicates that there is a considerable potential to achieve significant reductions in energy consumption and greenhouse gas emissions. 39% 36% CO 2 Emissions 40% Overall Energy Consumption 75% Old Buildings Energy inefficient City Regions/ Local authorities District Small Areas Building Group of regions/ local authorities Geographical division of a city into different areas and each local authority constitutes a number of districts. The district constitutes a group of small areas Groups of buildings in a district Individual building Apartments (midfloor, top-floor, maisonette, etc) Houses (detached, semidetached, end of terrace, etc) At the large scale, individual building analysis is often difficult due to lack of data availability and users’ privacy issues. Hence, archetypes development is a common approach for individual building analysis at energy and emission reductions are possible through building energy analysis at a local level. Moreover, energy planning is often implemented at the national level and thus, is not effectively addressed within local or regional level planning structures. Therefore, local authorities are not wholly informed when making energy efficient decisions are strategic level in their locality. One of the most promising solutions is to improve the energy efficiency in buildings with limited information, which can be accomplished by using energy modelling. 35% Dublin City by Small Areas: Residential Energy Use

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Page 1: GIS-Based District Building Energy Modelling. Usman Ali.pdf · INTRODUCTION The world has witnessed a major population shift to urban areas over the past few decades. METHODOLOGY

INTRODUCTIONThe world has witnessed a major population shift to urbanareas over the past few decades.

METHODOLOGY

GIS-Based District Building Energy ModellingUsman Ali ([email protected]) 1, Eleni Mangina 2, James O'Donnell 1

1 School of Mechanical & Materials Engineering, Energy Institute, University College Dublin, Ireland2 School of Computer Science and Informatics , University College Dublin, Ireland

RESULTS

CONCLUSIONSThe research conducted is identifies a generalized methodology for GIS-based district energy modellingusing bottom up approach. The modelling results help in the identification of energy efficient areas fromthe inefficient ones in the district. Furthermore, GIS-based modelling will aid the local authorities or cityplanners to identify priority areas for implementing energy efficiency measures and further improvesustainable energy policy decisions. The future work might also include the 3D-based GIS modelling usingCityGML.

ACKNOWLEDGEMENTThis publication has emanated from research conducted with the financial support of Science Foundation Ireland under the SFI Strategic Partnership Programme Grant Number SFI/15/SPP/E3125. The opinions, findings and conclusions or recommendations expressed in this material are thoseof the author(s) and do not necessarily reflect the views of the Science Foundation Ireland.

54% 2014 2025 2050

66%

Buildings play a significant role in driving the urban demandand supply of energy. Research conducted in the urbanbuildings sector indicates that there is a considerablepotential to achieve significant reductions in energyconsumption and greenhouse gas emissions.

39%36%CO2 Emissions

40%

Overall Energy Consumption

75%

• Old Buildings Energy inefficient

City

Regions/ Local authorities

District

Small Areas

Building

Group of regions/ local authorities

Geographical division of a city into different areas and each local authority constitutes a number of districts.

The district constitutes a group of small areas

Groups of buildings in a district

Individual building

Apartments (midfloor, top-floor, maisonette, etc)Houses (detached, semidetached, end of terrace, etc)

At the large scale, individual building analysis is oftendifficult due to lack of data availability and users’ privacyissues. Hence, archetypes development is a commonapproach for individual building analysis at energy andemission reductions are possible through building energyanalysis at a local level. Moreover, energy planning is oftenimplemented at the national level and thus, is not effectivelyaddressed within local or regional level planning structures.Therefore, local authorities are not wholly informed whenmaking energy efficient decisions are strategic level in theirlocality. One of the most promising solutions is to improvethe energy efficiency in buildings with limited information,which can be accomplished by using energymodelling.

35%

Dublin City by Small Areas: Residential Energy Use