CityBEM: Monthly building heating and cooling energy needs in cities

27.10.2017 |

CityBEM: an Open Source Implementation and Validation of Monthly Heating and Cooling Energy Needs for 3D Buildings in Cities

3D GeoInfo 2017 Conference, Melbourne, Australia26 - 27.10.2017

Syed Monjur Murshed, European Institute for Energy Research, GermanySolène Picard, École Supérieure d'Électricité, FranceAndreas Koch, European Institute for Energy Research, Germany

CityBEM: Monthly building heating and cooling energy needs in cities

27.10.2017 |

Contents

§ Research background

§ Objectives

§ Methodology

§ Results

§ Validation of method

§ Conclusion

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CityBEM: Monthly building heating and cooling energy needs in cities

27.10.2017 |

Background

§ Context of smart and low carbon cities, increasing energy efficiency, reducing GHG emission, etc. play an important role

§ Buildings are responsible for 40% of energy consumption and 36% of CO2 emissions in the EU (EU 2011)

§ Building Energy Models (BEM) can help to investigate detailed measures e.g., refurbishment plans, etc.˃ several such models (statistical vs. engineering), standards,

tools/software exist to calculate energy (heating and cooling) needs˃ models are prepared and applied at different spatial and temporal

extents and/or scales˃ one of the widely used standard is ISO 13970:2008 (ISO 2008)

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CityBEM: Monthly building heating and cooling energy needs in cities

27.10.2017 |

Background

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(ISO 2008)

§ ISO 13790-2008 standard˃ considers thermal gains and losses,

based on the simplified representationof building physics

˃ Hourly, monthly, or seasonal basis

§ Several advantages˃ an international collaboration and

standard, therefore, more robust˃ calculates energy demand for a large

number of buildings˃ less input data, simplified

representation

CityBEM: Monthly building heating and cooling energy needs in cities

27.10.2017 |

Background

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- Consider single building- Cannot perform citywide calculation

ISO 13970:2008 using non-GIS data

+ Widely used standard, applied in different countries+ Internal validation of model

CityBEM: Monthly building heating and cooling energy needs in cities

27.10.2017 |

Background

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- Only heating energy demand is calculated

- Mostly on residential districts- Robust validation is missing

ISO 13970:2008 using 3D city models

§ Eicker et al. 2012: heat demand in 3 districts in Germany, using DIN18599

§ Nouvel et al. 2013: implemented ISO 13970 method in 2 districts in Germany

§ Nouvel et al. 2015: combined statistical and engineering approaches for heating needs

§ Agugiaro 2016: residential heat demand in Trento in Italy

+ With the availability of 3D city models and different LODs, ISO standard is applied

CityBEM: Monthly building heating and cooling energy needs in cities

27.10.2017 |

Objectives

§ Implement the ISO 13970:2008 standard using the 3D city models to calculate the monthly building heating and cooling energy needs in cities => CityBEM

§ Use open source and publicly available datasets, tools and software to develop the CityBEM

§ Perform a quick and robust calculation at a city scale

§ Perform a 3-step validation of the CityBEM model

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Methodology: steps

ISO 13970:2008 is structured into 4 main blocks:

1. definition of building boundaries for conditioned and unconditioned spaces

2. identification of the zones (single vs. multi zones )

3. definition of the internal conditions for calculation of external climate, and other environmental data inputs (heat transfer losses, heat gain, etc.)

4. calculation of energy needs for heating and cooling, for each time step and building

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Methodology: steps

4. calculation of energy needs for heating and cooling, for each time step and building

7 main calculation steps:

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5 6 73

𝑄ℎ𝑡 = 𝑄𝑡𝑟 + 𝑄𝑣𝑒 = (𝐻𝑡𝑟+𝐻𝑣𝑒). .𝜃𝑖𝑛𝑡 ,𝑠𝑒𝑡 − 𝜃𝑒5. 𝑡

𝑄𝑔𝑛 = 𝑄𝑖𝑛𝑡 + 𝑄𝑠𝑜𝑙 = (𝛷𝑖𝑛𝑡 + 𝛷𝑠𝑜𝑙 ). 𝑡

𝑄𝐶,𝑛𝑑 = 𝑄𝑔𝑛 − 𝜂𝑙𝑠 . 𝑄ℎ𝑡

𝑄𝐶,𝑛𝑑 ,𝑖𝑛𝑡𝑒𝑟𝑚 = 𝑎𝐶,𝑟𝑒𝑑. 𝑄𝐶,𝑛𝑑

𝑄𝐻,𝑛𝑑 = 𝑄ℎ𝑡 − 𝜂𝑔𝑛 . 𝑄𝑔𝑛

𝑄𝐻,𝑛𝑑 ,𝑖𝑛𝑡𝑒𝑟𝑚 = 𝑎𝐻,𝑟𝑒𝑑. 𝑄𝐻,𝑛𝑑

CityBEM: Monthly building heating and cooling energy needs in cities

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Methodology: input data

Building geometry

• Wall area N, S, E, W• Volume• Floor area

Building typology

• Window area N, S, E, W• U values wall, roof, window, ground• G values window• Thermal bridges• Infiltration• Ventilation• Internal gain

Weather conditions

• Monthly temperature• Monthly wind speed• Monthly solar irradiance

CityBEM: Monthly building heating and cooling energy needs in cities

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Methodology: software architecture

CityBEM: Monthly building heating and cooling energy needs in cities

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Results

Around 4000 buildings in Karlsruhe Oststadt

Heating energy need (kWh/m²/year)

CityBEM: Monthly building heating and cooling energy needs in cities

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Results

Yearly specific building heating and cooling energy needs in 33 building typologies and corresponding number of buildings in each typology

CityBEM: Monthly building heating and cooling energy needs in cities

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Results

Calculation for Karlsruhe-Oststadt: Around 4000 buildings

Monthly specific heating and cooling energy needs for 7 building types and 5 age classes

CityBEM: Monthly building heating and cooling energy needs in cities

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Validation - approach

A 3 steps validation was performed

˃ Compare results with that in literature˃ Campare with ISO 13970:2008 appendix values ˃ Campare with a simulation software

TRNSYS: TRaNsient SYstems Simulation

CityBEM: Monthly building heating and cooling energy needs in cities

27.10.2017 |

Validation: TRNSYS

§ Input data˃ An office building (1975) and a residential building (1985) are

modelled in TRNSYS, with the same inputs as in CityBEM

§ Assumptions˃ No shading reduction factor in TRNSYS˃ Time average internal heat flow is considered˃ Introduce same time reduction factor

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CityBEM: Monthly building heating and cooling energy needs in cities

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Validation: TRNSYS

A residential building (1985)

An office building (1975)

The relative error of the yearly Heating: 5% - 10%.

Yearly cooling: 18% - 80%

CityBEM: Monthly building heating and cooling energy needs in cities

27.10.2017 |

Conclusion

Performance/test§ The CityBEM monthly model is tested in several European and

Asian urban cities, with varying number of buildings in both LOD1 and LOD2 data

§ The model proves very efficient and quick in displaying results in the virtual machine˃ around 3 minutes to run on about 4300 LOD2 buildings, 8

minutes on 12000 LOD2 buildings, 28 seconds on 600 LOD1 buildings, etc.

Limitation§ CityBEM requires a geometrically and topologically correct

CityGML dataset§ User and their behavior are constant

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CityBEM: Monthly building heating and cooling energy needs in cities

27.10.2017 |

Conclusion

Future research§ Calculation of energy use, considering the heating, cooling and

ventilation system (HVAC)§ Hourly or seasonal energy need or use§ Sensitivity of the critical model input parameters§ Simulation of energy saving potential or building refurbishment

plans, through a Graphic User Interface (GUI)§ More realistic representation of building using LOD3 or LOD4

models (multi-zone building)

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CityBEM: Monthly building heating and cooling energy needs in cities

27.10.2017 |

References

§ Agugiaro, G. (2016) Energy planning tools and CityGML-based 3D virtual city models: experiences from Trento (Italy). Applied Geomatics, 8, 41-56.

§ Eicker, U., R. Nouvel, C. Schulte, J. Schumacher & V. Coors. 2012. 3D Stadtmodelle für die Wärmebedarfberechnung. In Fourth German-Austrian IBPSA Conference. Berlin

§ EU 2011: “Review of the Energy Performance of Buildings Directive 2010/31/EU”, EC Directorate-General of Energy, Brussels.

§ ISO. 2008. Energy performance of buildings - Calculation of energy use for space heating and cooling. In ISO 13970:2008, 162. Geneva, Switzerland: ISO/TC 163/SC 2 Calculation methods

§ Kwak, H.-J., J.-H. Jo & S.-J. Suh (2015) Evaluation of the Reference Numerical Parameters of the Monthly Method in ISO 13790 Considering S/V Ratio. Sustainability, 7, 767-781.

§ Kim, Y.-J., S.-H. Yoon & C.-S. Park (2013) Stochastic comparison between simplified energy calculation and dynamic simulation. Energy and Buildings, 64, 332-342.

§ Kokogiannakis , G., P. Strachan & J. Clarke (2008) Comparison of the simplified methods of the ISO 13790 standard and detailed modelling programs in a regulatory context. Journal of Building Performance Simulation, 1, 209-219.

§ Corrado, V. & E. Fabrizio (2007) Assessment of building cooling energy need through a quasi-steady state model: Simplified correlation for gain-loss mismatch. Energy and Buildings, 39, 569-579.

§ Nouvel, R., A. Mastrucci, U. Leopold, O. Baume, V. Coors & U. Eicker (2015) Combining GIS-based statistical and engineering urban heat consumption models: Towards a new framework for multi-scale policy support. Energy and Buildings, 107, 204-212.

§ Nouvel, R., C. Schulte, U. Eicker, D. Pietruschka & V. Coors. 2013. CityGML-based 3D city model for energy diagnostics and urban energy policy supports. In 13th Conference of International Building Performance Simulation Association. Chambéry, France.

§ Vartieres, A., A. Berescu & A. Damian. 2013. Energy demand for cooling an office building. In 11th International Conference on Environment, Ecosystems and Development, 132-135.

§ Vollaro, R. D. L., C. Guattari, L. Evangelisti, G. Battista, E. Carnielo & P. Gori (2014) Building energy performance analysis: A case study. Energy and Buildings, 87, 87-94.

§ Zangheri, P., R. Armani, M. Pietrobon, L. Pagliano, M. F. Boneta & A. Müller. 2014. Heating and cooling energy demand and loads for building types in different countries of the EU. Report in the frame of the EU project ENTRANZE

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CityBEM: Monthly building heating and cooling energy needs in cities

27.10.2017 |

Thank you!Contact: murshed@eifer.orgEuropean Institute for Energy Research

Copyright © EIFER 2017

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