URBAN MICROCLIMATE AND

BUILDING ENERGY: A COUPLED

SIMULATION APPROACH

Gilles Plessis1, Hassan Bouia1, Maya Milliez 1, Mathieu

Schumann1, Marjory Musy2, Thomas Leduc2, Philippe

Alamy3

1EDF R&D EnerBaT (Energy in Buildings and Territories Dpt.),

Moret-sur-Loing, France2CRENAU, Nantes, France3EnerBIM, Toulouse, France

| 2ICUC9 2015 | 24/07/2015

CONTEXT : TOWARD A BIOCLIMATIC AND URBAN

DESIGN OF BUILDINGS

New buildings are very sensitive to their

environment

A bioclimatic and dynamical design of

buildings with renewable energy has to

take the local microclimate into account

Urban densification is also a major factor

of urban microclimate degradation

Specialists of urban issues seek more

information on the influence of buildings

Impact of local microclimate on buildings

Impact of buildings on local microclimate

| 3JNES 2015 | 02/07/2015

THE ANR MERUBBI PROJECT

Research centersEnergy simulation

software company

Technical

design office

Architects

Developing a simulation platform

to optimize the design of a new

building to be added to an

existing city block

| 4JNES 2015 | 02/07/2015

OUTLOOK: TOWARDS OPTIMIZATION OF NEW

BUILDING DESIGN

Optimization

Initial design taking energy

efficiency into account

Existing city block analysis

BIM, economic and

regulatory

calculation

Designs

Dynamical

simulation

Local micro-

climate

Envelope identification

Solar calculation

CAPEX OPEXBioclimatic

indicators

| 5JNES 2015 | 02/07/2015

GETTING FROM A 3D MODEL TO A 0DDYNAMICAL SIMULATION

ArchiWIZARD

Business software for building and

radiative transfer simulation

Import of SletchUp 3D model

Identification of building envelope

attributes

Solar radiation calculation by ray tracing

Regulatory calculations

BuildSysPro: EDF’s model library for building

energy simulation - written in Modelica under

the Dymola environment

Meteo EnvelopeOccupants

Heat and

cold

generation

and

distribution

Control

| 6ICUC9 2015 | 24/07/2015

FEASIBILITY: THEORETICAL CASE STUDY

Theoretical building block

Square matrix of low energy individual houses

(10m x 10m x 3m), placed 10m from each other

1

2

57

South

4

3 96

2 85

1 74

North

South

West East

| 7JNES 2015 | 02/07/2015

THEORETICAL CASE STUDY: RESULTS FOR

HEATING CONSUMPTION

3 96

2 85

1 74

North

South

West East

Difference in heating consumption (kWh/m²) (ref = single building)

| 8ICUC9 2015 | 24/07/2015

9 REAL CASE STUDIES × 3 CONFIGURATIONS

Individual house near Paris

Apartment building in Nantes

Office building in Strasbourg

| 9JNES 2015 | 02/07/2015

ARCHITECTURAL ANALYSIS OF THE « NANTES

RANZAY » CITY BLOCK

Cadastral map

Plot n°1 – Sheet 000

RV 01

City of Nantes

Google Maps

location plan

New building layout plan

| 10JNES 2015 | 02/07/2015

SKETCHUP 3D MODEL

| 11JNES 2015 | 02/07/2015

SOLAR RADIATION CALCULATION (ARCHIWIZARD)

| 12ICUC9 2015 | 24/07/2015

BUILDSYSPRO STUDY

Physical phenomena:

• Air renewal

• Thermal bridges

• Global radiation on walls

• Direct and diffuse radiation on

windows

• Long-wave radiation exchange: – Between walls

– With the sky

– With the ground)

1 studied configuration: whole city

block (new buildings included)

2 simulations

• With sun

• Without sun

| 13ICUC9 2015 | 24/07/2015

SIMULATION RESULTATSWITH SUN

Temperatures [°C]

Heating load [kW]

| 14ICUC9 2015 | 24/07/2015

SIMULATION RESULTATSWITHOUT SUN

Temperatures [°C]

Heating load [kW]

| 15ICUC9 2015 | 24/07/2015

BIOCLIMATIC INDICATORS FOR A

SOLAR HOUSE

Dynamic

simulation

with sun

Dynamic

simulation

without sun

Difference in

heating need

Simultaneity of need

and resource?

Rate of use of

the capacity

Energy need

coverage rate

Useful capacity

of the resource

Actual heating

need

Useful

resource

Used solar

resource

| 16ICUC9 2015 | 24/07/2015

Capacity and performance indicators for a low-energy single house in Chambéry

0

100

200

300

400

500

600

700

800

900

1000

Sun Sky Air

kWh/(m².an)

Simultaneous capacity Exploited capacity Energy needs Adjusted capacity

Capacity and performance indicators for an old single house in Chambéry

0

100

200

300

400

500

600

700

800

900

1000

Sun Sky Air

kW

h/(

m².

an

)

Simultaneous capacity Exploited capacity Real energy needs Adjusted capacity

BIOCLIMATIC INDICATORS OF THE SOLAR

RESOURCE FOR THE HEATING NEED

Useful solar

capacity

Actual heating

need

Heating need coverage

rate by the sun

Rate of use of the

solar capacity

12% 25% 6% 78%

Old building Low energy building

| 17ICUC9 2015 | 24/07/2015

RESULTS POST-PROCESSINGCOVERAGE RATES

Z1 Z2 Z3 Z4 Z5 Z6 Z7 Z8 Z9 Z10 Z11 Z12 Z13 Z14 Z15 Z16 Z17 Z18 Z19 Z20 Z21 Z22

Tcouv

Texp

Taux de couverture des besoins et d'exploitation du soleil

%

02

04

06

08

01

00

| 18JNES 2015 | 02/07/2015

PERSPECTIVES

For optimization, it is necessary to switch from detailed to reduced order

building models

Studying the impact of our findings on new design methods with help of the

architects

Identified challenging tasks:

Multi-criteria optimization and economical optimization mechanisms

Availability of sufficient and relevant data on existing city blocks

Promising elements have been detected:

Convincing link between 3D CAD-views and 0D/1D detailed energy modeling

(with a « BIM » spirit)

Introducing local micro-climate in building simulation tools

A positive adoption by architects

| 19JNES 2015 | 02/07/2015

THANK YOU FOR YOUR ATTENTION