FRENCH PERSPECTIVES TOWARDS ENERGY FLEXIBLE BUILDINGS - Public seminar Annex 67

FRENCH PERSPECTIVES TOWARDS
 ENERGY FLEXIBLE BUILDINGS

 JÉRÔME LE DRÉAU, MARIKA VELLEI
 (LA ROCHELLE UNIVERSITY, LASIE UMR CNRS 7356)

 JOHANN MEULEMANS
 (SAINT-GOBAIN RESEARCH)

 Public seminar Annex 67
 Energy Flexible Buildings (04/04/2019)
 1

OUTLINE

France, a specific country ?
 • Electrical production and consumption
 • Perspective of development of flexibility in residential buildings

Flexibility from space heating
 • Influence of the envelope properties & emitter types
 • Thermal comfort under dynamic conditions

Flexibility from white-goods usage

Perspectives

 2

FRENCH CONTEXT
Electricity production :
 • Large share of nuclear energy (72%)
 • Little renewable (7% windmills+PV)
 • Low CO2 content (but nuclear wastes) electricitymap.org

Electricity consumption :
 • Large share of direct electrical heating
 (45% of space heating)
 • Large usage of TOU (41% households with Weekly average
 electrical power use
 “heures pleines / heures creuses”)
 • 8 GW of flexibility from dom. hot water

Demonstration projects (with on-site measurements) : Voltalis (2009),
Modelec (2011), Smart-Electric Lyon (2012), GreenLys (2012), etc
 3

PERSPECTIVE OF DEVELOPMENT
OF FLEXIBILITY
Results from techno-economic analyses at French level:
 • comparison of different smart-grid solutions (flexibility from residential
 buildings or industry, batteries, PSPS, new generation)

 • flexibility mainly from industry (& tertiary) ≈5 GW

 • flexibility from residential sector
 • RTP (dynamic) control ≈1 GW (activated from 10 to 100 hrs per year)
 • TOU control ≈18 GW (for heating, DHW, white goods and electric
 vehicles)
 Share of flexible households (RTP + TOU)
 Horizon 2030 Horizon 2060
 Heating 8-25% (9 GW) 75%
 Domestic Hot Water 50-60% (5,4 GW) 100%
 White goods - 56%
 Electric vehicles 25-36% (4,5 GW) 80%
 4

FLEXIBILITY FROM
 SPACE HEATING

 Heating system (radiator or
 floor heating)
 • remote set-point control
 (e.g. pilot wire)
 • overriding possible

SIGNAL (H-12)
 68

 58
 SMART POWER PROFILE
 65

 METER signal
 60

 w/o flex with flex
 SP modulations
 48

 55

 38

 50

 28

 45

 18
 0 5 10 15 20 25
 40

 35

 Occupants 30

 • TOU (e.g. HP/HC) • usages
 25
 4,1 6,1 8,1 10, 1 12, 1 14, 1 16, 1 18, 1

 • RTP • thermal comfort
 Building
 properties

 5

[SPACE HEATING] ENVELOPE &
 EMITTERS PROPERTIES
 Temperature Temperature
 set-point set-point
 23°C 1 – 12h
 Type of 21°C
 21°C
 demand Time 19°C Time
 response Upward modulations Downward modulations
 (for valley filling, anticipation) (for peak shedding, load shifting)

 Type of 300 150 50 25
 building
 Heating need [kWh/m².year]

Type of 50’s BR 1982 BR 2005 BR 2012 BR 2020
emitter 6

[SPACE HEATING] ENVELOPE &
EMITTERS PROPERTIES
• Estimation of the energy shifted and power profiles (BES)

 Δqheating post-DR

 Δqheating DR

• Estimation of the mean power* change during the DR events
 50s BR 1982 BR 2005 BR 2012 BR 2020
 0 0
 Median power decrease [kW]

 -0,5 -0,5

 -1 -1

 -1,5 -1,5

 -2 -2

 -2,5 -2,5

 -3
 * corrected usages -3
 7
 1 hr 2 hrs 4 hrs 6 hrs 8 hrs 12 hrs RTE REI 2017

[SPACE HEATING] THERMAL COMFORT
 UNDER DYNAMIC ENVIRONMENT
 • Fanger’s PMV/PPD model (EN 15251) : derived from a steady-state
 heat balance equation and steady-state laboratory experiments

 • Proposal for a new thermal comfort model based on PMV :

 Thermal
 Comfort

 Repeated rises and falls of
 
 the temperature have the
• negative alliesthesia moving Thermal Thermal potential to induce
 away from neutral Alliesthesia Habituation habituation, which leads to
• positive alliesthesia moving a reduction of the normal
 towards neutral response or sensation
 8

[SPACE HEATING] THERMAL COMFORT
UNDER DYNAMIC ENVIRONMENT
Experimental data collected from IEQL (University of Sydney)
 • 56 students in climatic chambers
 • 6 different cyclical temperature variations (overall duration 2 hrs)
 • highest rates of temperature change (up to 30°C/h)

 20%

 5%
 -0,5
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FLEXIBILITY FROM
 WHITE-GOODS USAGE

 Washing machine /
 Dishwasher
 • option smart-start or
 delay start

SIGNAL (H-12)
 68

 POWER PROFILE
 SMART
 65

 58

 60

 w/o flex with flex
 METER signal
 48

 start
 55

 38

 50

 28

 45

 18
 0 5 10 15 20 25
 40

 35

 30

 • TOU (e.g. HP/HC) Occupants 25
 4,1 6,1 8,1 10, 1 12, 1 14, 1 16, 1 18, 1

 • RTP • usages (TUS)
 • flexibility

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MODELLING WHITE-GOODS USAGE
INPUT (USER,
 DEFAULT)

 Household Equipment usage Flexibility Equipment
 (nbr occupants, (mean nbr of cycles, (double tariff (energy class,
 occupation) monthly variation, subscriptions, tariff capacity, program
 waiting time) structure) type)

 CREATING SELECTING
 APPLYING CALCULATING
 STARTING
 TIME-SERIES FLEXIBILITY POWER
 TIME
 OF ACTIVITIES DEMAND
 (agent-based
 (random picking, dw & wm )
 (clustering)
 shifting)

 Time Use Survey Proba. flex. configurations Unit load curves
 (INSEE 2009-2010, (LINEAR 2009-2014, (260 equipment,
 12 000 foyers) 186 foyers) 1200 profiles)
DATABASE

 11

VALIDATION OF THE FLEXIBILITY
POTENTIAL dishwashers
Measured data : 107 households
(Froid Lavage, 2015), 41% TOU
 • 60 dishwashers
 • 100 washing machines
 • 23 dryers

Night-share of the annual energy
consumption :
 Flat tariff TOU tariff

Dishwasher 15% 32%

Washing
 6% 26%
machine

Dryer 15% 16%

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PERSPECTIVES
 FLEX.
 EQUIP.
 FLEXIBILITY
 OBJECTIVE
 68

 58

 48

 38

 28
 SMART
 METER
 18
 0 5 10 15 20 25
 DISTRIBUTION OBJECTIVE

 USERS
 65

 POWER PROFILE
 w/o flex
 68
 60

 58

 55

 48

 with flex
 50

 38

 28 45

 18
 0 5 10 15 20 25 40

 35

 68 30

 58

 25
 4,1 6,1 8,1 10, 1 12, 1 14, 1 16, 1 18, 1

 48

 38

 28

ESTIMATION OF
 18
 0 5 10 15 20 25

THE AVAILABLE
 68

 58

 48

 FLEXIBILITY
 38

 28

 18
 0 5 10 15 20 25

 68

 58

 48

 38

 28

 18
 0 5 10 15 20 25

 OBSERVATION &
 LEARNING
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MERCI !
Related projects :
 • ANR CLEF (2018-2021)

 • Collaboration LaSIE/SGR (2017-2018)

Contacts :
 • Jérôme LE DRÉAU (jledreau@univ-lr.fr)
 • Marika VELLEI (mvellei@univ-lr.fr)
 • Johann MEULEMANS (Johann.Meulemans@saint-gobain.com)
Websites :
 • http://lasie.univ-larochelle.fr/2018-2021-CLEF-ANR
 • https://gitlab.univ-lr.fr/jledreau

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REFERENCES
Journal articles :
 • M. Vellei and J. Le Dréau, “A novel model for evaluating dynamic thermal comfort under
 demand response events”, in Building & Environment (under review).

Conference articles :
 • J. Le Dréau, M. Vellei and Y. Abdelouadoud, “A Bottom-Up Model to Evaluate the Flexibility of
 French Residential Wet Appliances”, in IBPSA 2019 (under review).
 • M. Vellei and J. Le Dréau, “Evaluating Dynamic Thermal Comfort under Demand Response
 Events: a Novel Model Compared against Fanger's PPD Model”, in IBPSA 2019 (under review).
 • J. Le Dréau and J. Meulemans, “Upscaling the flexibility potential of space heating in single-
 family houses”, in CISBAT (under review), 2019.
 • J. Le Dréau and J. Meulemans, “Characterisation of the flexibility potential from space heating
 in French residential buildings,” in 7th International Building Physics Conference, IBPC 2018,
 2018.

Other publications :
 • J. Le Dréau and J. Meulemans, “Building stock characterisation of space heating flexibility from
 single-family houses “, in IEA EBC Annex 67 - Examples of Energy Flexibility in buildings, 2019.
 • ADEME, Systèmes Electriques Intelligents Premiers résultats des démonstrateurs, 2016.
 • ADEME & Artelys, Trajectoires d'évolution du mix électrique à horizon 2020-2060, 2018.
 • OPECST, Note n°11 Le stockage de l’électricité, 2019.
 • RTE, Réseaux électriques intelligents, 2017.

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