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12/8/2016
Smart-buildings integrated in smart-grids: a key challenge of electrical
engineering for the energy transition
Dautreppe Conference, 5-9 december 2016
Grenoble - France
Frederic WURTZ – Senior Researcher CNRS
Benoit DELINCHANT – Assistant Professor - UGA
Presentation of Work from
Europe FP7 Project – Marie Curie
• 2
Outline1° The necessity of an energy transition for the climate
2° The smart grid as part of the solution for the climate issues
3° « Smart Buildings » as keys allies of the «Smart-Grid »Buildings: the main consumers of energy in France / Brazil
Whereas buildings could be one of greatest producer of renewable energy
4°Energy transition scenario thanks to SB integrated in SG
5°What is a Smart-Building (SB)?
6°Scientific and technologic developments in SBDemand side management, Demand Response and Anticipative Optimal supervisionby using modelisation and optimisation
Optimal design of buildings integrating anticipative Management and Demand Response
Multi-physic modelisation of buildings
Experimental platforms in Grenoble: Smart building / Micro grid
7° SB: A complexity calling new scientific approaches and challenges
Physics, modeling and optimisation: yes, but with the right level of complexity
The necessity to introduce the human in the loop• Pro’sumer• Living lab
8°Perspectives and conclusions
The necessity of an energy transition for the climate
How can we inverse the curve and the trend ?For the climate as electrical engineer !
A necessity of the transition• 4
http://www.cop21.gouv.fr/
The smart grid as part of the solution for the climate issues
ElectricalnetworksMutation
TowardSmart grids
= Electricity+
InternetWind Farms
HTA BT
Small Size Hydrolic
Fuel Cell
PV
CHP
Active distribution of energy
Intermittent or random generationClassic generationFully controllable
Production Network Distributionand repartition
63 kV - 750 kV
Network fordistribution
1.5 kV - 50 kV
400 V
New scheme
08/12/2016 • 7
� 3° « Smart Buildings » as keyallies of the «Smart-Grid »
Buildings: the main consumers of energy in France
- In France- In Brasil
Whereas buildings could be one of greatestproducer of renewable energy
Toward the concept of « Smart-Building » -Buildings able to harvest, store, manage production
and demand response
Final consumption of electricity by sector
Sidérurgie; 5.5; 3%
Industrie; 33.6; 21%
Résidentiel-Tertiaire; 68.2;
43%
Argriculture; 2.9; 2%
Transport; 50.4; 31%
Sidérurgie
Industrie
Résidentiel-Tertiaire
Argriculture
Transport
Sidérurgie; 10; 2%
Industrie; 126; 30%
Résidentiel-Tertiaire; 273; 64%
Argriculture; 3; 1%
Transport; 12; 3%
Sidérurgie
Industrie
Résidentiel-Tertiaire
Argriculture
Transport
French final energy consumption 2005(Mtep)
French electricity consumption 2005 (TWh)
Source: http://www.industrie.gouv.fr
% of buildings:43%
% of buildings:64%
The importance of energy in buildings in FranceThe importance of energy in buildings in FranceSidérurgie; 5.5; 3%
Industrie; 33.6; 21%
Résidentiel-Tertiaire; 68.2;
43%
Argriculture; 2.9; 2%
Transport; 50.4; 31%
Sidérurgie
Industrie
Résidentiel-Tertiaire
Argriculture
Transport
Sidérurgie; 10; 2%
Industrie; 126; 30%
Résidentiel-Tertiaire; 273; 64%
Argriculture; 3; 1%
Transport; 12; 3%
Sidérurgie
Industrie
Résidentiel-Tertiaire
Argriculture
Transport
French final energy consumption 2005(Mtep)
French electricity consumption 2005 (TWh)
Source: http://www.industrie.gouv.fr
% of buildings:43%
% of buildings:64%
The importance of energy in buildings in FranceThe importance of energy in buildings in France
Energy productionIndustry
Buildings Transport
Buildings: the main consumerof electrical energy in the network !
Buildings: the main consumers of electrical energy in France
Evolution of final consumptionof electricity by sectorEvolution of energy consumption in buildings in France
• 9
Evolution of energy consumption
Evolution of global electricity consumption
Evolution of usage of electricity energy
Highly dependant from buildings: heating and variation of consumption during the day
• 10
Typical daily electrical consumptionin France
http://www.radiateur-electrique.org/isolation.php
Geographic Reglementary Consumption dependingfrom the climatic zone
http://www.rte-france.com/sites/default/files/bilan_electrique_2013_3.pdf
Thermal sensitivity of electricalconsumption in France
Buildings: the main consumersof energy in Brazil
Electrical Energy Key Figures: why it is important to work on “smart buildings” integrated in “smart grids”
for Buildings in Brazil
1. Electric consumption (%) ?
2. Electrical part in (%) :
1. Public ?
2. Commercial ?
3. Residential ?
3. Most important consumers in residential building ? • 11
• 14
From Prof. Roberto Lamberts, LabEEE
Bioclimatic zones: Z1: 21,5ºC, Z2: 16,9ºC, Z3: 23,1ºC,Z4: 21,6ºC, Z5: 22ºC, Z6: 24,1ºC,Z7: 26.1ºC, Z8: 26.9ºC
Buildings could be one of greatestproducer of renewable energy
And could become the key pillar
of the smart-grid of the future
• 15
Buildings could be one of greatestproducer of renewable energy
• 16
A building can get,
over a year,
more renewable
energy that
it needs
ΣEnergy/over year > 0
Consumption in kwh/year/m²
Building can produce more energy than they need
Buildings can help to:- Harvest- Store- Manage
renewable energy
Buildings could be one of greatestproducer of renewable energyA « smart-building » can be energy positive
What can be done with the excess of energy:
• 17A crazy dream ?
Buildings could become THE KEY PILLARof the smart grid of the future using
only renewable energy
Feed Electrical VehiclesV2H – Vehicule to House concept
Send Electricity to the network
• For other consumers
• For massive storage at levelof the national network
– For summer to winter in France –Interseasonal intermittence
– Thanks to:» Power to Gaz» Big hydraulic pump installation
Buildings could be one of greatestproducer of renewable energy
A dream that can become a reality !
Argued at the french level by an official study …
www.ademe.fr/sites/default/files/assets/.../rapport100enr_comite.pdf
• 18
Toward a 100% electricalmix in 2050 for France
The potentiel of renewable energy exists The evaluated cost is (perhaps?) acceptable
For this option, one key pillar will be the buildings
See video: Reportage France 2 sur le rapport ADEME Un mix ener gétique100% renouvelable en France,
https://www.youtube.com/watch?v=4IcYrG7ZqLQ
PV on Buildings: could be the greatest capacity 34%
(68 GW/196 GW)
Demand response of building willHelp to manage the grid: 18 GW of
demand response
Estimated need: 422 TWhAnnual potential: 1268 TWh
Peak demand in France 102 GWDemand response capabilities of buildings- Hot water tanks: 4 GW (4/102=4%)- Heater/HVAC (75%): 14 GW (14/102=14%)- Oven/Washing machine: 0,695 GW ( 1%)
In global 18/102=17%
4°Energy transition scenario thanks to SB integrated in SG
-Harwest the energy at world level
-The scenario of the energy transition supported by SG-SB
• 19
Energy transition scenario thanks to SB integrated in SG
Smart-buildings & Smart-grids: help for collecting the potential of renewable energy at world level
• 20
The potential The strategy
SG based on SBas a key pillar
EnerN
et, Internet de l'énergie –Y
ouTube
(seehttps://w
ww
.youtube.com/w
atch?v=jl53-LA
ziXg)
A proposal of scenario for the energy transition supported by SG-SB
• 21
The strategy The steps
1°Increasing efficiency
2°Substition of energy production
by decarbonised(**) electricity
3°Electric mobilityusing decarbonized
electricity
buildings as a key contributor
http://ww
w.energy-green.net/blog/
articles/wind-pow
er/wind-turbine-for-green-building.htm
l
V2H(*) concept
The actors
Companies
CitizensLocal
authoritiesStates
(1°,2°,3°: Is the proposed strategy of most of scenarios for energy transtion->See work of Patrick Criqui, member of GIEC, Lab EDDEN Grenoble –
Economie du développement durable et de l’énergiehttp://edden.upmf-grenoble.fr/https://www.futuribles.com/fr/article/transition-energetique-quelle-trajectoire-genealog/
(*) V2H: Vehicule to Home(**): Energy produced with no CO² émissions
5°What is a smart-building ?
Seen by Electrical Engineers
Working on the “smart building” integrated in the “smart grid”
• 22
• 23
What is a smart-building ?The functionnalities
Grid, Generatorsand Storage
Loads
UsersWeather
BuildingAnticipationcapabilities :•Weather forecast
• -> PV, Wind• Internal needs
• Heating/cooling needs
Offers services:• equip. usage• comfort req.
Multi sources control :• arbitration between generators• scheduling production / storage• uncertainties on availability
Load management :• uncontrolled load prediction • scheduling / adjusting / shedding
• 24
What is a smart-building ?The location in the smart environment of the future
Sources and storage
Loads
Users
Météo
Building
Local intelligence
Cloud
Distributed Intelligence
Networks/ Mutualisation
Models
Dynamic
Algorithms
Measures
Uncertainties
What is a smart-building ?Canopea - Solar Decathlon 2012
• 25
The French Rhône Alpes centered in Grenoble won the competition
http://www.g2elab.grenoble-inp.fr/grand-prix-international-solar-decathlon-2012--497448.kjsphttp://www.g-scop.grenoble-inp.fr/accueil/la-team-rhone-alpes-remporte-le-solar-decathlon-europe-2012--499021.kjsphttp://www.echosciences-grenoble.fr/articles/la-team-rhone-alpes-remporte-le-solar-decathlon-2012
« Prise en compte de la complexité de modélisation dans la gestion énergétique des bâtiments », Yanis Hadj Said,thèsede Docteur, docteur de l’université Grenoble alpes, 20 juillet 2016, available soon
6°Scientific and technologic developments in SB
For Electrical Engineers
Focus on some researchers made in my group Working on the “smart building” integrated in the
“smart grid”
• 26
• Demand side management, demand Response and Anticipative Optimal supervision by using modelisation and optimisation
• Optimal design of buildings integrating Demand Side Management and Demand Response
• Multi physic modelisation• Experimental platforms
Issued and objectives for scientific and technological research about SB integrated in SG
Main issues and objectives
Improve efficiency of lighting, appliances, fans and pumps
Help the grid with local production : PV on the roof to supply HVAC
Improve the usage of energy :
• Awareness of people when using energy• Automation / Regulation : automatic sun shading, cooling using fresh air during nights,
controlling HVAC according to meteorological forecast…
=> Improve interaction between grid and buildings:
Optimal power flow including buildings :
• Production : disturbed energy resources management• Consumption : demand side management
For the whole grid / for micro-grids (autonomy)
Building active solution for Demand Response
• 27
Demand side management, demand Response and Anticipative
Optimal supervisionby using modelisation and
optimisation
Optimization trade-off between :
• Energy consumption (or energy price)
• Human comfort
• 28
Smart Buildings offering Demand Side Management, Demand Response, Anticipative optimal supversion
• 29
At the scale of the building:locally adaptation
of production to needs
P
The scientific problematic
• Demand side Management
• Load Matching
• Demand Response
• Anticipativesupervision
24 hours prevision
Weather
Dynamic prices
• 30
Anticipative management and demand Response
But also : MILP, MINLP, SQP and dynamic approaches
Under constraints :
Ax ≤ b
Aeq.x = beq
lb ≤ x ≤ ub
With :
x are the variables (continue, binary or integers)
A, Aeq are matrixes;
f, b, beq are vectors
Objective function to minimize xf T xf T:Formulation : Mainly Mixed Linear Programming
The approach used: Optimization
Solved with : Matlab
CPLEX (Ilog), GUROBI
Smart Buildings offering Demand Side Management, Demand Response, Anticipative optimal supervision
"Optimal Household Energy Management and Economic Analysis: From Sizing To Operation Scheduling",T. T. HA PHAM, C. CLASTRES,F. WURTZ, S. BACHA, and E. ZAMAI, publié dans Advances and Applications in Mechanical Engineering and Technology, Vol. 1, n° 1, pp. 35-68https://halshs.archives-ouvertes.fr/halshs-00323581
Smart Buildings offering Demand Side Management, Demand Response, Anticipative optimal supervision
• 31
The approach used: Resulting optimisation tools
� Option : Ecology
� Option : Economy
� Option : Autonomy
�Option : Confort
Optimizer
"Ancillary services and optimal household energy management with photovoltaic production«C. CLASTRES, T.T. HA PHAM, F. WURTZ, S. BACHA, Energy, ISSN 0360-5442, DOI: 10.1016/j.energy.2009.08.025., volume 35 issue 1, Elsevier Publication, 2010, pp. 55-64, https://hal.archives-ouvertes.fr/halshs-00323576v1
Exemple of demand Side Management
Smart Buildings offering Demand Side Management, Demand Response, Anticipative optimal supervision
• "Lithium-ion Battery Modelling for the Energy Management Problem of Microgrids”, D. TENFEN, E. C. FINARDI, B. DELINCHANT, F. WURTZ, IET Generation, Transmission & Distribution, Volume 10, Issue 3, 18 February 2016, p. 576 – 584, DOI: 10.1049/iet-gtd.2015.0423 , Print ISSN 1751-8687, Online ISSN 1751-8695
• “Load Demand, Batteries, and Electric Vehicles Modelling to the Energy Management of Microgrids”, Daniel Tenfen*; Benoit Delinchant; Frédéric Wurtz; Erlon C. Finardi; Jaqueline Rolim; Rubipiara C. Fernandes, 2nd Elecon Workshop, Magdebourg, Allemagne, 28-29 octobre 2014 available at http://www.elecon.ipp.pt/images/Workshop2/Papers/Load_Demand_Batteries_and_Electric_Vehicles_Modelling_to_the_Energy_Management_of_Microgrids.pdf
Optimal operating of laptops power supply,in order to maximize autonomy
• 33Hoang:Anh Dang, Benoit Delinchant, and Frederic Wurtz, “Toward autonomous photovoltaic building energy management: modeling and control of electrochemical batteries”, IBPSA 2013, Chambery, August 2013, http://www.ibpsa.org/proceedings/BS2013/p_2095.pdf
0 4 8 12 16 20 240
200
400
600
800
Time(h)
Pow
er (
W)
Total consumption power
Photovoltaic power
0 4 8 12 16 20 24-200
0
200
400
600
800
Time (h)
Ele
ctric
al g
rid p
ower
(W
)
0 4 8 12 16 20 240
20
40
60
80
100
Time(h)
SO
C (
%)
Grid (W)
SoC (%)
Pre-chargingbatteries
Auto-consumption
Smart Buildings offering Demand Side Management, Demand Response, Anticipative optimal supervision
�185 inputs
�(50x24)+11=1211 continues variables� (24x24)= 576 binary discretes variables
� (178x24)+1=4273 constraints
• 34
- Charging of the battery with carbonfree energy during the day
- Use of the energy stored in the battery for shaving the peek demandof the evening
• « Gestion des flux multi-énergie pour les systèmes V2H», A. Dargahi,thèse de l’Université de Grenoble, 26 Septembre 2014, https://tel.archives-ouvertes.fr/tel-01111994
• A. Dargahi, S. Ploix, A. Soroudi, F. Wurtz, (2014) "Optimal household energy management using V2H flexibilities", COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, Vol. 33 Iss: 3, pp.777, DOI:10.1108/COMPEL-10-2012-0223
Anticipative demande side Management of Vehicule to Home (V2H)
Smart Buildings offering Demand Side Management, Demand Response, Anticipative optimal supervision
Anticipative demande side Management: trade off consumption - comfort
• 35
• Anticipativesupervision
24 hours prevision
Weather
Dynamic prices
Smart Buildings offering Demand Side Management, Demand Response, Anticipative optimal supervision
http://www.vesta-system.fr/fr/produits/vestaenergy/vesta-energy.html
Industrial solution available at
ELECON: An example of a Portugal - French – Brazilian –
German program about interaction between SG and SB
• 36
Smart Buildings offering Demand Side Management, Demand Response, Anticipative optimal supervision
http://www.elecon.ipp.pt/
Optimal design of buildingsintegrating Demand Side
Management and Demand Response
Especially in sketch phases
• 37
Optimal design of buildings integrating Demand Side Management and Demand Response
building envelope Size of energy systems
Do it simultaneously!État de charge de la batterie au cours de la journéepour un coût d'investissement PV de 1100 €/m²
Chauffage, Ballon,…
kWh
24 h
kWh
24 h
SOC
GRID
The scientific problematic
As early as possible in the designProcess: Integrate Demand Responseand Anticipative Management
State of charge of the battery
Optimal strategycontrol
• "Sketch Systemic Optimal Design Integrating Management Strategy, Thermal Insulation, Production And Storage Energy Systems (Thermal And Electrical): Application To An Energy- Positive Train Station"F. WURTZ, J. POUGET, X. BRUNOTTE, M. GAULIER, Y. RIFONNEAU, S. PLOIX AND B. L’HENORET , IBPSA 2013 – FRANCE, http://www.ibpsa.org/proceedings/BS2013/p_2376.pdf
• “On The Sizing Of Building Enveloppe And Energy System Integrating Management Strategy In Sketch Phase”, IBPSA 2015, http://www.ibpsa.org/proceedings/BS2015/p2142.pdf
Électricité prise sur le réseau
Electricity fromthe network
• 39
The approach used: Optimization
But also possible with: MILP after linerizarion of the models
With :
Ej: the optimisation variable
P: parameters fixed during the optimisation
Fob: objective function, cost, comfort,Si: constraints,
Formulation : We explored Non linear optimisation approach
Solved with : Matlab
CPLEX (Ilog)Own developed tools (CADES, SML – Composer)
, GUROBI – Linear approach
P1⇒
minp
fob(p)
avec gi(p)≤ 0 i=1,l
gi(p) 0= i=l+1,m
pjmin
≤ pj
pjmax≤ j=1,k
P1⇒
min fob(E,P)
Ej
Smax i≤Si(E,P) ≤ Smax i
Emin j ≤ Ej ≤ Emax j
avec
We are exploring: SQP
Optimal design of buildings integrating Demand Side Management and Demand Response
"Optimal Household Energy Management and Economic Analysis: From Sizing To Operation Scheduling",T. T. HA PHAM, C. CLASTRES,F. WURTZ, S. BACHA, and E. ZAMAI, publié dans Advances and Applications in Mechanical Engineering and Technology, Vol. 1, n° 1, pp. 35-68https://halshs.archives-ouvertes.fr/halshs-00323581
,Non Linear approach
Optimal design of buildings integrating Demand Side Management and Demand Response
• 40
User
Geographical localization
Preferences of the user
Typical loads
(devices, typical practices …)
Sizes:� Power of the photovoltaic panels: 4 kW
� Capacity of the batter y: 1140 Ah
� Power subscription on network: 9 kW
� Rated power of generating set : 0 kW
� Option : Ecology
� Option : Economy
� Option : Autonomy
�Option : Confort
Optimizer
Data
base
Sizing including anoptimal control strategy
The approach used: Resulting optimisation tools
Parametric set of sizes
or
Set of solutions in case of Compromises – Pareto Fronts
or
"Optimal Household Energy Management and Economic Analysis: From Sizing To Operation Scheduling",T. T. HA PHAM, C. CLASTRES,F. WURTZ, S. BACHA, and E. ZAMAI, publié dans Advances and Applications in Mechanical Engineering and Technology, Vol. 1, n° 1, pp. 35-68https://halshs.archives-ouvertes.fr/halshs-00323581
Optimal design of buildings by optimisation ?
• 41
The kind of model we use
Electric Equivalentcircuits
The right level of model composed at system level
« Optimal Sizing Of A Complex Energy System Integrating Management Strategies For A Grid-connected Building »,Van-Binh Dinh, Benoit Delinchant, and Frederic Wurtz, IBPSA 2015, http://www.ibpsa.org/proceedings/BS2015/p2141.pdf
P1⇒
minp
fob(p)
avec gi(p)≤ 0 i=1,l
gi(p) 0= i=l+1,m
pjmin
≤ pj
pjmax≤ j=1,k
P1⇒
min fob(E,P)
Ej
Smax i≤Si(E,P) ≤ Smax i
Emin j ≤ Ej ≤ Emax j
avecMethods:- Déterministes Non Linéaires (Gradient SQP)
Model composer CADES V3.0
Projet VEGEP
Solved optimisation problem
Optimal modeling and design of buildings ?The example of an Energy positive railway Station
An example of use case
« Les enjeux de la conception en phase d'esquisse pour les systèmes du génie électrique : illustration sur le cas des systèmes énergétiques pour les bâtiments », F. Wurtz , B. Delinchant , Van Binh Dinh , Julien Pouget , Xavier Brunotte, SGE 2014 - Symposium de Génie Electrique 2014, Cachan : France (2014), http://hal.archives-ouvertes.fr/hal-01024644
Optimiser CADES
• Dynamic tarifof energy
5 c€/kWh
70 c€/kWh
• Area
• Cost of technology- Building- Systems (PV, Battery,heating, co-generator,…)
• Life-time (30 ans)
• Discount rate
•Optimal results
•Building Envelop
•Systems
•Management•strategy
Optimisation with hundreds to thousantsParameters and constraints
Parametrizedoptimisation results
179 m²
85 m²
5 c€/kWh
70 c€/kWh
6 c€/kWh
9 c€/kWh
Dynamic tarification
Yellow tariff
Optimal modeling and design of buildings ?The exemple of an Energy positive railway Station
The tools developed and some results
• "Sketch Systemic Optimal Design Integrating Management Strategy, Thermal Insulation, Production And Storage Energy Systems (Thermal And Electrical): Application To An Energy- Positive Train Station"F. WURTZ, J. POUGET, X. BRUNOTTE, M. GAULIER, Y. RIFONNEAU, S. PLOIX AND B. L’HENORET , IBPSA 2013 – FRANCE, http://www.ibpsa.org/proceedings/BS2013/p_2376.pdf
• “On The Sizing Of Building Enveloppe And Energy System Integrating Management Strategy In Sketch Phase”, IBPSA 2015, http://www.ibpsa.org/proceedings/BS2015/p2142.pdf
Modelisation, multi-physics and inter-operabilityfor buildings
* Thèse Sana Gaaloul, «Interopérabilité basée sur les standards Modelicaet composant logiciel pour la simulation énergétique des systèmes de bâtiment », https://hal.archives-ouvertes.fr/tel-00782540* "A New Co-Simulation Architecture for Mixing Dynamic Building Simulation and Agent Oriented Approach For Users Behaviour Modelling"S. GAALOUL, HOANG-ANH DANG, A. KASHIF, B. DELINCHANT AND F. WURTZ, IBPSA2013,Le Bourget du Lac, FRANCE, http://www.ibpsa.org/proceedings/BS2013/p_1312.pdf
Smart Building Platform V1 inGrenoble
12/8/2016•47
Motor / Speed driver WattmeterPower Switch
Wirelesssensors
• Complete description: http://predis.grenoble-inp.fr/• « Modélisation en vue de la simulation énergétique des bâtiments :
Application au prototypage virtuel et à la gestion optimale de PREDIS MHI», thèse del’université de Grenoble, 04 Novembre 2013, http://tel.archives-ouvertes.fr/tel-00957613
• "Building Simulation of Energy Consumption and Ambient Temperature: Application to The Predis Platform« , HOANG-ANH DANG, S. GAALOUL, B. DELINCHANT, AND F. WURTZ, IBPSA 2013 , http://www.ibpsa.org/proceedings/BS2013/p_2096.pdf
• Measures and characterization• Design and operation of buildings• User behavior
Deploiement of plug and play communication architecture for sensors&actuators – Monitoring supervision solutions
• 48
Smart Building Platform V1 inGrenoble
Complete description: http://predis.grenoble-inp.fr/
• 49
Modeling and optimisation tools
From the Smart Building Platform to prototype and real smart-buildings
Smart building platformAdvanced prototypes
Canopea - Presentation Movie - Solar Decathlon 2012:https://www.youtube.com/watch?v=p28tFxd9MZY
Real housesProject COMEPOS: Deploiement of energy positiv housesIn France
http://www.comepos.fr/
modification of the energy
management strategies
recomputation of energy management strategies
proposition of energy management strategies
New Experimental building platform
GreEn-ER
Imagined and specified thanks to the experiment of the first platform
Grenoble, FRANCE
• 50
Smart Building Platform V2 inGrenoble
• 51
Smart Building GreEn-ER – Building of G2ELAB since July 2015
22 000 m² - 2000 usersHighly efficient – Massive use of sensors
Inside GreEn-ER: an autonomous and energy positive platforms
Smart Building Platform V2 inGrenoble
CPV : Concentrating Photovoltaics,2-axis sun tracker. 10kWp (9x1.14kWp)
Eolian : vertical axis, (1kW per unit)
CHP : Combined Heat & power(10kW electric, 25kW thermic)
…
• 52
GreEn-ER – MHI*
*MHI: Monitoring et Habitat Intelligent – Monitoring and Smart House Platform
600 m², autonomous micro-grid, 50 users, …
Complete description will be soon available at: http://predis.grenoble-inp.fr/
7° SB: A complexity calling new scientific approaches and challenges
Physics, modeling and optimisation with the right level of complexity
The necessity to introduce the humain in the loopPro’sumer as active consumer
Pro’sumer as active investorSmart-Building & Human in the loop
The real key pillar of the energy transition ?The need of Living lab
• 53
Physics, modeling and optimisation with the right level of complexity
Example of equivalent circuit model for optimal anticipative control
• 54
Efficient models are not the more complexBuilding
Physical thermal Equivalent circuit
From 2 to 15 parameters
(Thermal resistance and capacities)
Measures
WinterNumber of parameters
Err
orof
the
mod
el There is the good compromisein complexity
From phd defense A. Le Mounier, « Méta-optimisation pour la calibration automatique de modèles énergétiques bâtiment pour le pilotage anticipatif », 29 juin 2016, Thèse en génie électrique de la communauté université Grenoble Alpes, soon available
Physics, modeling and optimisation with the right level of complexity
• 55
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Analytic Semi analytic Numeric0D 1D 2D 3D
Static Dynamic
Users:The main
Uncertainty !
Necessity to introducethe human in the loop !
For Demand Response will everything be automatic ?
Was our first idea, but …
Our current hypothese is that the user/inhabitants must be involved
• Inhabitant want to decide, must understand, …• If they can not decide, and do not understand -> Reject
The consumer will becomean active pro’sumer
Smart-Building & Human in the loop – The concept of pro’sumer as active consumer
modification of the energy management strategies
recomputation of energy management strategies
proposition of energy management strategies
Usersunderstanddecide, …
Dynamic prices
Nudges EnvironmentalSignals
Demand Response
Sell/exchangeof energie
Consumptionof Energy
Advices, help, …
The pro’sumer can invest and own the system of energyproduction mainly situated over/near from Smart-buildings
Smart-Building & Human in the loop – The concept of pro’sumer as active investor
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« Centrales villageoises » (See http://www.centralesvillageoises.fr )Cooperatives of citizens invest ang manage PV stations
Installed on roofs
14 initiatives in France100 kWc
cover (in average) the electrical needs
of the investors (heating excluded)
With ethic fundinghttp://energie-partagee.org/
Credible Scenario in the context of the3rd industrial industrial revolution
popularized by Jeremy Rifkin* (among others)
Five pillars of the Third Industrial Revolution neededfor the energy transitions
The second one is:
• Transforming the building stock of every continent into greenmicro–power plants to collect renewable energi es on-site
Revolution of Internet of Energie (EnerNet) -> Is arrivinghttp://www.revolutions-energetiques.com/interview-de-joel-de-rosnay/ orEnerNet, Internet de l'énergie – YouTube (see https://www.youtube.com/watch?v=jl53-LAziXg)
What means that
Citizens in « smart-building » can create cooperative able by agregation to be as big and powerful than the existing group of production and distribution of Energy and Electricity ?
Smart-Building & Human in the loop – The real key pillar of the energy transition ?
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A dream ? Can really the final users in their « smart-building » take the power and promote the energy transition ?
•https://en.w
ikipedia.org/wiki/T
he_Third_Industrial_R
evolution_(book)
Can really the final users in their « smart-building » take the power and promote the energy transition ?
http://videos.tf1.fr/jt-we/2014/ils-achetent-groupe-pour-diminuer-leur-facture-d-electricite-8511534.html
In Espagna 500 000 famillies joigneda cooperative and negociate newtarification for their Electric BillUp to 20 % of price decrease
https://www.quieropagarmenosluz.org/
http://www.placedesenergies.com/achats-groupes-electricite.php
Emerging initiativesin France
Extrapolate if citizens with their« smart-buildings » will exchange
their own produced energie-> Enernet !
Smart-Building & Human in the loop – The real key pillar of the energy transition ?
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GreEn-ER-MHI ournew platfom is aLiving Lab
Producingscience and technology
Test it with real users
Those users caninnovate
See what works(or not) withreal users
« Google » innovation strategy !
User can become designers of the building (and reciprocally)
Experiments with the « Human in the loop »
Measure and modeling of comfort directly feeled by the users
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Smart-Building & Human in the loop – The need of the concept of living lab
Users can modify,Model, diagnose
the « smart-building »
Benoit Delinchant, Frédéric Wurtz, “The Grenoble PREDIS – Building platform: A living lab and experimentallab for the study of energy and comfort in Smart-Buildings”, Third ELECON Workshop , url: http://www.elecon.ipp.pt/images/Workshop3/Presentations/Elecon3.pdf
Inácio Bianchi, Antonio Faria Neto,Benoit Delinchant, Frederic Wurtz, Samer Alabrach“Energy Saving Using Ceiling Fans in Environmental Comfort Systems”,Third ELECON Workshop, url: http://www.elecon.ipp.pt/images/Workshop3/Presentations/Elecon9.pdf
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Conclusions & Perspectives
Need of an energy transition
Based and Smard-grids with Smart-Buildings as a key Pillar
New frontier for electrical engineering:
New scientific and technological development
• High efficient components and materials• Models, optimisation tools• Design tools, optimal control tools
Electrical engineering and science are the conditions of the transition But the final user must be and will be placed at the center of the game
The key research point: the right level of physic, automatisation, …
Pro'sumer
Not only a techno push approach
But also a user centered services approach
That must be imagined in lab, but tested in living-labs (platforms) with the final user as “human in the loop”
Need of a new inter-disciplinary research approach !
If you want a 1 page summary in french
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http://www.liberation.fr/debats/2016/01/14/le-batiment-intelligent-cle-de-la-transition-energetique_1426468See also:
https://lejournal.cnrs.fr/billets/le-batiment-intelligent-cle-de-la-transition-energetique