Micro and nano for energy
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Microtechnologies, a unique advantage for Energy‐ production, ‐ transportation ‐ use
G. Kotrotsios
N hât l 04 05 2010Neuchâtel, 04.05.2010
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d i 1984…depuis 1984
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 1
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A dAgenda
• Why use micro‐, nano‐ and ICT
• What CSEM is doing today – yesterday?: examples
C f t ti i ti• Comfort optimization
• Presence detection and lighting control
• Automatic Meter Reading (AMR)• Automatic Meter Reading (AMR)
• Tomorrow
• Systems: Data decentralization smart grid• Systems: Data decentralization, smart grid
• Devices: ICT for energy saving and the Next Generation of PV as a
marriage between « traditional » PV and MNT
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 2
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P i tili d i ?Pourquoi utiliser des micro‐ , nano‐,…?
• Axioma I:
– The cheapest KWh is the one that has not been used
A i II• Axioma II:
– The next cheapest KWh is the one that intellently used
• Beyond ecologic production, there is enormous potential for
– economies of consumption– economies of consumption
– Intelligent and economic use in
‐Demand SideDemand Side
‐Supply Side
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 3
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A dAgenda
• Why use micro‐, nano‐ and ICT
• What CSEM is doing today – yesterday?: examples
C f t ti i ti• Comfort optimization
• Presence detection and lighting control
• Automatic Meter Reading (AMR)• Automatic Meter Reading (AMR)
• Tomorrow
• Systems: Data decentralization smart grid• Systems: Data decentralization, smart grid
• Devices: ICT for energy saving and the Next Generation of PV as a
marriage between « traditional » PV and MNT
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 4
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I t lli t S t f C f t t lIntelligent Systems for Comfort control
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 5
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How it works?How it works?
Climate Prediction
External Temperature, Solar Radiation
Internal Temperature
Flow Temperature
Return Temperature
Val e ControlO ti l C t lB ildi
Popt UT_int + -1/Kp
Heating PowerSample Vector
User Adaptation Block
Valve ControlOptimal ControlBuildingBehaviorPrediction User Setpoint, Window OpeningP T_comfort
• Predictif control
• Self‐commissioning adaptive controlSelf commissioning adaptive control
system
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 6
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lower consumption with improved comfort... lower consumption...with improved comfort
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Wh t’ d f ?« What’s good for me »?
f h l b l• Optimisation of the global consumption
• Electric (light, home appliances, IT, etc..)
H ti C f t• Heating, Comfort
• Simultaneously: Electric and Heating
• Per house, neighbourhood, district, etc…
• Centralised versus decentralised optimisation optimisation of chagre (Demand• Centralised versus decentralised optimisation optimisation of chagre (Demand
Side Management)
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A dAgenda
• Why use micro‐, nano‐ and ICT
• What CSEM is doing today – yesterday: examples?
C f t ti i ti• Comfort optimization
• Presence detection and lighting control
• Automatic Meter Reading (AMR)• Automatic Meter Reading (AMR)
• Tomorrow
• Systems: Data decentralization smart grid• Systems: Data decentralization, smart grid
• Devices: ICT for energy saving and the Next Generation of PV as a
marriage between « traditional » PV and MNT
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 9
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C t lli li hti i i t lli tControlling lighting using intelligent sensors
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Th diff i i d i
M t f l t i d l t t
The differences in sensing and processing
Management of electric doors, elevators, etc..
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A dAgenda
• Why use micro‐, nano‐ and ICT
• What CSEM is doing today – yesterday: examples?
C f t ti i ti• Comfort optimization
• Presence detection and lighting control
• Automatic Meter Reading (AMR)• Automatic Meter Reading (AMR)
• Tomorrow
• Systems: Data decentralization smart grid• Systems: Data decentralization, smart grid
• Devices: ICT for energy saving and the Next Generation of PV as a
marriage between « traditional » PV and MNT
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 12
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Automatic Metering ReadingAutomatic Metering Reading
N b tt (i d ti li )• No battery (inductive coupling)
• Low consumption
• ~10 ppm error‐rate OCR in 10 ms
• “Low cost”
• Compact
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 13
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Wh t’ d f ?« What’s good for me »?
l f f h• Real time information for the users
• Reading of consumption of individual appliances
A t t d• A step towards
• smart home
• smart grid• smart grid
• Security Quality of Life Economy Global optimisation• Security, Quality of Life, Economy, Global optimisation
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 14
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A dAgenda
• Why use micro‐, nano‐ and ICT
• What CSEM is doing today – yesterday: examples?
C f t ti i ti• Comfort optimization
• Presence detection and lighting control
• Automatic Meter Reading (AMR)• Automatic Meter Reading (AMR)
• Tomorrow
• Systems: Data decentralization smart grid• Systems: Data decentralization, smart grid
• Devices: ICT for energy saving and the Next Generation of PV as a
marriage between « traditional » PV and MNT
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 15
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M ti tiMotivation
• Low power was always the concern of CSEM
• More recently two topics have been developped CSEM
Wi l N t k ( d f it d b l Zi b )• Wireless sensor Networks (order of magnitude below Zigbee)
• WiseNET
• Solar Energy• Solar Energy
• Solar Island: large scale
• Organic Photovoltaics• Organic Photovoltaics
• How to produce a lever effect between the small and the big?
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M it i li d t d i ti i tMonitoring applied today in preventive maintenance
• Example: Hydropower
• Dams structural monitoring
• Land‐sliding above the dam
• Water turbidity
• Water pollution in the dam
• Generator optimal use (eccentricity and vibrations…)
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 17
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Th ll f th biThe very small for the very big…
Alternative energy production system
Hundreds of monitoring devices
High Density Sensor Network: Monitoring and Optimisation
Sensor Node
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Wh thi ill b ibl t l l ?When this will be possible at large scale?
• Large number of sensor nodes:
• No power supply
Mi i l Di i• Minimal Dimensions
• Negligeable costs
• Easy Deployment• Easy Deployment
• Environmental compatible
• Adequate communication Protocols• Adequate communication Protocols
Exploitation as a system optimisation toolExploitation as a system optimisation tool
Expoitation as energy decrease of a sum of a very large number of
« small » individual energy consumers
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« small » individual energy consumers
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A dAgenda
• Why use micro‐, nano‐ and ICT
• What CSEM is doing today – yesterday: examples?
C f t ti i ti• Comfort optimization
• Presence detection and lighting control
• Automatic Meter Reading (AMR)• Automatic Meter Reading (AMR)
• Solar Islands
• Tomorrow• Tomorrow
• Systems: Data decentralization, smart grid
• Devices: ICT for energy saving and the Next Generation of PV as aDevices: ICT for energy saving and the Next Generation of PV as a
marriage between « traditional » PV and MNT
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 20
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It ill b ibl !!It will be possible!!
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 21
Source: Gene A. Frantz, TI Developer Conf., 2008.
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Energy ScavengingEnergy Scavenging
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 22
Source: MEDEA+ report on “Energy Autonomous Systems: Future Trends in Devices, Technology and Systems,” 2008.
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E H ti O d f it dEnergy Harvesting – Orders of magnitude
Source Caractéristiques Efficacité Puissance (η) collectée
Photovoltaïque Intérieur 0.1mW/cm2 10 µW/cm2
10 24% 10-24% Extérieur 100mW/cm2 10mW/cm2 Vibration/ Mouvement
0 5m@1Hz Puissance 3 Home 0.5m@1Hz 1m/s2@50Hz
Puissance maximale dépend de la source
4 µW/cm3
Industrie 1m@5Hz 10m/s2@1kHz 100 µW/cm3
Energie gThermique Home 20mW/cm2 0.10% 25 µW/cm2 Industrie 100 mW/cm2 0.30% 1-10mW/cm2 Electromagnétique GSM 900MHz 0.03-0.3 µW/cm2 50% 0.1 µW/cm2 1800MHz 0.01-0.1 3 µW/cm2
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 23
Source: Chris van Hoof, ISSCC 2008 Workshop.
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E t it f b tt iEnergy storage capacity of batteries
• Energy storage density continuously
increases~1.5x/decade (~1.04x/year)
• Growth smaller if comparing to wireless• Growth smaller if comparing to wireless
(~1.4x/year), speed of microprocessors
(~1.7x/year) hard disc capacity storage
(~2.0x/year)
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 24
Source: MEDEA+ report on “Energy Autonomous Systems: Future Trends in Devices, Technology and Systems,” 2008.
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T dTrends…
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 25
Source: Paul Wright, “Energy Scavenging/Harvesting,” CITRIS, 2008
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E tEnergy storage
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 26
Source: MEDEA+ report on “Energy Autonomous Systems: Future Trends in Devices, Technology and Systems,” 2008.
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A dAgenda
• Why use micro‐, nano‐ and ICT
• What CSEM is doing today – yesterday: examples?
C f t ti i ti• Comfort optimization
• Presence detection and lighting control
• Automatic Meter Reading (AMR)• Automatic Meter Reading (AMR)
• Tomorrow
• Systems: Data decentralization smart grid• Systems: Data decentralization, smart grid
• Devices: ICT for energy saving and the Next Generation of PV as a
marriage between « traditional » PV and MNT
Copyright 2009 CSEM | Club Ravel , 6 octobre 2009 | G. Kotrotsios | Page 27
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L t b t h t i t t !Last but perhaps most important !
E ’ i h ll id tifi d i th• Europe’s main challenges as identified in the
Strategic Research Agenda of the Photovoltaic (PV) platform
( with considerble contribution by Top Swiss Scientists):( with considerble contribution by Top Swiss Scientists):
• Transit from the PV modules to PV systems: ICT Smart Grid• Transit from the PV modules to PV systems: ICT, Smart Grid
• Combine MNT with « traditional » PV for the next generation
• Rapid « lab to fab »• Rapid « lab to fab »
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C l iConclusions
h l l d d f• Microtechnologies are already used for energy management
E t ti l• Enormous potentiel
• Through Optimisation of small sources of entropy
• Through the usage of subsystems as tools to optimize systemically• Through the usage of subsystems as tools to optimize systemically
• In integrating these tools
• Trend towards
• Device optimization extensively using Micro‐, Nano and ICT technologiesDevice optimization extensively using Micro , Nano and ICT technologies
• System integration
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Thank you for your attention!