TU Delft WHISPERING WITH APPLIED SMART METERS
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1 WHISPERING WITH SMART METERS ir. Eric Willems TU Delft APPLIED PHYSICS Innovation manager HUYGEN TNO Cauberg-Huygen Deerns Applied research built environment TKI and EU-H2020 funding Give Brains To buildings, TUD 2020-02-07
Transcript of TU Delft WHISPERING WITH APPLIED SMART METERS
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WHISPERING WITH SMART METERS
ir. Eric Willems TU DelftAPPLIED PHYSICS
Innovation managerHUYGEN
TNOCauberg-Huygen
Deerns
Applied research built environment
TKI and EU-H2020 funding
Give Brains To buildings, TUD 2020-02-07
THE VALUE OF SMART METER DATA
Predict energy use/costs
Detect mal function or anomalies
Interact with energy grid/district
Identify user behaviour
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“DeltaT, predictor for heating”
“Date-time, predictor for occupant behavior”
“Other influential factors are minor”
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December 2016 – March 2017
18% of the time shows poor indoor air quality
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OCCUPANT BEHAVIOUR AND INDOOR AIR QUALITY
Decision tree in search for hot water
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ENERGY PERFORMANCE AND OCCUPANT BEHAVIOUR
• Indoor minus Outdoor temperature (DeltaT)
is key
• Date-time also indicator
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OCCUPANT BEHAVIOUR FROM ELECTRICITY USE
Box-plot of hourly electricity use
OFFICE BUILDINGS
Zelfde plaatje als voor gas
Train and Test dataWith actual - not predicted - climate data
BUILDINGS BEHAVE ENERGTICALLY LINEAIR
DeltaT, predictor for heating
Date-time, predictor for occupant behavior
Other influential factors are minor
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RESEARCH DEVELOP-MENT
MARKET UPTAKE
Gezondheidszorg
Renovatie & transformatie
Wonen & retail
Bedrijfsgebouwen
Cultuur, recreatie & sport
Onderwijs
Cultuur, recreatie & sport
Eric Willems – Innovation [email protected]+31 6 52351683
www.huygen.netwww.sensi-sensoren.nl
