improved heat metering – dh substation control using sensor fusion networks prof. jerker delsing...
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Improved heat metering – DH substation control using sensor fusion networks
Prof. Jerker Delsing
Y. Jomni, K. Yliniemi and Dr. J. van Deventer
EISLAB
Luleå University of Technology
Sweden
Vision
Sensors on Internet High accuracy sensor technology Sensor talks TCP/IP Minimal size < 1 cm3
Power life time > 2 year Wireless ad-hoc networking Roughed packaging Ad-hoc application integration Secure
< 1 cm3
Sensor networks
Sensor use of a locally available data
System optimization based on local sensor fusion
Sensor fusionSystem optimization
Mulle – EIS platform
• Minimal ultra-light little EIS
• < 4cm2, 22x25x10 mm, including power
• Full EIS sensor network functionality
– TCP/IP
– Ad-hoc wireless networking
– Security Temperature sensor
District heat substation traditional
Flow
Heat exchanger
withcontrol valveTr
Tap hot water
Space heating
Heat system controler
Tvv
TuTi
Tf
Heat meter
District heat substation with sensor network system
Flow
Heat exchanger
withcontrol valveTr
Tap hot water
Space heating
Heatmeter & system controler
Tvv
TuTi
Tf
Enable use of more advanced heat metering algorithms
Adaptive heat meter algorithm Feed forward heat meter algorithm
Estimation of hot water flow
Space heating and hot water flow have different time scales
Error in hot water flow estimation
Estimation of tap warm water
System optimization from using sensor fusion networks
Heat metering Clearly improved measurement accuracy
Estimation of tap hot water flow Accuracy ~2%
Estimation of tap hot water energy Accuracy ~2% Use of additional temperature improve accuracy ~1%
District heat substation with sensor network system
Flow
Heat exchanger
withcontrol valveTr
Tap hot water
Space heating
Heatmeter & system controler
Tvv
TuTi
Tf
Internet
Network of DH substations
DH-substation
InternetDH-substationDH-substation
DH-substation
System optimization from using sensor fusion networks
Sub station optimization
Maximize T Reduced forward temperature
Total system energy efficiency optimization
New customer communication - services
Usage patterns
Heat
Tap hot water Customer system optimization, examples
Indication of lowered environmental impact - i.e. CO2
Remote optimization of control loops for reduced energy cost
Conclusions
Sensor fusion networks enables Clearly improved heat metering Additional data can be generated - hot water usage System optimization enabled Customer communication enabled
http://www.csee.ltu.se/eislabfo