DYNAMIC MODELLING OF THERMAL GRIDS AND BOREHOLE THERMAL STORAGE Hanne Kauko [email protected] Karoline Kvalsvik [email protected] RockStore Workshop, Stockholm 20.9.2018
Jun 28, 2020
DYNAMIC MODELLING OF THERMAL GRIDS AND BOREHOLE THERMAL STORAGE
Hanne Kauko [email protected]
Karoline Kvalsvik [email protected]
RockStore Workshop, Stockholm 20.9.2018
Outline
1. Background from previous projects
2. Dynamic modelling of thermal systems
3. Earlier results
4. Tasks in RockStore
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KPN INTERACT (2013-2017) – Efficient interaction between energy demand, surplus heat/cool and thermal storage in building complexes
.
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Results from INTERACT:Comparison of simulation software for modelling BTES
• TRNSYS• Polysun• Modelica• IDA ICE• Matlab/Simulink
+Carnot• Earth Energy
Designer (EED)
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IDA ICE
IPN DSTG (2015-2017) - Development of Smart Thermal Grids
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KPN LTTG+ (2018-2020) - Local low-temperature grids with surplusheat utilization
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Our approach: dynamic modelling usingDymola/Modelica
• "Dynamic" instead of steady-state: new opportunities and added complexity• Necessary realism in systems with energy storage• Requires a control strategy and a control system
• Physical models in Modelica/Dymola• Object-oriented, easy reuse of components• Flexible, full control of code
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A model of a local thermal grid shouldinclude:
• Loads, pipes and supplier
• Demand profiles and customer substation
• Ambient temperature and heat loss
• Pumps and pressure loss
Loads and user profiles
Measured demand
(various building types)
Heat exchanger models
using NTU method
valves
Secondary fluids
with own pumps
Radiator in
contact
with 21 °C
Control
temperature
Figure taken from: Kauko, Hanne; Kvalsvik, Karoline Husevåg; Rohde, Daniel; Nord, Natasa; Utne, Åmund. (2018)
Dynamic modeling of local district heating grids with prosumers: A case study for Norway. Energy. vol. 151.
Pipes
Temperature, mass flow and pressure in given
Heat loss for twin pipes (Wallenten)Pressure drop, aiming for R-value of 150 Pa/m
Length, inner diameter, internal distances, conductivity of insulation and soil
Temperature, mass flow and pressure outfound
Ambient temperature
Brøset – modelled area
Figure taken from: Kauko, Hanne; Kvalsvik, Karoline Husevåg; Rohde, Daniel; Nord, Natasa; Utne, Åmund. (2018) Dynamic modelingof local district heating grids withprosumers: A case study for Norway. Energy. vol. 151.
Supplier and prosumer
Figures taken (and the left modified) from: Kauko, Hanne; Kvalsvik, Karoline Husevåg; Rohde, Daniel; Nord, Natasa; Utne, Åmund. (2018) Dynamic modeling of local district heating grids with prosumers: A case study for Norway. Energy. vol. 151.
BTES?Daniel Rohde’sDymola version of a model in Bauer, D., et al. (2011). "Thermal resistance and capacity models for borehole heat exchangers." International Journal of Energy Research 35(4): 312-32
Solar+BTESConclusion: • can supply any amount• pure matter of scaling
Cold fluid down
Hot fluid up
BTES model in Modelica
• BTES model developed for the BTES park at Ljan school, Oslo
• Seasonal storage of solar collectorsintegrated in the school yard• 24 x 200m boreholes• Heat pump applied in the winter
• Modelling results validated againstmeasurement data
• Later the model was modified and tested for seasonal storage of high-temperature heat14
Charging at HT over summer and discharging over winterInlet and average outlet temperatures from the BTES park with different borehole depth
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d = 40 m
d = 20 md = 10 m
Time [h]
Tem
pera
ture
[°C]
Charging:180 MWh heat at 90 °C and a constantmass flow over the summer (5 months)Discharging:Corresponding to measured heat demand from a apartment block of på 2082 m2
Temperature profile on the ground over a year, with a boreholdedepth of 20 m
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Models in RockStore?
• Adjust the model to match BTES parks included as case studies in RockStore and validate the model towards measurement data
• Integrate the BTES-park model in a model of a local DH-grid?• Study the potential of HT-seasonal storage in building areas identified as case studies in
RockStore
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Teknologi for et bedre samfunn