DYNAMIC MODELLING OF THERMAL GRIDS AND BOREHOLE THERMAL STORAGE

Hanne Kauko hanne.kauko@sintef.no

Karoline Kvalsvik kakv@norceresearch.no

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