Model for thermal energy storage in packed beds with gaseous heat
transfer fluid
1.
Purpose of model
The model describes a sensible high-temperature packed-bed
thermal energy storage unit. It is composed of the packed-bed,
fluid in and outlet spaces, and thermal insulation. Gaseous heat
transfer fluid and solid media storage material are generally
assumed. It has been validated with air as heat transfer fluid and
natural rock as storage material. Main focus is the
- transient behavior of the temperature field in the packed
bed,
- fluid pressure loss and
- transmission heat losses to the environment.
2.
Level of detail, physical effects considered, and physical
insight
- The packed bed is discretized in one dimension, which is the
main fluid flow direction.
- A single energy equation is used for each finite volume,
meaning particle and fluid temperature are not distinct, but a mean
packed-bed temperature is used. This generally holds for ideal heat
transfer between the storage material and heat transfer fluid.
Neverthess, the effect of a limited heat transfer between both can
be still taken into account by adoption of the effective packed-bed
thermal conductivity correlation for example using the approach of
Vortmeyer (1974).
- An additional body force according to the Darcy-Forchheimer
equation is added to the dynamic momentum balance to account for
the packed bed flow resistance.
- Enclosed fluid volumes on the hot and cold side of the storage
unit are included using a single control volume. They can be used
to model additional pressure and heat loss at the fluid in- and
outflow.
- An additional heat port is added between the packed bed and air
in and outlet space. It can be used to account for other means of
heat transport such as conduction, radiation or natural convection
besides the advective energy transport into and out of the packed
bed.
- The thermal insulation model is replaceable and can therefore
consider static or dynamic heat transfer with various heat paths
and insulation layers.
- A storage material medium model is required, which has an
additional state variable for the specific internal energy in order
to account for a temperature variant specific heat capacity.
3.
Limits of validity
- The one-dimensional spatial representation leads to the
plug-flow assumption, meaning no lateral temperature and velocity
variations are taken into account
- No gravitational force is taken into account in the dynamic
momentum balance, as a horizontal air flow direction has been used
at all tested plants so far.
- Natural convection inside the packed bed is not taken into
account
- The convective heat transfer between packed bed and insulation
depends on the lateral packed bed temperature profile. This profile
generally requires a dynamic model for the heat transfer
coefficient. Nevertheless, several correlations are implemented,
but the user should be aware of this.
- The thermal capacity and flow resistance of the grating used to
hold the storage material at in and outlet is not taken into
account, but added to the packed bed volume
4.
Interfaces
- Hot Air Inlet/Outlet
- Cold Air Inlet/Outlet
5.
Nomenclature
(no
remarks)
6.
Governing Equations
(no
remarks)
7.
Remarks for Usage
- The heat transfer
fluid momentum balance is dynamic to allow very small mass flows
without numerical errors
- The mean sphericity
describes the ratio of the surface of a set of monodisperse spheres
with the same number and overall volume as the particle set to the
particles set surface. It thus is not solely depended on the
particles shape, but also on the particle size
distribution.
8.
Validation
The model has been validated with two experimental setups of
Siemens Gamesa Renewable Energy in Hamburg-Altenwerder (6 MWh_th)
and -Bergedorf (130 MWh_th), Germany.
9.
References
[1] M. von der Heyde,
Abschlussbericht zum Teilprojekt der TUHH im
Verbundforschungsprojekt Future Energy Solution (FES), BMWI
03ET6072C, 2021
[2] M. von der Heyde,
Electric Thermal Energy Storage based on Packed Beds for Renewable
Energy Integration, Dissertation, Hamburg University of Technology,
2021
10. Version
History
First Version in
04.2020 for the research project Future Energy Solution (FES) by
Michael von der Heyde (heyde@tuhh.de)
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