thermal energy storage modelling device scale prospective
TRANSCRIPT
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Thermal energy storage modelling –device scale prospective
Dr Adriano Sciacovelli
Birmingham Centre of Energy Storage University of Birmingham, United Kingdom
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Outline
Thermal energy storage technologies
Relevant scales in TES – focus on device
Modelling similarities and distinctive features of TES
technologies
– Sensible
– Latent
– Thermochemical
Couplings across scales
Conclusions
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TES modelling scales – focus at device scale
Informed by techno-
economic
Informed by
fundamental science
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TES technologies – Top down view
Energy conversion
Transport
Medium
Heat/cold storage process
Heat or
cold
Energy network
UsersEnergy
Ding, Y et al. UK TES (2015).
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TES technologies – Top down view
Transport
Medium
Heat / cold release process
Energy conversion
Heat or
cold
Energy network
UsersEnergy
Ding, Y et al. UK TES (2015).
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TES technologies – Classification
Energy conversion
Heat or
cold
Energy conversion
Heat or
cold
Transport
Medium
Transport
Medium
Sensible storage materials Phase change materials Thermochemical storage material
Energy and Buildings 2015;15:414-419
Thermochemical TRL 3-4Latent TRL 4-6Sensible – in use
Technological potential Modelling challenges
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TES technologies – Classification
Salt hydrates,
water-salt
solutions
Macro-
encapsulated
materials
Composites
Zeolites
Salt hydrates
Paraffin, sugar
alcohols
Metal
Oxides
Hydro-oxides
Cabeza, L.F. et al. Advances in Thermal storage (2015).
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TES - common features across technologies
Energy conversion
Heat or
cold
Energy conversion
Heat or
cold
Transport
Medium
Transport
Medium
Heat transfer fluid
(direct)Heat transfer fluid
(indirect)Integrate heat transfer &
storage fluid
Mehling, H. et al. Heat and cold storage with PCM An up to date introduction (2008)
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Physical modelling similarities/distinct features
Sensible Latent Thermochemical
Single phase flow
Conduction/convection
heat transfer
Phase change
Multi species
Multiphase flow ( )
reactions
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Physical modelling similarities/distinct features
Ph
ysic
al in
sig
ht a
nd
assu
mp
tion
s
Balance equations• Mass balance(s)
• Linear/angular momentum
• Energy balance(s)
• Entropy
Constitutive relations• Mass (Darcy, Forchheimer,..)
• Heat (Fourier, Newton,
Radiation
• Phase change (enthalpy, cp)
• Reaction kinetics (linear driving
force, …)
• Mixture rules (effective
properties, interactions…)
• Constraints
• …G
ove
rnin
g e
qu
atio
ns
Boundary and initial
conditions
Numerical methods• FEM
• FDM
• FVM
• …
Reference solution• Analytic solutions
• Test cases
• …
Model
Sim
ula
tion
res
ults
Performance
Predictions
Parametrization &
design
Control &
diagnostic
Inverse modelling
Forward modelling
Optimization
Material
dependentSystem
dependentValidation
Experiments
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Sensible thermal energy storage
Liquid air
storage
WO 2012/020233 A2
𝑇 → 𝑇𝑜𝑢𝑡𝑇𝑜𝑢𝑡 𝑇𝑖𝑛
𝑻 → 𝑻𝒐𝒖𝒕
Sciacovelli, A. et al. Appl. Energy 190, 84–98, 2017.
Sciacovelli, A. et al. J. Energy Resour. Technol. 140, 22001, 2017.
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Sensible thermal energy storage
Momentum:
Continuity:
Energy (fluid/solid):
0i
i
v
x
iji ij L
j j
v vv F
t x x
f ss s sj f s
j j j
T TT T Tv St Nu T T
t x x x
1s s
f s
j j
T TSt T T
t Pe x x
2
2
1p p
p
T TPe r
t r r r
𝑇𝑜𝑢𝑡
𝑇𝑖𝑛
Sciacovelli, A. et al. Appl. Energy 190, 84–98, 2017.Esence, T. et al. Sol. Energy 153, 628–654, 2017
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Sensible thermal energy storage
LAES cycles
TES cycles
𝑇𝑜𝑢𝑡
𝑇𝑖𝑛
𝑻 → 𝑻𝒐𝒖𝒕
𝑻 → 𝑻𝒐𝒖𝒕
Sciacovelli, A. et al. Appl. Energy 190, 84–98, 2017.
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Sensible thermal energy storage
Material-device coupling plays a role even for conventional
materials
Sciacovelli, A. et al. Appl. Energy 190, 84–98, 2017.
Quartzite rocks
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Latent heat thermal storage
Materials
Ta
rge
t a
pp
lic
ati
on
1
2
46
5
3
[1] Axial fins [2] Y fins [3] Radial fins
[4] Corrugated
fins[5] Pin fins [6] Triple tube
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Latent heat thermal storage
Heat transfer fluid
(indirect)
Solid PCM (on
the pipe)
Liquid PCM
Heat transfer fluid
𝑻 → 𝑻𝒐𝒖𝒕
𝑻𝒊𝒏
𝑻𝒐𝒖𝒕
Sciacovelli, A. et al. Int. J. energy Res. 73, 1610–1623, 2013.
Sciacovelli, A. et al. Int. J. Numer. Methods Heat Fluid Flow 26, 489–503, 2016
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Latent heat thermal storage
phase change (energy) enthalpy method
co-existence of solid/liquid (fluid flow) liquid fraction/darcy term
Natural convection Boussinesq approximation
Sciacovelli, A. et al. Int. J. Numer. Methods Heat Fluid Flow 26, 489–503, 2016
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Latent thermal energy storage
Momentum:
Continuity:
Energy (solid/liquid PCM):
0i
i
v
x
Prij gi i
j i i L
j j
v vv Ra e T s v F
t x x
1 1 s sj
j j j
T Tf T fL v L k f
T t T x x x
• Flow-energy coupling
• Intrinsically non linear
• Need to track melting front
• Strong property-process coupling
Sciacovelli, a et al. Appl. Energy 137, 707–715, 2015
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Latent thermal energy storage
Extracted energy 1000s 2000s
Initial configuration 46.3% 63.9%
Single bifurcation 52.2% 71.8%
Double bifurcation 58.5% 88.0%
-20
0
20
40
60
80
100
-200
-150
-100
-50
0
0 250 500 750 1000 1250 1500 1750 2000
Time
Rel
ativ
e d
iffe
ren
ce
Hea
t fl
ux
(W/c
m2
)
Sciacovelli, a et al. Appl. Energy 137, 707–715, 2015
T [K]
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Latent TES – optimization coupling
FE analysis
Sensitivityanalysis
Update with gradient based
optimizer
Convergence?
STOP
No
Yes
Regularization
START
- 71 %
Pizzolato, A. Sciacovelli A et al. Int. J. Heat Mass Transf. 113, 875–888, 2017
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Conclusions – couplings across the scales
Ph
ysic
al in
sig
ht a
nd
assu
mp
tion
s
Balance equations• Mass balance(s)
• Linear/angular momentum
• Energy balance(s)
• Entropy
Constitutive relations• Mass (Darcy, Forchheimer,..)
• Heat (Fourier, Newton,
Radiation
• Phase change (enthalpy, cp)
• Reaction kinetics (linear driving
force, …)
• Mixture rules (effective
properties, interactions…)
• Constraints
• …G
ove
rnin
g e
qu
atio
ns
Boundary and initial
conditions
Numerical methods• FEM
• FDM
• FVM
• …
Reference solution• Analytic solutions
• Test cases
• …
Model
Sim
ula
tion
res
ults
Performance
Predictions
Parametrization &
design
Control &
diagnostic
Inverse modelling
Forward modelling
Optimization
Material
coupling
(direct)
System
coupling
(direct) Validation
Experiments
material and
system couplings
(Indirect)