pumped thermal exergy storage past, present and...
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Pumped Thermal Exergy Storage Past, Present and Future
Alexander White
Josh McTigue, Pau Farres-Antunez, Haobai Xue
Caroline Willich, Christos Markides (Imperial), Chris Dent (Durham)
Department of Engineering
UK Energy Storage Conference Birmingham. 1st December 2016
What is Pumped Thermal Exergy Storage?
• The literature uses several names… • PHES: Pumped Heat Electricity Storage • TEES: Thermo-Electrical Energy Storage
Work Work + ? Thermal exergy Thermal exergy Heat pump Heat engine Storage
CHEST: Compressed Heat Energy Storage SEPT: Stockage d’Electricité par Pompage Thermique
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Hot Storage
Cold Storage
Combined
CHP
Th
pW
Q0
Qc
CHP
pW
Qh
Qc
Tc
Th
T
CHP
c
pW
Qh
Q0
T0
Possible embodiments of PTES
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Possible embodiments of PTES (red = Isentropic’s PHES)
• Storage type:
- hot / cold / combined
- sensible heat / latent heat
- packed bed / liquid tank / other (e.g., concrete)
• Thermodynamic cycle:
- Rankine / Joule-Brayton / other (e.g., transcritical CO2)
• Compression & expansion:
- turbomachinery / reciprocating / other
• Heat exchange:
- direct (packed bed) / intermediate HX
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A (very) brief history of PTES
1852: Kelvin’s “Heat Multiplier”
2007: (Oct): Isentropic’s PHES patent
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A (very) brief history of PTES
1852: Kelvin’s “Heat Multiplier”
1924: “Thermodynamic” steam- based storage device (Marguerre)
1977: Forerunner of LAES (Smith) 1978: First solely thermal energy storage system (Cahn)
2007: (Jan): PHES patent (Wolf) 2007: (Oct): Isentropic’s PHES patent
Last Thursday: Isentropic’s SVS engine is “turned over”
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Whole-system analysis (Strbac et al 2012)
-0.6-0.4-0.20.00.20.40.60.81.01.2 46 31 25
2 5 10
Annu
al s
avin
g, ´£
bn/y
Installed capacity, GW
Storage cost, ´£/kW.y
savingscost
-0.6-0.4-0.20.00.20.40.60.81.01.2 111 75 41
2 5 10
Annu
al s
avin
g, ´£
bn/y
Installed capacity, GW
Storage cost, ´£/kW.y
Bulk storage (2020) Distributed storage (2020)
• Savings from distributed storage are greater for a given storage cost
• Benefits are relatively insensitive to storage efficiency
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Cost minimisation and endoreversible stuff (Thess, Guo et al)
Totalcost = Engine
cost+ Cost of heat
exchange + Storagecost
C = keWe + kxAx + ks
Es
ρe
CWe
= ke + kxAxWe
+ kstd
ηe ρe
A crude model of costs:
endoreversible analysis minimises this
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Cost minimisation and endoreversible stuff (Thess, Guo et al)
Totalcost = Engine
cost+ Cost of heat
exchange + Storagecost
C = keWe + kxAx + ks
Es
ρe
CWe
= ke + kxAxWe
+ kstd
ηe ρe
A crude model of costs:
endoreversible analysis minimises this
Figure courtesy of Markides
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Endoreversible analysis: maximum power of CHE
Q1 = αh(Th −T1)
Q2 = α0(T2 −T0)
W.p eW
.
RHE
T
RHP
h
T0
T2
T1
T3
T4
ηe
* =WpQ1
= 1− T0
Th
Chambadal-Novikov efficiency:
Maximum normalised power:
ψe =
We
(αh +α0)T0
=( Th /T0 −1)2
4
Occurs at T1 /T2 = Th /T0 and α0 = αh
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Q4 = k Q1
k = discharge time, td
charge time, tc
Round-trip efficiency:
χ = COPp × ηe =
(k +1)θ − k(k +1)θ +1
where:
θ = Th /T0
eW.p W
.
RHP
T
RHE
h
T0
T2
T1
T3
T4
Q1 = αh(Th −T1)
Q2 = α0(T2 −T0)
Endoreversible analysis: efficiency for hot storage
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Q4 = k Q1
eW.p W
.
RHP
T
RHE
h
T0
T2
T1
T3
T4
Q2 = α0(T2 −T0)
Q1 = αh(Th −T1)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.0 0.5 1.0 1.5 2.0 2.5 3.0
-250 0 250 500
Hot storage
!!R
ound
-trip
effi
cien
cy, r
Temperature ratio, Ts / T0
Storage temperature, oC
Endoreversible analysis: efficiency for hot storage
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Q3 = k Q2
Q1 = α0(T0 −T1)
Q2 = αc (T2 −Tc )
.p
.We
WRHP
RHE
3
T4
Tc
T1
T2
T0
T
0
0.1
0.2
0.3
0.4
0.5
0.6
0.0 0.5 1.0 1.5 2.0 2.5 3.0
-250 0 250 500
Hot storageCold storage
Rou
nd-tr
ip e
ffici
ency
, r
Temperature ratio, Ts / T0
Storage temperature, oC
Endoreversible analysis: efficiency for cold storage
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0.0
0.2
0.4
0.6
0.00 0.05 0.10
-175
-125
-75
100
300500
Rou
nd-tr
ip e
ffici
ency
, r
Normalised power output, se
HotCold
Endoreversible analysis: efficiency vs. power density
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Tc= -150oC
0.0
0.2
0.4
0.6
0.00 0.05 0.10
-175
-125
-75
100
300500
Rou
nd-tr
ip e
ffici
ency
, r
Normalised power output, se
HotCold
Combined
Endoreversible analysis: combined hot & cold storage
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Exergetic storage density (kWh / m3)
0
50
100
150
200
250
-250 -125 0 125 250 375 500
liquid N2
CAES
hotwaterPHS
PTEShot
PTEScold
Exer
getic
den
sity
, kW
h / m
3
Storage temperature, oC
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Isentropic’s “SVS” (Scaled Validation Model of PHES)
Hot and cold “layered” thermal stores for a 120 kW system
HOT (500 oC)
COLD (–150 oC)
Efficiency-cost optimisation (packed-bed reservoirs)
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valves
86
88
90
92
94
96
98
100
0.75 1.00 1.25 1.50 1.75
Effic
ienc
y (%
)
Normalised cost per unit returned energy
R1: Hot (Argon)R2: Cold (Argon)
Isentropic’s layered store concept GA optimisation for different packed-bed thermal reservoirs (Josh McTigue, 2015)
Open symbols = layered stores
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Isentropic’s “SVS” : The Engine
Double-acting “reversible” reciprocating compressor / expander
HOT side
COLD side (below gallery)
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PTES is sensitive to all loss parameters (low “work ratio”)
50
60
70
80
90
100
0 5 10 15
Ther
mod
ynam
ic e
ffici
ency
, r
Pressure ratio, `
d = 0.99d = 0.95d = 0.90
50
60
70
80
90
100
0 25 50 75 100
Ther
mod
ynam
ic e
ffici
ency
, r
Pressure ratio, `
d = 0.99d = 0.95d = 0.90
Liquid PTES 2-stage A-CAES
χ = fn Pi , Ti , η j , εk , fl( )
heat exchange effectiveness
polytropic efficiencies pressure loss factors
Compression & Expansion Losses: Valve Losses
P-V diagram from an ‘off-the-shelf’ compressor
“Isentropic”’s cunning valve design
P-V diagram from “Isentropic”’s device
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Early prototype piston / valve arrangement for a heat pump
Compression & Expansion Losses: Thermodynamic Losses
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10ï2 10 0 10 2 10 410ï3
10ï2
10ï1
10 0
10 1
Loss
Pe
CFD Air rv=6.8
CFD Helium r v=6.8
CFD Helium r v=2.0
Exp. Helium r v=2.0
isothermal adiabatic
slow fast
Load-Integrated Energy Storage (LIES)
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Electricity in
Electricity out
Refrigeration and / or cooling
Low-grade heating
More LIES
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-200
0
200
400
600
-0.4 -0.2 0
1
2
3
4
Tem
pera
ture
, C
Specific Entropy, KJ/kgK
T-s Diagram
Charge Discharge
-200
0
200
400
600
-0.4 -0.2 0
1
2
3
4
Tem
pera
ture
, C
Specific Entropy, KJ/kgK
T-s Diagram
Charge Discharge
Optimised for work output Lower discharge pressure
qout < 50 oC
qout < 50 oC qout > 75 oC
The UK’s Energy Storage Inventory (data from DOE)
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0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
1963
1965
1974
1984
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Inst
alle
d ca
paci
ty, G
WPHS Mechanical Batteries
SUMMARY
q PTES has good potential for distributed storage
q High power density and efficiency go together for (hot + cold) storage
q Possible scope for load integration (cooling / heating)
q Low temperature PTES is probably best used for low-grade heat
q High compression and expansion efficiencies need to be demonstrated
q To reap the benefits of a whole-system approach it’s probably best to have a whole system
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