High Temperature Energy Storage in a Rock Bed

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High Temperature Energy Storage in a Rock Bed

Kurt Engelbrecht, Stefano Soprani, Loui Algren, Kenni Dinesen, Thomas Ulrich, Ole Alm, Eva Sass Lauritsen, Fabrizio Marongiu, Allan Schrøder Pedersen

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DTU Energy, Technical University of Denmark

Project Description (HT TES project)

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Source: SEAS-NVE

• Heat is stored at high temperature (600 ⁰C).

• The heat is used to produce high pressure steam to expand in a turbine.

• Funded by EUDP

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Project Challenges and Research Areas

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• Choose suitable rock material

• Design of the rock bed

• System testing

• Model rock bed operation, both thermal and economic aspects

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Brief summary of thermal rock storage

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• Low cost electricity is stored as heat in a rock bed then used to produce electricity or district heating when prices are high

• Due to the reduced efficiency associated with thermal conversion to electricity, the technology relies on relatively high electricity price fluctations

• The main advantages are low cost and easy scalability

• Storage period is a few days up to several weeks, depending on the insulation and thermal losses

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Rocks…the very basics

‘Monomineralic’ rocks (>90% one mineral)

‘Polymineralic’ rocks:

(several minerals)

Quartzite (Hardeberga, Sweden) Magnadense (Kiruna, Sweden) Dunite (Norway)

Ansite (Norway)

Granite (Bornholm)

Norite/Gabbro (Telnes, Norway) Diabas (Finland, Sweden)

Basalt (Germany/Austria) Hyperite (Norway)

Rock texture

Mineral 1

Mineral 2 Mineral 3

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Dunite

before after

After heating

1000um

olivine

Microscopic textur e

1000um

Before heating

olivine

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Rock selection for first experiments

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• We chose Swedish diabase as the first rock material

• Cheap and available day-to-day in Denmark

• Available in different sizes

• Able to withstand cycling to 600 C

• First rocks tested were sieved between 20 mm and 40 mm

• We are looking at different rock types and sizes for future experiments

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Experimental setup “shoebox”

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Heater

Fan Thermal

insulation

Hot end Cold end

Containment grids

20 October, 20 October, 2017 2017

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Experimental setup “shoebox”

9 20 October,

20 October, 2017 2017

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Experimental setup “shoebox”

10

Fan Hot-end

16 x temperature sensors To the chimney

(outside)

Heater (behind the ”shoebox”)

Cold end

Size = 1.5 m³ of rocks ~ 450 kWh_th ΔT=600C Max. charging rate = 25 kW

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Experimental result - charging

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Heater power 25 kW

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Experimental result - discharging

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Experiment status

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• Initial testing indicated that heat losses were a problem and more insulation has been added.

• Our first heater is broken and we are waiting on its replacement

• Next step is to fully test the 20-40 mm Swedish diabase

• Future tests will investigate the effects of varying the rock size

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Modelling efforts in the project

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• Inside the project we have both economic models of the Danish electricity market and the cost of the thermal storage and a numerical model of thermal interactions in the rock bed.

• A goal of the project is to couple the two models to give accurate performance predictions and a prediction for how a company might invest is such a storage based on realistic market conditions

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DTU Energy, Technical University of Denmark 15

15

EL-1

High temp.

air El

DK1

HT-TES Charger (heater+fan)

HRSG Steam Turbine

Steam

04-12-2017

Economic model: electricity storage

• Model considers both a scenario with a higher mix of renewables for 2035 and actual market

prices for Denmark in 2015.

• Prices of all necessary

components are inputs to the model

• Main output is how large an investment in the system is optimal

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Case 1:

electricity storage 2035 prices

04-12-2017 HT-TES WP4 modeling

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Unit CAPEX [DKK/M W]

OPEX[DKK/M W/y]

Yearly

investment Cost[MDKK]

Invested capacity

Charger 625,000 6250 2.9 MDKK 55.6 MW_el Discharg

er 4,580,000 180,000 2.8 MDKK 5.5 MW_el / 12 MW_th

Storage 2,620 0 0.2 MDKK 1000

MWh_th

Revenue 7.76 MDKK

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DTU Energy, Technical University of Denmark HT-TES WP4 modeling 04-12-2017 17

Unit CAPEX [DKK/MW ]

OPEX [DKK/M W/y]

Yearly

investment Cost[MDKK]

Invested capacity

Charger 625,000 6250 0.34 MDKK 6.5 MW_el Dischar

ger 5.5 MW_el /

12 MW_th

Storage 2,620 0 0.10 MDKK 540 MWh_th

Revenu

e 0.75 MDKK

Case 2:

electricity storage

DK1 2015 prices

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Governing Equations of a 1D Numerical Rock Bed Model

          

2 2

f f f f

f f f s c f r f f f c f

h

r disp c

N uR e,P r k T

m tc T T aAT T c T A T

x d t

e n th a lp y flo w h e a t tr a n s fe r to c a p a c ity o f e n tr a in e d flu id r e g e n e r a to r m a te r ia l

k A T x a x ia l d is p e r s io n

 

            

 

 





f

m t p x

v is c o u s d is s ip a tio n

 

 



^f ^f

  

^{f f} _scf _r _c

^{ } 1

_o _e_f_fc²2^r _rc

^{ } 1

^r

h

N u R e , P r k T M T u a A T T A H k A A

d t x t

a x i a l

m a g n e t i c w o r k e n e r g y s t o r e d h e a t t r a n s f e r f r o m f l u i d

c o n d u c t i o n

i n m a t r i x

  ^ ^   ^

    

  

Fluid:

Regenerator:

x

 

^,

oH x t



T

_f

(x,t)

T

_r

(x,t)

 

m t

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Coupling economic model to 1D model

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• Bed size

• Charge and discharge

characteristics

• Heater power

1D model inputs

• Rock type

• Bed geometry

• Air flow rate etc Run 1D model over an entire

year

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Some model constraints

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• Minimum temperature for steam productin is 530 C

• Charge inlet temperature is 600 C

• Maximum outlet temperature is 300 C

• We use the return temperature from the heat recovery steam generator as the inlet discharge temperature (100 C)

• Initial rock bed temperature is 20 C

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Full year rock bed operation for 2035

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• Economic model calls for a bed that is approximately 3,400 m3 in volume.

First we model a 15 x 15 x 15 m³ rock bed

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Full year rock bed operation for 2035

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• “Skinny” bed 10 x 10 x 33.75 m

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Predicted power supplied to power cycle

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Preliminary model conclusions

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• Sometimes the temperature in the bed is too low to produce steam, although the economic model expects a power production

– May need a minimum charge energy constraint in the economic model

• System optimization based on rock bed dimensions and rock size is necessary

• We have demonstrated modelling a full year of operation using a detailed 1D numerical model of the rock bed

– System optimization of such a rock storage will be performed in the near future

• Pressure drop can become a major issue for long beds or small rock sizes

• Reducing rock size from 20 mm to 16 mm gives approximately 2% more power production over the full year

• Reducing the length of the bed to 8.4 m while increasing cross sectional area gives a reduction in power production of 5.5% over the full year

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Conclusions

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• At DTU we have a functional 1.5 m³ rock bed storage that can operate at temperatures up to 600 C

– Capable of quickly testing different rock types and sizes and system configurations

• Economic modelling shows that for 2015 prices, the system needs to use an existing steam turbine to be economical

– Using a 2035 scenario with higher renewable mix it can make sense to invest in a new turbine dedicated to a rock storage unit

• We have demonstrated modelling a full year of operation using a detailed 1D numerical model of the rock bed

– System optimization of such a rock storage will be performed in the near future

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DTU Energy, Technical University of Denmark 26

THANK YOU FOR YOUR ATTENTION

20 October, 2017

High Temperature Energy Storage in a Rock Bed

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