Evaluating the value of concentrated solar power in ... SolarPACES_Pitz-Paal.pdf · Evaluating the...

Evaluating the value of concentrated solar power in electricity systems with fluctuating energy sources

Robert Pitz-Paal DLR

Benedikt Lunz, Philipp Stöcker, Dirk Uwe Sauer RWTH Aachen University

> Value of CSP > Robert Pitz-Paal • SolarPACES 2015 > 14.09.2015 DLR.de • Chart 1

• What is residual load and how big will it be in Germany 2050?

• What technology can cover the residual load?

• How to find the lowest cost technology mix?

• Can import of CSP electricity contribute to this mix?

Outline


Principle of electric power supply: Supply and Demand need to match

-150

-100

-50

0

50

100

150

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2424 2448 2472 2496 2520 2544 2568Pow

er i

n GW

Hour of Year

Laufwasser Wind onshore Wind offshore PV Last ResiduallastResidual Load PV: 151 GW, Wind onshore: 82 GW, Wind offshore: 20 GW, Load deman: 602 TWh, FRES share: 83 %

Figu

re: W

uppe

rtal

Inst

itut

Scenario for Germany 2050: 83% variable power in total supply capacity


Load

Energy Scenarios for Germany 2050: The future may look very different….


0

200

400

600

800

S1 S2 S3 S7

528 TWh /57%FEE

635 TWh /45%FEE

458 TWh /67%FEE

749 TWh /68%FEE

TWh

Residual loaddemandPV

Wind offshore

Wind onshore

Load following Biogas power plants

Concentrated Solar Power with storage (+.hybridisation)

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ygro

up /

Wik

imed

ia C

omm

ons

Flexible fossil fuel power plant

© Im

agin

is / F

otol

ia

Flexible generation capacity (net - producers)

Load-following Combined heat and power

© V

isual

Con

cept

s / F

otol

ia

Geothermal power plants with stoarge

© v

isdia

/ Fo

tolia

How to cover the residual load (1/2):


Grid extension

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lia

Demand Side Management (industry)

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ndre

i Mer

kulo

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Power-to-Gas (Chemicals)

Hann

o Bö

ck /

http

s://

hboe

ck.d

e/

„smart grid“

© G

ert S

kriv

er /

Wik

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ons

Curtailment of variable supply

© v

ege

/ Fo

tolia

Dual-use storage

© P

etai

r / F

otol

ia

© V

ladi

slav

Koch

elae

vs /

Fot

olia

Electric storage

Flexibility technologies to shift the supply in time or space

Power-to-Heat

© c

oppi

right

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ia

Demand Side Management (domestic)

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How to cover the residual load (2/2):

• Characterization of available technologies • Technical: efficiency, ramp up time, etc. • Economical: investment, O&M costs, fuel costs etc. • Basic dataset for important technologies is already available

• Determination of residual load to be covered

• Fluctuating renewable infeed minus load • Hourly resolution for one year

• Cost-minimal selection of technologies (software tool)

• Result: power system which is able to cover the residual load at all times • Selection based on full costs • Installed power, generated electricity and other data of used technologies

Basic Idea


Simplified methodology: how optimizing the technology mix covering the residual load?

Cut residual load in individual load bands

Characterize the different load bands

Identify for each load band the technology

that covers the load at lowest cost


0 1000 2000 3000 4000 5000 6000 7000 8000

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-50

0

50

Stunden

Leis

tung

in G

W

Residual load – for one year in hourly resolution

FRES-share 76%


Time in hours

Pow

er in

GW

0 1000 2000 3000 4000 5000 6000 7000 8000

-100

-50

0

50

Zeit (h)

Res

idua

llast

(GW

)Positive residual load is cut into load bands


Time in hours

Pow

er in

GW

FRES-share 76%

1770 1780 1790 1800 1810 1820 1830

Residuallast FhISE 2013 Referenzszenario in Bändern

Zeit (h)0-5 GW

5-10 GW 10-15 GW

15-20 GW

20-25 GW 25-30 GW 30-35 GW 35-40 GW

40-45 GW 45-50 GW

50-55 GW 55-60 GW

60-65 GW 65-70 GW 70-75 GW

A positive load in the top band indicates a positive load in all lower bands: i.e. no system designed to cover the load in a lower band can provide additional energy to the upper band


Time in hours

Example of the annual load curve of the lowest band

Band 1, 6596 full load hours


Example of the annual load curve of the highest band


Band 50, 346 full load hours

Technology (Cost in Mio. €/GW)

Lignite CCS Gas Turbine

Combined Cycle

Full load hours in load band

5970 5970 5970

Annuity 221,0 32,7 61,0 Operation & Maintenance 89,1 13,1 21,0 Fuel cost 21,3 430,0 311,0 Start-up cost 6,0 5,3 18,6 CO2-Cost 35,5 199,0 144,0 Total annual cost 373,0 680,0 556,0 Specific generation cost in €ct/kWh

6,2 11,4 9,3

WKA & PV 76%, Band 1 (1 GW)


Example: Technologies compete in a load band


Lignite CCS Gas Turbine

Combined Cycle

Full load hours in Load band

2520 2520 2520

Annuity 221,0 32,7 61,0 Operation & Maintenance 89,1 13,1 21,0 Fuel cost 9,0 181,0 131,0 Start-up cost 6,3 5,4 20,9 CO2-Cost 15,0 83,9 60,7 Total annual cost 340,0 316,0 295,0 Specific generation cost in €ct/kWh

13,5 12,5 11,7

WKA & PV 76%, Band 36 (1 GW)


Example: Technology competition in a different load band


Hydrogen Storage

Methan-Storage

Gas- Turbine

Lignite CCS

Full load hours (Discharge)

3110 3110 3110 3110

Charging Power 4,5 GW 8,8 GW - - Capacity 796 GWhth 964 GWhth - -

Total annual cost 323 Mio. € 1061 Mio. € 338 Mio. € 345 Mio. € Specific storage/ generation cost

10,4 €ct/kWh

34,1 €ct/kWh

10,9 €ct/kWh

11,1 €ct/kWh

FRES-share 76%, Band 36 (1 GW)


Example: Storage technology use negative residual to be charged

• Certain E2P necessary for delivering power to a load band • In comparison to gas turbines battery storage is not economic for supplying

power to a load band, if E2P > 2,5h is necessary (1GW and > 2,5 GWh) • Battery storage rather used for optimizing operation of conventional power

plants or for supplying peak loads.

Batteries vs. power plants


- €

20 €

40 €

60 €

80 €

100 €

1 2 3 4 5 6

Annu

al fi

xed

cost

s pe

r kW

Energy to power ratio (E2P)

Gas turbine

Batterystorage

Gas turbine - 375 €/kW - Lifetime >30a

Battery storage - 45 €/kW plus 150 €/kWh - Lifetime <30a

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1,000

0 1000 2000 3000 4000 5000 6000 7000 8000

€/kWh

Full load hours

Merit-Order cost for best option

Datenquelle: Prof. Pitz-Paal

The electricity cost of the „winning technologies“ as a function of the full load hours


Is CSP import an economic option for Germany to cover a part of the residual load?


CSP + HVDC cost assumptions for 2050


CSP hybrid HVDC

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2050 (min) 2050 (max)System parameters Annual System efficiency sol- > electr 19% 22%Annual system effciency fossil -> electr. 45% 50%CO2 Emission factor (natural gas) [t/MWhth 0,247 0,247 ( ) ( )specific CSP costSolar field [€/m²] 55 80Themal storage 11 16Power block 590 750Engineering, Development, EPC, Contingen 25% 29%Annual O&M % of invest 2% 2%specific fuel cost[€/MWhth] 33,1 33,1CO2 penalty [€/t CO2] 76,0 76,0 Financial parameterslife time 30 30interest rate 8% 8%

2050 (min) 2050 (max)Cost HVDCEarth cable €/kM-MW 700 720Sea cable €/kM-MW 825 850Overhead line €/kM-MW 120 125Cost per DC/AC Station €/MW 90.000 95.000Losses earth cable %/1000kM 3,50% 3,50%Losses sea cable %/1000kM 2,70% 2,70%Losses overhead cable %/1000kM 4,5% 4,5%Losses AC/DC conversion 0,7% 0,7%Annual O&M % of Invest 2% 2%Lifetime HVDC 40 40interest rate 8% 8%

CSP plant optimization for each load-band


converter (thermal electricity)

electricity

ηstorage SOCmin

thermal storage

time series solar

irradiation

primary renewable energy source

co-firing Fuel cost

CO2 emission coefficient

fuel CO2

thermal energy

€

maxshare

ηthel

• Reference case is average between 2050 min and max • Progress case is equal to 2050 max

Generation cost to cover different load bands: CSP Generation + HVDC + Fuel + CO2 Penalty


0,000

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1,000

0 1000 2000 3000 4000 5000 6000 7000 8000

€/kWh

Full load hours

Cost Curve for CSP Import (average)

CSP Import is cheapest option

Datenquelle: Prof. Pitz-Paal


The electricity cost of the „winning technologies“ compared to the CSP cost curve

1. Example Results for 90% CO2 Reduction Target Fraction of Wind an PV 45%; 100% = 234 GW


0%10%20%30%40%50%60%70%80%90%

100%

without CSP with CSPreference

with CSPprogress

S2 - 45 % FRES

Shar

e of

inst

alle

d po

wer

DSM industry

DSM household

Hydrogen storage

Industrial CHP

Wood power station

Gas turbines - biogas

Gas-steam - biogas

Gas turbines - natural gas

Gas-steam - natural gas

Geothermal

CSP

Wind offshore

Wind onshore

PV

9,1 €ct/kWh 7,6 €ct/kWh 7,0 €ct/kWh

26 GW 31 GW

1. Example Results for 90% CO2 Reduction Target Fraction of Wind an PV 45% 100% = 635 TWh


0%

31% 36%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


with CSP progress

S2 - 45 % FRES

Shar

e of

ene

rgy

DSM industry

DSM household

Hydrogen storage

Industrial CHP

Wood power station

Gas turbines - biogas

Gas-steam - biogas

Gas turbines - natural gas

Gas-steam - natural gas

Geothermal

CSP

Wind offshore

Wind onshore

PV

Mix of energy cost in CSP reference scenario


2. Example: Results for 90% CO2 Target Fraction of Wind an PV 67%; 100% = 213 GW


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


with CSPprogress

S3 - 67 % FRES

Shar

e of

inst

alle

d po

wer

DSM industryDSM householdHydrogen storageIndustrial CHPWood power stationGas turbines - biogasGas-steam - biogasGas turbines - natural gasGas-steam - natural gasGeothermalCSPWind offshoreWind onshorePV

7,9 €ct/kWh 7,8 €ct/kWh 7,6 €ct/kWh

4 GW 9 GW

1. Example: Results for 90% CO2 Target Fraction of Wind an PV 67%: 100% = 458 TWh


0% 5% 12%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


with CSPprogress

S3 - 67 % FRES

Shar

e of

ene

rgy

DSM industryDSM householdHydrogen storageIndustrial CHPWood power stationGas turbines - biogasGas-steam - biogasGas turbines - natural gasGas-steam - natural gasGeothermalCSPWind offshoreWind onshorePV

CSP import lowers electricity cost to cover residual load


6

7

8

9

10

40% 60% 80% 100%

over

all e

lect

rici

ty c

osts

in €

ct/k

Wh

Share wind and PV

without CSP

with CSP reference

with CSP progress

CSP import lowers cost

Up to 12%

• In energy systems with high shares of fluctuating renewables a mix of technology options is required to balance the residual load

• A simplified methodology is presented, that can cost-optimize the technology mix to cover the residual load for different energy scenarios

• Import of hybrid CSP by HVDC is considered as one reasonable option in Germany in this context to achieve a 90% CO2 reduction goal until 2050

• Import of CSP allows for up to 12,5% lower overall electricity cost compared to reference case and would require less PV and wind power in Germany

• CSP is required for mid-load power and replaces mainly biomass power plants

• This analysis can be considered as a first step. Issues that are not considered are grid limitations, role of existing depreciated facilities, integration of European capacity and other aspects.

Summary


• Which role can CSP play in national power systems?

• What are the key factors which influence the use of CSP?

• How are CSP systems dimensioned in a power system context? • Size of storage, collector field, co-firing unit, turbine

• What is the mix of generation, storage and other flexibility technologies?

• What are the electricity generation costs?

If you are an expert and have access to country specific data, you are invited to join.

New SolarPACES Grid Integration Working Group under preparation using this Methodology


Date post:	06-Jun-2020
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