Techno-Economic Analysis and Comparison of CSP with Hybrid

Techno-Economic Analysis and Comparison of

CSP with Hybrid PV-Battery Power Plants

Results from the THERMVOLT Study

Manfred Engelhard1, Stephan Hurler1, Adrian Weigand1, Stefano Giuliano2, Michael Puppe2, Heiko Schenk2, Tobias Hirsch2, Massimo

Moser3, Tobias Fichter3, Jürgen Kern3, Franz Trieb3, Dietmar Brakemeier4, Johannes Kretschmann4, Ursula Haller4, Roland Klingler4,

Christian Breyer5 and Svetlana Afanasyeva5

1 M+W Group GmbH

2 German Aerospace Center, Institute of Solar Research 3 German Aerospace Center, Institute of Engineering Thermodynamic 4 Fichtner GmbH 5 Lappeenranta University of Technology

giz Webinar May 16th 2017

“Dispatchability on RE:

Comparing CSP with PV Battery”

© M+W Group 2 2016_10_11 THERMVOLT_Results - SolarPACES M. Engelhard.pptx / 11.10.2016

Semiconductor Facility Pharmaceutical Campus

M+W Group - Global Leading Engineering and Construction Company

High Tech Research Center

6,000+ dedicated

employees

1912 established

in Germany

€ 3.0 bn order intake

and sales

Leading player with

global reach

Anderes

Bild?

Mehr High-

tech

Engineering and Construction of Technology

Facilities

High Tech Research Center Energy Plant


Motivation and Goals for THERMVOLT Study: Dispatchable Solar Power Photovoltaic power plants (PV) offer low generation cost but also a volatile power

generation and cannot guarantee alone supply security.

Concentrating solar power plants (CSP) can offer firm capacity by integration of

thermal energy storages and/ or by using a solar fossil hybrid operation strategy.

In principle hybrid PV-Battery-GT (PVBGT) power plants have the same capability as

CSP in terms of flexibility of power generation depending on demand. They use a

battery and a fossil back-up (e.g. GT) and are operated as an interconnected system

or as a virtual power plant.

The THERMVOLT study offers a cost comparison of a variety of PV-based and CSP-

based power plant concepts and their combinations under the same boundary

conditions – they must be able to follow a given load profile and need to decrease

greenhouse gas emissions (CO2eq) at lowest cost.


THERMVOLT – Projekt Data and Partners

Projekt data

Project coordiantion: German Aerospace Centre (DLR)

Project start: 11/2014

Project duration: 20 Month

Budget total: : ~0,7 Mio. Euro

Co-funded by German Federal Ministry for Economic Affairs

and Energy, BMWi (contract no. 0325760).

Project partner industry

M+W Germany GmbH

Fichtner GmbH

Research

German Aerospace Center

Institute of Solar Research

Institute of Engineering Thermodynamic

Lappeenranta University of Technology (subcontracted by DLR)

Gefördert durch:

aufgrund eines Beschlusses

des deutschen Bundestages


THERMVOLT – Basic Concepts

CSP

Solar thermal power plants

(incl. thermal storage &

fossil co-firing)

PV

PV-Battery power plants

(inkl. battery & fossil co-

firing)

CSP-PV

Combined CSP-PV power

plants

Converter

PV field

Battery storage

Li-Ion+ -

Control logic

Gas turbine

G

DC AC

Solar tower

Receiver Hot storage

G

Steam generator

Condenser

Heliostat field

Steam turbine

Cold storage

BurnerSolar tower

Receiver Hot storage

G

Steam generator

Condenser

Heliostat field

Steam turbine

Cold storage

Burner

Converter

PV field

Fix-mounted

Control logic

DC AC

Power OutputBattery storage

Li-Ion+ -


THERMVOLT – Common Boundary Conditions

Location: Morocco, Saudi Arabia

Meteorological data

Plant size: 100 MWe

Storage capacity: optimised

Economic modell (LCOE)

Investment cost (CAPEX)

Operating cost (OPEX)

El. generation defined

by load profiles:

1. Baseload

2. Typical day

3. Solar only

Solar field design: optimised

RE-share and permitted CO2 emissions

Fuel cost

2015, 2020, 2030

Validation of annual yield models


Sites

2 sites:

Morocco

Kingdom Saudi

Arabia

Location overview

Location Ouarzazate, Morocco Taiba, KSA

Latitude °N 31.1 24.3

Altitude m 1150 24.33

Annual DNI kWh/m² 2373 2408

Annual GHI kWh/m² 2118 2338

Ambient temperature @DP °C 30 47

Fossil fuel Diesel Natural gas


Load Profiles: typical Day

Typical day (mid-load power plant)

Morocco: strong evening peak, no operation during night hours

KSA: moderate afternoon/evening peak, reduced operation during night

hours


Methodology

Reference systems for all technologies

are modeled in commercial or

validated simulation tools by the

partners and used as reference.

Those reference systems were used for

validation of a common tool for the

yield analysis (INSEL) applied for this

study.

During the yield calculation on an

annual basis the sizes of solar fields

and different storage capacities are

optimized for each variant.

To predict the cost development of the

technologies, a model based on

learning rates is applied.

Finally an economic model is used to

calculate LCOE of all variants, including

effects like degradation and different

cost scenarios (sensitivities).

1. Validation of reference

systems

2. Modelling and yield

analysis of CSP, PVBGT

and CSP-PV systems

INSEL

1. Results for simplified

modelling approach

2. Detailled annual yield

analysis

Reference tools

CSP: DLR with Ebsilon & custom model; Validation

by Fichtner with SolPro

PV: M+W and LUT with PV-Syst

Battery storage: M+W and LUT with custom models

Fossile power plants: Fichtner with KPro


Review of Reports as Basis for Scenarios


Comparison of Thermvolt Fingings* to Saudi Aramco**

Key insights:

• PV fixed tilted very similar

• Battery very similar, but Aramco expects as slightly faster cost decline

• Aramco is more conservative on CSP as we, however the TES assumptions are not disclosed and

could easily explain the difference

* base case

** Saudi Aramco presented own

expectations at MENASol 2016,

Dubai, May 25


Cost Assumptions [1]

Experience curve approach has been chosen for capex projections

Literature review provided the basis for the THERMVOLT scenario assumptions

Three scenarios have been developed and capex numbers for all relevant components have been

derived on the assumed future capacities, market growth and learning rates of CSP, PV and

batteries (and major CSP components)

[1] Breyer C. et al (2016). Assessment of Mid-Term Growth Assumptions and Learning Rates for comparative Studies of

CSP and Hybrid PV-Battery Power Plants, SolarPACES Conference 2016 (to be published)

Plants Learning

Rate

Range

Doublings

2015-2020

Doublings

2020-2030

Capex 2015

[€/kW; €/kWh]

Capex 2020

[€/kW; €/kWh]

Capex 2030

[€/kW; €/kWh]

Cum.

Capacity

2020 [GWe]

Cum.

Capacity

2030 [GWe]

base case

CSP, Tower 10-12% 1.62 2.37 5431 3645 – 3722 - 3798 2826 – 2939 - 3052 15.4 79.5

CSP, Trough 10-12% 1.62 2.37 4618 4222 – 4318 - 4415 3285 – 3425 – 3565

PV plant 15-20% 1.35 1.71 1250 924 - 964 - 1003 631 – 693 – 760 598 1958

Battery Plant 15-20% 1.61 3.22 200;400 147; 294 +/- 5% 80;159 +/- 8% CAGR 25% CAGR 25%

low growth

CSP, Tower 10-12% 0.85 1.64 - 4031 – 4081 - 4131 3298 – 3393 – 3489 9.0 28

CSP, Trough 10-12% 0.85 1.64 - 4624 – 4692 - 4760 3836 – 3954 – 4073

PV plant 15-20% 0.76 0.87 - 1054 – 1079 - 1104 867 - 913 – 958 397 728

Battery Plant 15-20% 0.69 1.38 - 175; 350+/- 5% 135;269 +/- 8% CAGR 10% CAGR 10%

high growth

CSP, Tower 10-12% 2.12 2.59 - 3435 – 3523 - 3612 2643 – 2760 – 2876 21.8 131

CSP, Trough 10-12% 2.12 2.59 - 3990 – 4101 - 4211 3065 – 3211 - 3357

PV plant 15-20% 1.85 2.14 - 827 – 876 - 925 513 – 583 – 653 844 3725

Battery Plant 15-20% 2.43 4.85 - 126; 251+/- 5% 50;101 +/- 8% CAGR 40% CAGR 40%

[Overview of learning rates and growth expectations [1]. CSP: for a 100 MW power plant, SM 2.4 and TES of 10 hours. PV: single axis tracking.

Battery: energy to power ratio variable. The capex are given in a range of minimum – average – maximum values based on the learning rate range.

Cum. Capacity 2015 PV: 230 GWe Cum. Capacity 2015 CSP: 5 GWe


Results – Morocco

Cost vs. CO2 emissions in 2015 and 2030 for Baseload and Typical Day load curve in Morocco.

The solar only data point („_so“) does not fulfill the load curve and serves as a reference point.


Morocco – 2015 Typical Day



Morocco – 2030 Typical Day



Results – Saudi Arabia

Cost vs. CO2 emissions in 2015 and 2030 for Baseload and Typical Day load curve in Saudi Arabia

The solar only data point („_so“) does not fulfill the load curve and serves as a reference point.

.


Saudi Arabia – 2015 Typical Day

Cost vs. CO2 emissions in 2015 and 2030 for Baseload and Typical Day load curve in Saudi Arabia.


Saudi Arabia – 2030 Typical Day

Cost vs. CO2 emissions in 2015 and 2030 for Baseload and Typical Day load curve in Saudi Arabia.


Sensitivity– Moroco 2030

Sensitivitäty:

CSP: low, base and high cost

PV and Batteriy: low, base and high cost, fossil

base

CSP-PV: low, base and high cost, fossil base

Conclusion:

Variance for PV-based concept high (high

potential/ risk)

For CSP based concepts lower variance


Conclusions

All 3 base concepts (CSP, Hybrid PV-Battery and their combinations) can contribute

to the supply certainty to the grid depending on the demand curve.

With the used boundary conditions the analysis showed that a combination of CSP

and PV plant is in many cases the most cost effective solution.

(direct PV power delivery during the day, CSP delivers preferred at evening/ night)

While in 2015 the PV-Battery systems are more expensive due to high storage

cost, they can become competitive in 2030. This is strongly depending on the load

conditions and the required need to decrease greenhouse gas emissions (CO2eq).

For load profiles requiring load at night (e.g. KSA) in 2030 the LCOE for all concepts

is nearly the same. For load profiles requiring most of the load during the day (e.g.

Morocco) hybrid PV-Battery power plants can somewhat lower the LCOE.

For all technologies in 2030 the lowest LCOE are achieved with configurations

with very low specific CO2 emissions!

It is important to keep in mind:

the boundary conditions of the analysis – a fixed load curve that has to be

fulfilled at any time.

The assumed market growth of the technologies: CSP and Battery will only

reduce their cost if the assumed capacity is installed by 2030.


Quo vadis solar power?

Thank you for your attention!

The authors would like to thank the

German Federal Ministry for Economic

Affairs and Energy for the financial support

of the project THERMVOLT (contract no.

0325760).


Contact

Thank You!

Manfred Engelhard

Technology Manager Energy

M+W Central Europe GmbH

[email protected]

Documents

Techno-Economic Analysis and Comparison of CSP with Hybrid