Wir schaffen Wissen – heute für morgen

(1)

Wir schaffen Wissen – heute für morgen 6^th Workshop of SAEE Student Chapter, ETH, 17^th Oct 2014

Development of the CROSSTEM model – A tool for analyzing uncertainty in the evolution of the Swiss electricity system Rajesh Mathew Pattupara

(2)

• Introduction – Background of Swiss Electric system

• CROSSTEM Model

• Motivation – European nuclear phase-out and its consequences

• Scenarios & Key Assumptions

• Preliminary results

• Conclusions

• Model limitations, issues and challenges

Outline

22.10.2014

PSI, Seite 2

(3)

Introduction

• Electricity accounts for one quarter of Swiss energy demand

• Large differences in seasonal output, seasonal demand.

• Creates seasonal dependence on electricity import.

26% 32%

6% 36%

2.55%

2.13%

Fossil fuels Wind

Solar PV Biogas

Waste Electricity generation mix 2012¹

(4)

• Nuclear phase out – No replacement of existing Nuclear power plants at the end of their 50 year lifetime. Last power plant off grid by 2034.

• Ambitious carbon reduction targets

• Uncertainty in electricity demand – The Swiss Energy Strategy 2050 defines possible demand pathways

• Business as Usual (WWB)

• Political Measures (POM)

• New Energy Policy (NEP)

• Uncertainty regarding future supply options – A combination of gas based generation, renewables and electricity imports are mentioned in SES 2050.

Future of Electricity system

22.10.2014

PSI, Seite 4

(5)

Swiss Energy Strategy 2050 – Demand projections

(6)

• Cost implications of renewable / low carbon policy

• Revenue from trade

• CO2 emission targets

• Expansion of Gas plants

• Balancing supply and demand

• Intermittent nature of renewables

• Electricity imports Developments in Europe

• Integration of intermittent Renewables

• Nuclear phase-out?

• CO₂ emission targets

• Gas imports

Future of Electricity sector – Tradeoffs

22.10.2014

PSI, Seite 6

Electricity Supply Options

Gas Renewables

Import Supply

Security Cost of

Supply

Climate change System

balancing

(7)

• CROSs border Swiss TIMES Electricity Model

• Extension of the STEM-E model to include the four neighbouring countries

• Time horizon: 2010 – 2070

• An hourly timeslice (288 timeslices)

• Detailed reference electricity system with resource supply, renewable potentials and demands for 5 countries

• Calibrated for electricity demand and supply data between 2000-2010

• Endogenous electricity import / export based on costs and technical characteristics

2 0 1 0

20 11 - 20 12

20 13 - 20 17

20 33 - 20 37

2068-2073 Milesone year 2070

CROSSTEM Model

(8)

TIMES – The Integrated MARKAL / EFOM System

• Technology rich, Perfect foresight, cost optimization framework

• Used to explore a range of parametric sensitivities under a “what-if”

framework via exploratory scenario analysis.

• Integrated modelling of the entire energy system

• Prospective analysis on a long term horizon (20-50-100 yrs)

• Allows for representation of high level of temporal detail – load curves

• Enhanced Storage algorithm – modelling of pumped storage systems

• Optimal technology choice – based on costs, environmental criteria and other constraints.

MARKAL – MARKet ALlocation

EFOM – Energy Flow Optimization Model

TIMES modelling framework

22.10.2014

PSI, Seite 8

(9)

Motivation – European nuclear phase-out

(10)

European Nuclear phase-out - Background

22.10.2014

PSI, Seite 10

• Low carbon pathway for electricity – EU Roadmap 2050

• “Nuclear Renaissance” – Switzerland and France to continue with its nuclear program. Italy to have 25% of net generation from nuclear by 2030. Germany to extend life times of existing plans³.

• Fukushima Accident – Socio-political consequences

• Nuclear phase-out

• Germany by 2022

• Switzerland by 2034

• Italy to continue with its nuclear moratorium

• France to reduce share from 75% to 50% by 2025 (?)

. 3. http://www.world-nuclear.org

(11)

European Nuclear phase-out - Background

• Alternative supply options – Germany substituting nuclear power with coal based generation → 43% (2010) to 52%(2013)

• Green house gas (GHG) reductions – Complete de-carbonization of power sector by 2050

.

Alternative low carbon sources of electricity

• Technical, Economical and Social challenges and uncertainties

(12)

2 basic scenarios and 3 CCS scenario variants selected for Analysis

• Reference Scenario (REF) – Nuclear policies of 5 countries

implemented. No CO₂ emission targets. Nuclear phase-out in CH by 2034, DE by 2022. French nuclear fleet can be replaced.

• CO2 reduction scenario (CO2-Base) – REF scenario with a cap on the total CO₂ emission from electricity generation is applied across all

regions. Level of decarbonisation to reach 60% of 1990 levels by 2030, 95% by 2050.

2. EU Roadmap 2050 - http://ec.europa.eu/energy/energy2020/roadmap/doc/com_2011_8852_en.pdf

Scenarios

22.10.2014

PSI, Seite 12

(13)

CCS Scenario variants

• High CCS scenario (CO2-CCS-H) – Upper variant of CCS potentials.

• Low CCS scenario (CO2-CCS-L) – Lower variant of CCS potentials.

• No CCS scenario (CO2-NoCCS) – No investment in CCS technology.

Free trade allowed in this scenario.

(14)

Input Assumptions

• Electricity Demand – EU Trends to 2050 (Reference scenario), BAU demands for CH (SES 2050)

• Trade with “fringe regions” – Historical limits applied

• CO2 price – European ETS prices implemented (SES 2050, Bfe)

• Fuel Prices – International fuel prices from WEO 2010.

Methodological Assumptions

• Copper Plate regions – No transmission and distribution infrastructure within each country. Interconnectors between regions, with no trade loss.

• Endogenous trade limits – Based on historical trends. Net importers cannot become net exporters and vice versa. Not applied to NoCCS.

.

Key assumptions

22.10.2014

PSI, Seite 14

(15)

Results

(16)

-1000 0 1000 2000 3000 4000 5000 6000 7000

2010 2050 2050 2050 2050 2050

Ref CO2-Base CO2-CCS-H CO2-CCS-L CO2-NoCCS*

PJ

Net Import Wood

Waste & Biogas Wind

Solar

Geothermal Oil

Gas-CCS Gas (Flex) Gas (CHP) Gas (Base) Coal-CCS Coal Nuclear Hydro (P) Hydro (D) Hydro (R) Pumps

Total Demand

Electricity generation mix – 5 countries aggregated

Aggregated Results

22.10.2014

PSI, Seite 16

(17)

50 100 150 200 250 300

PJ

Net Import Wood

Waste & Biogas Wind

Solar

Geothermal Oil

Gas-CCS Gas (Flex) Gas (CHP) Gas (Base) Coal-CCS Coal Nuclear Hydro (P) Hydro (D)

Country wise Results

Electricity generation mix - Switzerland

(18)

-500 0 500 1000 1500 2000 2500 3000

2010 2050 2050 2050 2050 2050

Ref CO2-Base CO2-CCS-H CO2-CCS-L CO2-NoCCS

PJ

Net Import Wood

Waste & Biogas Wind

Solar

Geothermal Oil

Total Demand

Electricity generation mix - France

Country wise Results

22.10.2014

PSI, Seite 18

(19)

500 1000 1500 2000 2500 3000

PJ

Net Import Wood

Waste & Biogas Wind

Solar

Geothermal Oil

Country wise Results

Electricity generation mix - Germany

(20)

-200 0 200 400 600 800 1000 1200 1400

2010 2050 2050 2050 2050 2050

Ref CO2-Base CO2-CCS-H CO2-CCS-L CO2-NoCCS

PJ

Net Import Wood

Waste & Biogas Wind

Solar

Geothermal Oil

Total Demand

Country wise Results

22.10.2014

PSI, Seite 20

Electricity generation mix - Italy

(21)

50 100 150 200 250 300

PJ

Net Import Wood

Waste & Biogas Wind

Solar

Geothermal Oil

Country wise Results

Electricity generation mix - Austria

(22)

Load Curves

22.10.2014

PSI, Seite 22

(23)

Load Curve – Winter Weekday 2050 (CO2-CCS-L)

(24)

Load Curve – Summer Weekday 2050 (CO2-CCS-L)

22.10.2014

PSI, Seite 24

(25)

0 5 10 15 20 25 30

Mt CO2

Switzerland Austria Italy France Germany

CO₂ emissions – Regional disaggregation

CO2 emissions

(26)

• Model of the electricity system of Switzerland and its neighbouring countries over a long term horizon combined with dispatch aspect achieved.

• Effects of surrounding country developments on the Swiss electricity system have been demonstrated.

• Possibilities for alternative low carbon electricity generation pathways for the five countries has been explored.

• Sensitivity of various CCS potentials analysed

• Decarbonisation of the power sector is plausible, but significant investments necessary in both renewable technologies as well as CCS.

Conclusions

22.10.2014

PSI, Seite 26

(27)

22. Oktober 2014 PSI,

Limitations & Uncertainties

• CROSSTEM is not a pure dispatch model.

• Modelling of representative days – Overall simplifications

• T&D infrastructure not explicitly modelled.

• CO2 transport not modelled

• Trade with fringe regions

• Model assumes perfect information, perfect foresight, well functioning markets and economically rational decisions – Optimal solution for 5 countries together, not for each country

Model Limitations

22. Oktober 2014

PSI, Seite 27

(28)

22. Oktober 2014 PSI, 22. Oktober 2014

PSI, Seite 28

Thank you for your attention !!!

(29)

Energy Economics Group

Laboratory for Energy Systems Analysis

General Energy Research department & Nuclear Energy and Safety Research Department