Wir schaffen Wissen – heute für morgen

International Energy Workshop, Stanford

6 July 2011

Cost of ad-hoc nuclear policy uncertainties in the

evolution of the Swiss electricity system

Ramachandran Kannan and Hal Turton

Energy Economics Group, Laboratory for Energy Systems Analysis

2

Outline

�Overview of Swiss electricity systems

�Swiss TIMES Electricity Model• Model features

• Input data and key assumptions

� Scenario definitions

� Results and discussions

� Conclusions

3

Final energy demand in 2009 (877 PJ)

Gas12%

Oil (Heating)22%

Oil (Transport)33%

Waste1%

District heat2%

Wood4%

Coal1%

Renewable1%

Electricity24%

Final energy demand in 2009 (877 PJ)

Industry19%

Service16%

Transport35%

Agriculture1% Residential

29%

Overview of Swiss energy system

Energy Economy (2009)

� Energy expenditure: CHF 27.1 Billion (5.1% of GDP)

� Energy import: CHF 8.7 Billion (4% of import expenditure)

� Energy import dependency: 80%

Electricity demand in 2009 (207 PJ)

Industry32%

Residential31%

Agriculture2%

Transport8%

Service27%

4

Swiss electricity system

Electricity generation mix (2009)

Gas23.76%

Solar PV1.04%

Oil2.81%

Waste61.81%

Wood4%

Landfill gas6%

Wind1%

Others5%

Nuclear39%

Hydro-River24%

Hydro-Dam32%

�An annual average growth of 1.3% over the past

ten years.

� Self sufficiency in annual electricity generation,

but still dependent on imported electricity for

seasonal demand.

� Power sector is nearly decarbonised.

� Electricity trading is important in terms of power

system balance and revenue (CHF 1.5 Billion in

2009).

5

Swiss electricity system

Electricity load curves (2008)

Seasonal: Weekdays

3

4

5

6

7

8

0 6 12 18

GW

WIN_WK SPR_WK

SUM_WK FAL_WK

Seasonal: Saturdays

3

4

5

6

7

8

0 6 12 18

GW

WIN_SA SPR_SA

SUM_SA FAL_SA

Seasonal: Sundays

3

4

5

6

7

8

0 6 12 18

GW

WIN_SU SPR_SU

SUM_SU FAL_SU

6

Overview of Swiss energy system

2010 energy policy targets: status as of 2009

� Fossil fuel reduction target of 10% from 2000 level: -1.3% ����

� Carbon reduction targets of 10% from 1990 level: -2.7% ����

� Cap the growth in electricity demand to < 5% from 2000 level: +14.4% (2010) ����

� Renewable electricity production of 1% from 2000 level (0.5 TWh): +0.46 TWh ☺☺☺☺

� Renewable heat production of 3% from 2000 level (3 TWh): +3.37 TWh ☺☺☺☺

Quelle: EnergieSchweiz, 2010

7

Swiss electricity system

Challenges and uncertainties

� Retirement of the exiting nuclear reactors and filling the supply gap: The Swiss Federal Nuclear Safety Inspectorate gave a positive assessment on construction of new nuclear power plants (Nov. 2010). After the Fukushima nuclear disaster, the Swiss Federal council has suspended plausible new nuclear option (May 2011).

� Ambitious carbon reduction targets: 60-80% by 2050.

� Large seasonal and diurnal variation in demand.

� Renewable electricity – Limited resources and high variability in availability.

� Uncertainties in future growth of electricity demand.

� Imported electricity - Security and availability concerns in light of climate policy in cross-bordering countries.

� Role of long term electricity trading - Uncertainty in development of electricity market in neighbouring countries under a low carbon economy.

8

- 2,000 4,000 6,000 8,000 10,000 12,000 14,000

CHF/kW

Hydro River - RfbHydro Dam - Rfb

Hydro (Small) - RfbHydro (Pump) - Rfb

Hydro River - NewHydro Dam - New

Hydro (Small) - NewHydro (Pump) - New

Hydro Large Dam - NewNuclear

CoalCoal CCS

GasGas CCSCHP-Bio

CHP-GasCHP-W.Gas

CHP-Gas (Fuel cell)Wind turbine

Solar PVGeothermal

Capital cost (learing rate)

Swiss TIMES electricity model

Model features

� Single region model with 2000-2100 time horizon and an hourly timeslice

� Calibrated to 2000-2010 data

Key Parameters

� Electricity demand growth: 0.7% (2010-2020); 0.4% (2020–2035); 0.27% (2035…).

� Discount rate 3% (slightly higher than the long term yields from confederation bounds)

For more details: R. Kannan and H. Turton (2011) Documentation on the development of Swiss TIMES Electricity Model

(STEM-E), http://eem.web.psi.ch/Projects/STEM-E.html

Electricity generation costs (2010 data)

0

1

10

100

Hyd

ro R

iver

- R

fb

Hyd

ro D

am -

Rfb

Hyd

ro (

Sm

all)

- R

fb

Hyd

ro (

Pum

p) -

Rfb

Hyd

ro R

iver

- N

ew

Hyd

ro D

am -

New

Hyd

ro (

Sm

all)

- N

ew

Hyd

ro (

Pum

p) -

New

Hyd

ro L

arge

Dam

- N

ew

Nuc

lear

Coa

l

Coa

l CC

S

Gas

Gas

CC

S

CH

P-B

io

CH

P-G

as

CH

P-W

.Gas

CH

P-G

as (

Fue

l cel

l)

Win

d tu

rbin

e

Sol

ar P

V

Geo

ther

mal

Rp/

kWh

Long-run

Peak

Short-run

9

Scenario definitions

1. Base scenario (Base) – Self-sufficiency in electricity supply. A constraint is

introduced in such a way that annual exports and imports are required to be balanced

but the timing of electricity trade is left unconstrained.

2. No nuclear scenario (B_NoNuc) - No new investment in nuclear plants, but operation

of the existing nuclear plants can continue till the end of their 50 years lifetime.

3. Renewable scenario (B_RNW) - Nuclear and gas-fired power plants are restricted.

Since Swiss renewable resources are assumed to be not fully adequate to meet the

demands, the self-sufficiency constraint is relaxed so that net imports can account for

up to 35% of the electricity demand.

4. Carbon stabilization scenario (CO2_S) – Capped CO2 emission intensity of

electricity (g-CO2/kWh) to the level in the year 2010. In addition, nuclear investment is

completely restricted, but gas with CCS is available.

10

Results

Electricity generation mix

Electricity generation mix: Summary

-50

0

50

100

150

200

250

300

350

2010

2020

2048

2080

2020

2048

2080

2020

2048

2080

2020

2048

2080

BASE B_NoNuc B_RNW CO2_S

PJ

Pumps

Import (net)

Wood

Waste & Biogas

Wind

Solar

Geothermal

Oil

Coal-CCS

Coal

Gas-CCS

Gas (F)

Gas (B)

Nuclear

Hydro (P)

Hydro (D)

Hydro (R)

� Gas-based generation represents the most cost-effective non-nuclear alternatives but undermines long-term carbon reduction targets. � For low carbon and non-nuclear, imported electricity is required between 10-35% of the demand.� Imported gas/electricity would increase concerns about supply security, particularly in winter when gas demand is also high for heating applications.

11

Results

Installed capacityInstalled Capacity: Summary

0

5

10

15

20

25

30

35

20

10

20

20

20

48

20

80

20

20

20

48

20

80

20

20

20

48

20

80

20

20

20

48

20

80

BASE B_NoNuc B_RNW CO2_S

GW

Wood

Waste & Biogas

Wind

Solar

Geothermal

Oil

Coal-CCS

Coal

Gas-CCS

Gas (F)

Gas (B)

Nuclear

Hydro (P)

Hydro (D)

Hydro (R)

�Short-duration intermittence is not considered but it is likely that dam hydro could support the management of intermittency.

12

Results

Load curve Base scenario (Summer weekday)

Base: SUM-WK (2048)

0

5

10

15

20

0 4 8 12 16 20

GW

h

0

5

10

15

20

25

30

Rp

/kW

h

Export: Base: SUM-WK (2048)

0

2

4

6

8

10

0 4 8 12 16 20

GW

h

Import

Gas-CCS

Gas (CHP)

Gas (F)

Hydro (D)

Hydro (P)

Other RES

Waste

Solar

Geothermal

Oil

Gas (B)

Wind

Nuclear

Hydro (R)

Demand (GW)

Marginal cost

13

Results

Load curve Base scenario (Winter weekday)

Base: WIN-WK (2048)

0

5

10

15

20

0 4 8 12 16 20

GW

h

0

5

10

15

20

25

30

Rp

/kW

h

Export: Base: WIN-WK (2048)

0

2

4

6

8

10

0 4 8 12 16 20

GW

h

Import

Gas-CCS

Gas (CHP)

Gas (F)

Hydro (D)

Hydro (P)

Other RES

Waste

Solar

Geothermal

Oil

Gas (B)

Wind

Nuclear

Hydro (R)

Demand (GW)

Marginal cost

14

Results

Load curve Summer weekday

Base: SUM-WK (2048)

0

5

10

15

20

0 4 8 12 16 20

GW

h

0

5

10

15

20

25

30

Rp

/kW

h

Export: Base: SUM-WK (2048)

0

2

4

6

8

10

0 4 8 12 16 20

GW

h

B_NoNuc: SUM-WK (2048)

0

5

10

15

20

0 4 8 12 16 20

GW

h

0

5

10

15

20

25

30

Rp

/kW

h

Export: B_NoNuc: SUM-WK (2048)

0

2

4

6

8

10

0 4 8 12 16 20

GW

h

B_RNW: SUM-WK (2048)

0

5

10

15

20

0 4 8 12 16 20

GW

h

0

5

10

15

20

25

30

Rp

/kW

h

Export: B_RNW: SUM-WK (2048)

0

2

4

6

8

10

0 4 8 12 16 20

GW

h

CO2_S: SUM-WK (2048)

0

5

10

15

20

0 4 8 12 16 20

GW

h

0

5

10

15

20

25

30

Rp

/kW

h

Export: CO2_S: SUM-WK (2048)

0

2

4

6

8

10

0 4 8 12 16 20

GW

h

15

Results

Load curve Winter weekday

Base: WIN-WK (2048)

0

5

10

15

20

0 4 8 12 16 20

GW

h

0

5

10

15

20

25

30

Rp

/kW

h

Export: Base: WIN-WK (2048)

0

2

4

6

8

10

0 4 8 12 16 20

GW

h

B_NoNuc: WIN-WK (2048)

0

5

10

15

20

0 4 8 12 16 20

GW

h

0

5

10

15

20

25

30

Rp

/kW

h

Export: B_NoNuc: WIN-WK (2048)

0

2

4

6

8

10

0 4 8 12 16 20

GW

h

B_RNW: WIN-WK (2048)

0

5

10

15

20

0 4 8 12 16 20

GW

h

0

5

10

15

20

25

30

Rp

/kW

h

Export: B_RNW: WIN-WK (2048)

0

2

4

6

8

10

0 4 8 12 16 20

GW

h

CO2_S: WIN-WK (2048)

0

5

10

15

20

0 4 8 12 16 20

GW

h

0

5

10

15

20

25

30

Rp

/kW

h

Export: CO2_S: WIN-WK (2048)

0

2

4

6

8

10

0 4 8 12 16 20

GW

h

16

Results

Seasonal electricity supply and demand balance

Seasonal electrcity supply-demand balance (2050)

0

50

100

150

200

250

300

Demand(2050)

Generation Import Export Generation Import Export

Base B_RNW

PJ

Summer

Spring

Fall

Winter

17

Results

CO2 emissions and marginal cost of CO2

CO2 emissions

0

2

4

6

8

10

12

14

20

10

20

20

20

48

20

80

20

20

20

48

20

80

20

20

20

48

20

80

20

20

20

48

20

80

BASE B_NoNuc B_RNW CO2_S

Mt

CO

2

Marginal cost of CO2

0

200

400

600

800

1000

1200

1400

1600

1800

2000

2015 2020 2025 2034 2048 2063 2080 2100

CH

F 20

10/t-

CO 2

18

Results

Undiscounted electricity system costs

Undiscounted electricity system cost: Summary

-2

0

2

4

6

8

10

2010

2020

2048

2080

2020

2048

2080

2020

2048

2080

2020

2048

2080

BASE B_NoNuc B_RNW CO2_S

Billion C

HF20

10

Trade Balance

Tax

Resource

Variable O&M

Fixed O&M

Capital

19

Results

Average cost of electricity supply

Electricity generation cost: Summary

0

2

4

6

8

10

12

201

0

202

0

204

8

208

0

202

0

204

8

208

0

202

0

204

8

208

0

202

0

204

8

208

0

BASE B_NoNuc B_RNW CO2_S

Rp

/kW

h

� With nuclear, average cost of electricity is 4-5 Rp/kWh while the marginal cost of electricity supply at an hourly level rises to 17 Rp/kWh in winter.

�In the non-nuclear options, average cost of electricity doubles (highly sensitive to the gas price & capital cost reduction in renewable technologies).

20

Conclusions

Short-term (through 2025)

� Independent of decisions on new nuclear plants, there is a need for new supply in the short-term.

�Support for the continued operation of existing nuclear and hydro plants remains important under all cases.

� The most cost-effective shot-term supply option is new gas combined-cycle power plants.

� Realising CO2 reduction targets requires considerable investments in non-hydro renewables, incurring high cost.

Medium and long term

� Nuclear is the cost-effective technology options and favourable to a low carbon policy.

�For a low carbon and non-nuclear policy, large investment in renewable or CCS is inevitable, which would double the electricity cost.

� In any options, import of gas or a net import of electricity is required.

� Swiss energy system would still rely on imported electricity for seasonal demands.

21

Conclusions

� Non-nuclear option incurs high cost with some tradeoffs between supply security and climate policy.

� An increased dependence on imported natural gas or electricity, raising supply security concerns. There are needs to develop or enhance policy approaches supporting energy security.

� Developing strategic reserves of natural gas and diversifying supplies.

� Reinforcement of interconnection capacity, expanding energy storage potential and negotiating long-term contracts with reliable partners.

�Deployment of capital intensive renewable technologies requires high capital outlays.

�Financing the necessary capital investment shall be addressed.

�Create an appropriate investment climate that reduces (or shares) some of the risks associated with new technologies.

� Large-scale deployment of CCS is not fully demonstrated. Importantly,potential carbon storage sites are yet to be fully characterized in Switzerland.

Policy implications

22

Future direction

� Within STEM-E

� A comparison between the hourly STEM-E model and an aggregated timeslice model.

� Implementation of other policies, e.g. feed-in tariff, electricity surcharge, …..

� Sensitivities on electricity demand variance, …

� Extension of STEM-E to other sectors – A whole energy systems model (on going and funded by Swiss Federal Office of Energy).

� CROSSTEM (Swiss + 4 regions) – inclusion of four cross bordering counties’ electricity systems (to be kicked off and funded by Swiss Federal Office of Energy).

Energy Economics GroupLaboratory for Energy Systems Analysis

General Energy Research Department & Nuclear Energy and Safety Research Department