Development of Swiss TIMES electricity model

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Wir schaffen Wissen – heute für morgen

Joint TERI-ETSAP Workshop

Energy Modelling Tools & Techniques to address Sustainable Development & Climate Change New Delhi, 21-22 January 2010

Experience from the development of a new Swiss TIMES Electricity Model Ramachandran Kannan

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Presentation outline

Overview of Swiss energy system

• Energy and emissions

• Policy objectives

Swiss power sector

• Challenges and opportunities

Development of Swiss TIMES electricity model

• Swiss MARKAL model

• Motivations

• Status of the current model (Sept-Nov 09)

Preliminary results

Future direction

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Swiss energy system overview

Final energy dem and in 2008 (900 PJ)

Industry 20%

Service 16%

Transport 34%

Agriculture

2% Residential

28%

Final energy demand in 2008 (900 PJ)

Gas 12%

Oil (Heating) 22%

Oil (Transport) 34%

Waste District heat 1%

2%

Wood 4%

Coal 1%

Renewable 1%

Electricity 23%

Energy Economy

Energy expenditure: ~US$ 25 Billion* (5.4% of GDP) Energy import: 4.1% of total import expenditure Energy dependency: 80% (two-third of the final energy demand is fossil fuels)

Electricity dem and in 2008 (211 PJ)

Industry 33%

Residential 30%

Agriculture 2%

Transport 8%

Service 27%

* CHF 28. 29 Billion SOFE, 2008: Table 2

CO2 emission from fuel combusion (41 Mt-CO2 in 2007)

Transport

39% Industry

14%

Conversion 8%

Others 2%

Agriculture 1%

Residential 25%

Commercial 11%

Swiss energy system overview

CO₂ emissions

Energy use accounts for 82% of the total GHG emissions

Residential and transport sectors account for two- third of the total CO₂emissions

Power sector is nearly decarbonised

CO₂emission declines in end-use sectors due to fuel switch from oil to gas while natural gas based emission increased by 65% from 1999 level

CO2 em ission

0 5 10 15 20 25 30 35 40 45

1990 2007

Mt-CO2

Residential Others Agriculture Commercial Industry Transport Energy

CO2 emission by fuel Gas 14%

Liquid 75%

Others 11%

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Swiss energy system overview

Energy policy objectives To improve energy efficiency

To extend the use of renewable forms of energy To ensure the security of supplies

To relieve the burden on the climate and thus promote a sustainable economy

Policy goals for the year 2010

Fossil fuel reduction target of 10% from 2000 level

Carbon reduction targets of 10%^* (& 80% by 2050)from 1990 level Limit the growth in electricity demand to < 5% from 2000 level Renewable electricity production of 1% from 2000 level (0.5 TWh) Renewable heat production of 3% from 2000 level (3 TWh)

*15% from combustible fuel and 8% from vehicle fuel

Source: SwissEnergy, 2009

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Swiss energy system overview

Trend in greenhouse gases with respect to 1990 level

Source: FOEN, 2009

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Swiss energy system overview

Trend in sectoral GHG emissions with respect to 1990

2010 10%

Source: FOEN, 2009 Can the CO₂target

be met?

Swiss energy system overview

GHG emissions within energy sector

The fluctuation from energy industryis caused by annual fluctuation in waste incineration and combustion activities in the petroleum refinery industry

Source: FOEN, 2009

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Swiss power sector

Gas 1.22%

Wind 0.49%

Solar PV 0.82%

Landfill gas 0.21%

CHPs 50%

Waste incinerati

ons 48%

Others 5%

Nuclear 39%

Hydro-Runoff 25%

Hydro-Dams 31%

Electricity generation mix (2008)

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Swiss power sector

Swiss Electricity balance (2008)

Electricity demand: An annual average growth of 1.7% over the past ten years

Self sufficiency in annual electricity generation, but still dependent on imported electricity for seasonal demand

Electricity trading (US$ 7 Billion in 2008*)is important in terms of power system balance and trade revenue

Swiss Electricity balance 2008

-30 -20 -10 0 10 20 30 40 50

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

PJ

Swiss Electricity balance

-300 -200 -100 0 100 200 300 400 500

2000 2005 2008

PJ

Imports Exports Net generation Losses Consumption

* CHF 7.96 B, Source: SOFE, 2008: Table 42

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Swiss power sector

CO₂ emissions trend since 1990

Power sector CO₂emission is increased by 35%, but mainly from incineration plants!

CO2 emissions from power sector

0 1 2 3 4

1990 2007

Mt-CO2 Solid

Liquid Gas Others

Source: FOEN, 2009

Swiss power sector

Weekly: winter

3 4 5 6 7 8

0 6 12 18

MW

WIN_Wk WIN_Su WIN_Sa

Weekly: summer

3 4 5 6 7 8

0 6 12 18

MW

SUM_Wk SUM_Su SUM_Sa

Electricity load curves (2008) Seasonal demand pattern

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Swiss power sector

Seasonal: Weekdays

3 4 5 6 7 8

0 6 12 18

MW

WIN_Wk SPR_Wk SUM_Wk FAL_Wk

Seasonal: Saturdays

3 4 5 6 7 8

0 6 12 18

MW

WIN_Sa SPR_Sa SUM_Sa FAL_Sa

Seasonal: Sundays

3 4 5 6 7 8

0 6 12 18

MW

WIN_Su SPR_Su SUM_Su FAL_Su

Electricity load curves (2008) Weekly demand pattern

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Swiss energy system overview

Where are we in meeting the policy targets for 2010? -Status in 2007 Fossil fuel reduction target of 10%: +1.5%

Carbon reduction targets of 10%: -1.6%

Limit the growth in electricity demand to < 5%: +12.1%

Renewable electricity production of 1% (0.5 TWh): +0.44 TWh ☺☺☺☺

Renewable heat production of 3% (3 TWh): +2.63 TWh ☺☺☺☺

Source: SwissEnergy, 2009

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Swiss power sector

Challenges

Far away from the policy target of limiting the electricity demand growth by <5%

Uncertainties in future growth of electricity demand

-due to uncertainties in uptake of energy efficiency on the demand side

Retirement of the exiting nuclear reactors and filling the supply gap

-political uncertainty over new investment / possible life extension of nuclear reactors

Discussions on new natural gas plant or distributed CHP

-ongoing consultation of carbon offset policy

Source: Axpo, 2009

Swiss power sector

Opportunities

Large pumped storage potential - unique position to store off-peak electricity (from base load plants or intermittence renewable) and supply (and export) for peak load demand

Large potential for geothermal power (and heat) generation without any intermittence issues – unproven technology, but relatively cheap

Electricity feed-in tariff to promote small scale (<10MW) renewable sources

Can contributes to the decarbonisation of transport sector via electric (plug-in or battery) or hydrogen (ICE or fuel cell), whichever will be the winner

Source: Axpo, 2009

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Swiss MARKAL model

2000-2050 in 5 years time step

Five end-use sector with detailed energy pathways, including advanced vehicle technologies and biorefineries

Key analytical tool used for the analyses of 2 kW society and Energie Trialog project

Limitations of Swiss MARKAL

Load curve is not fully implemented within the MARKAL approximation of six timeslices

Electricity trading is fully exogenous (not cost optimized)

Issues of end-of-horizon effects to analyse long-term policy goals

Reinvestment or refurbishment for hydropower plant (i.e. retrofit / repower / reengineering) has not been fully accounted

Inadequate model documentation to understand the model input data Other general limitation within MARKAL paradigm

Developments of Swiss TIMES electricity model

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Motivations

An advanced analytical tool similar to MARKAL

- To generate better insights for the short and medium time horizon with smaller time steps while retaining long model time horizon

- Better treatment of technical and economical life time to reflect market risks or behaviours

Possibilities of implementing high number of seasonal, weekly and diurnal timeslice, thereby enhancing the depiction of load curve

- Exploring the possibilities of electricity trading under a cost optimal framework

- Peak demand for non-electric commodity (e.g. to see the tradeoffs between gas and electricity distribution networks at peak hours)

Easy data management with Veda interface

- Option for scheduling retirement or refurbishment of the existing power plants (over 3000 small hydropower plants)

Limited improvement in MARKAL through ETSAP supports

Developments of Swiss TIMES electricity model

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Developments of Swiss TIMES electricity model

Model (version 1.0) overview

Long time horizon (2000-2100) with a combination of 2, 5,10 and 20 years time steps

36 annual timeslices - the finest timeslice has an hour resolution Actual electric load curve for year 2008 is implemented

Calibrated to actual electricity and fuel data for years 2000-2008, and near term calibration till 2015

Large scale hydro and nuclear plants are characterised at plant level based on historical data

Explicit electricity demand for the five end use sectors

• Demand drivers can be implemented e.g. residential demand linked to population growth or household income; industrial demand linked to GDP, …

• Enable to analyse tax and subsidies at sectoral level, e.g. carbon tax for service sector or subsidies for residential renewable micro electricity generation

Preliminary results for four scenarios focusing on low carbon objectives and uncertainties of new investment in nuclear plant

Developments of Swiss TIMES electricity model Model input data sources

(Caveat: So far the focus has been on model methodology and structure. Input dada to be updated!)

Calibration

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Various publications of SOFE

- Schweizerische Gesamtenergiestatistik, Elektrizitatsstatistik, Statistik der

Wasserkraftanlagen, Thermische Stromproduktion inklusive Wärmekraftkoppelung,

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^FOEN

- Swiss communication to UNFCCC

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European Network of Transmission System Operators for Electricity

- Load curves, electricity trading, ….

Energy resources

•

Fossil fuel prices

- UK Climate Change project

•

Renewable potential

- Renewable energy map of SATW (Swiss Academy of Engineering Sciences)

Technology data

•

Swiss MARKAL, IEA

Electricity demand projection

•

Energy perspective 2035

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Developments of Swiss TIMES electricity model

Modelling issues

Input data quality –extensive sensitivities, working with the Technology Assessment Group and external stakeholder, ….

The three diurnal timeslices did not give a perfect fit for weekend electricity demand pattern - could be improved by choosing 8-10 diurnal timeslices but computational and data availability issues need to be addressed

Difficulties in capturing electricity trading mechanism (price vs. cost) – Enhancing the time slice for peak load

What currency to adopt CHF vs. $ (vs. €)?

TIMES vs. actual demand

3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0

0 4 8 12 16 20

MW

WIN_Wk TIMES_WIN_Wk SUM_Su TIMES_SUM_Su

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Preliminary results

Scenarios

1. BASE: Business as usual

2. CO2_S: Stabilizing CO₂ at 2000 level (power sector only) 3. NoNuc_S: The above scenario without any newly built nuclear 4. CO2_Z: Zero carbon electricity by 2050

5. NoNuc_Z: The above scenario without any newly built nuclear

CO₂ emissions from waste incineration and biomass are not accounted!

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Preliminary results

Electricity generation mix

Base NoNuc_Z

-200 -100 0 100 200 300 400 500

2000 2010 2020 2035 2050 2080 2100

PJ

Wastes Imports Solar PV/Wind Biomass Geothermal Hydro Oil Nuclear Gas Export

-200 -100 0 100 200 300 400 500

2000 2010 2020 2035 2050 2080 2100

PJ

Expansion of installed capacity

0 1 2 3 4 5 6 7 8 9

2000 2010 2020 2035 2050 2080 2100

GW

Preliminary results

Electricity expansion plan

Expansion of installed capacity

0 1 2 3 4 5 6

2000 2010 2020 2035 2050 2080 2100

GW

Base NoNuc_Z

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Preliminary results

Marginal cost

CO2_Z NoNuc_Z

Marginal cost of CO2

0 200 400 600 800 1000 1200

2000 2010 2020 2035 2050 2080 2100

$/t-CO2

Marginal cost of CO2

0 200 400 600 800 1000 1200

2000 2010 2020 2035 2050 2080 2100

$/t-CO2

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Preliminary results

Comparison of electricity generation mix in 2050

0 50 100 150 200 250 300

BASE CO2_S NoNuc_S CO2_Z NoNuc_Z

PJ

Export Gas Nuclear Oil Hydro

Geothermal Biomass Solar PV/Wind Imports Wastes

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Preliminary results

Comparison of primary energy supply in 2050

*In 2000, an equal amount of imported electricity was exported

Primary energy supply

0 100 200 300 400 500 600 700

2000 BASE CO2_S NoNuc_S CO2_Z NoNuc_Z

PJ

Gas Nuclear Oil

Hydro Geothermal Biomass

Solar PV/Wind Imported Electricity Wastes

Preliminary results

Comparison of energy system cost

Undiscounted energy system cost

0 2 4 6 8 10 12

BASE CO2_S NoNuc_S CO2_Z NoNuc_Z

Billion $ (2000)

Resource Capital Varibale O&M Fixed O&M

• Resource cost includes imported electricity

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Future direction

Extending the timeslice to 72 or 144 to enhance load curve fit

Extension to other energy service demands (migration from electricity model to energy system model)

Stakeholder engagement for data validation

- Internal (PSI and other ‘like’ minds) - External

Updating the input data parameters:

- Technology data (NEEDs, Axpo, ??) - Electricity demand

- Fossil fuel price

Disaggregation of hydropower plants at individual plant level to enhance reinvestment and/or refurbishment under a cost optimization framework

Implementing electricity feed-in tariff policy

Enhancing the characteristics of electricity trading – country specific interconnectors, and price

Energy Economics Group

Laboratory for Energy Systems Analysis

General Energy Research Department & Nuclear Energy and Safety Research Department