Wir schaffen Wissen - heute für morgen Potential impact of post Fukushima nuclear policy on the future role of CCS in climate mitigation scenarios in Switzerland Nicolas Weidmann, Hal Turton, and Ramachandran Kannan Energy Economics Group, Laboratory for Energy Systems Analysis, Paul Scherrer Institute, Switzerland IEW212, June 19, 212
Outline 1 Introduction Scope, Objective Swiss MARKAL model Scenario definitions 2 Scenario analysis Reference scenario, climate scenario Nuclear phase-out under climate constraint Carbon capture and storage 3 Conclusion and Outlook Summary and conclusion Outlook
Overview Swiss energy system Primary and final energy consumption PJ 14 12 1 8 6 4 2 Swiss primary and final energy consumption 21 Primary energy Final energy (by fuel) Final energy (by end use sector) Agriculture / stat. Diff Transport Services Industry Residential District heat Electricity Other renewables Nuclear Hydro Gas Oil products Oil Waste Coal Wood
Overview Swiss energy system Electricity generation mix (21) Power sector nearly decarbonised Self sufficiency in annual electricity generation but still dependent on import for seasonal demands Electricity trading is important (power system balance, revenue)
Overview Swiss energy system Challenges for the future Swiss energy system Development of future electricity demand (population/gdp growth increase, electrification) Nuclear phase-out Climate policy Energy security Future availability of technologies supporting low carbon energy system
Objective and Methodology Objective Analyze how uncertainties may affect future Energy system and cost-effectiveness of technologies Identify robust combinations of technologies and fuels Potential role of low carbon electricity sources (new renewables, CCS) under nuclear and climate constraints Scenario analysis Uncertainties Definition of scenarios Scenarios analysed using Swiss MARKAL energy system model
Swiss MARKAL model Description of modeling framework Technology-rich bottom-up energy system model of entire Swiss energy system (single region model) Extensive representation of end-use efficiency technologies 4-years time horizon (21-) Calibration to years 2-21
History of Swiss MARKAL model Model development initiated by M. Labriet at the University of Geneva (Labriet, 23) Building up first version of the model including five end-use sectors, conversion and supply Further developments and analyses by T. Schulz (Schulz, 27; Schulz et al., 27, 28) Implementation of extensive end-use technology options in transport and residential sector (including energy saving options based on marginal cost curves) and N. Weidmann (Weidmann, Turton, andwokaun, 29; Weidmann, Kannan, andturton, 211; ETS, 29) Further development of the model in all end-use sectors Calibration of the entire model to 21 data and demand update Development and implementation of CCS module
Swiss MARKAL model Reference energy system Import of Oil Import of Natural gas Renewable resources Domestic Biomass Wind energy Refineries Natural gas Fischer- Tropsch Electricity sector Gas powerplant Biomass CHP Wind turbine Bio fuels Heat End-use technologies Transport (cars, trucks, aviation, ships, railway) Industry (lighting. Heating, autoproduction of electricity) Residential (lighting cooking, heating, cooling) Solar energy Hydro energy Solar PV Hydro powerplant Electricity Services (lighting, heating, applications) Import of uranium Nuclear powerplant Agriculture Resources Conversion End-use Energy services
User-defined constraint: A_CCS_1x Activity(ENGACCSR)*EFF(CCS_CAPT) >= Activity(CCS_CAPT) User-defined constraint: A_CCS_2x Activity(ENGHCCSR)*EFF(CCSCAPTH) >= Activity(CCSCAPTH) User-defined constraint: A_CCS_1 Activityi*ENVACTcapt,i (ENGACCS tech) = Activity of CCS_COMB_1 User-defined constraint: A_CCS_6 Activityi*ENVACTcapt,i (CHPNGCCS tech) = Activity of CCS_COMB_2 User-defined constraint: A_CCS_3 Activity(CCS_CONV_2) = Activityi*ENVACTi(CCS_CAPTxx) User-defined constraint: A_CCS_5 Activity(CCS_CONV_2) = Activityi*ENVACTi(CCSCAPTHxx) User-def. constraint: A_CCS_A Activityi(CCS_COMB_1, CCS_COMB_2, CCS_CAP) = Activity(CCS_TRANS) User-def. constraint: A_CCS_B Activity(CCS_TRANS) = Activity(CCS_STG) CCS module Swiss MARKAL model Swiss MARKAL CCS Module Natural gas Electricity CO2 ENGACCS3 Powerplant + capt. ENGACCS5 Powerplant + capt. CCS_COMB_1 Combine captured CO2 streams Conv. NGCC CCS retrofitting ENGACCSR1 Powerplant ENGACCSR3 Powerplant CCSCAPTE1 Capturing of CO2 CCS_CONV_1 CCSCAPTE3 Combine captured Capturing of CO2 CO2 streams IMPSTGPOT1 Import of STGPOT (storage potential 1) IMPSTGPOT2 Import of STGPOT (storage potential 2) ENGACCSR5 Powerplant CCSCAPTE5 Capturing of CO2 STGPOT CO2_STOR CCS_TRANS Transport of CO2 CCS_STG Storage of CO2 Heat CHPNGCCS3 CHP Powerplant CHPNGCCS5 CHP Powerplant CCS_COMB_2 Combine captured CO2 streams CHP NGCC CCS CHPNGCCR1 CHP Powerplant CCSCAPTH1 Capturing of CO2 retrofitting CHPNGCCR3 CHP Powerplant CCSCAPTH3 Capturing of CO2 CCS_CONV_2 Combine captured CO2 streams CHPNGCCR5 CHP Powerplant CCSCAPTH5 Capturing of CO2
Scenario definitions Ref : Reference scenario (nuclear replacement, no (climate) policies) NoNuc: Nuclear phase-out Clim: Climate target (domestic CO 2 reductions by 2% by, 6% by ) Cumul A: Cumulative CO 2 target Cumul B: Cumulative CO 2 target with fixed end point) CCS: Carbon Capture and Storage technologies available General model assumptions Oil, coal, and geothermal based power generation are fully restricted Hydro assumed to follow a fixed production path (34.8 TWh el in, 33. TWh el in ) Renewable potentials (Solar PV: 13.7 TWh el, Wind: 4 TWh el, Biomass: 28.1 TWh th ) Discount rate: 3%
Reference scenario Primary energy supply PJ 12 1 8 6 4 2 Primary energy - Ref 21 215 225 23 24 245 Solar Wind Biomass Hydro Nuclear Gas Oil Coal
Climate scenario Primary energy supply 12 Primary energy - Ref vs. Clim. 1 8 6 4 2 21 PJ Geo Solar Wind Biomass Hydro Nuclear Gas Oil Coal Ref Ref Clim
Climate scenario Electricity and CO 2 emissions Electricity gen. - Ref vs. Clim CO 2 emissions - Ref vs. Clim PJ 35 3 25 2 15 1 5 Million tons of CO 2 45 4 35 3 25 2 15 1 5 21 Ref Ref Clim 21 Ref Ref Clim Solar Biomass CHP NGA CC Hydro Wind NGA CHP Nuclear Other Electricity Residen al Service Upstream Transport Industry Agriculture
Climate scenario Final energy in residential heating and car sector Final energy res. heat. - Ref vs. Clim Final energy car sector - Ref vs. Clim 18 18 16 16 14 14 12 12 1 1 PJ 8 PJ 8 6 6 4 4 2 2 21 21 Ref Ref Clim Ref Ref Clim Savings District heat Oil Electricity Natural gas Biomass Ba ery Natural gas Diesel Hydrogen Gasoline
Nuclear phase-out under climate constraint Primary energy supply Primary energy - Clim. vs. Clim.+NoNuc 12 1 Geo Solar 8 Wind PJ 6 4 Biomass Hydro Nuclear 2 21 Gas Oil Coal Ref Clim Clim + NoNuc
Electricity supply Nuclear phase-out under climate constraint 35 Electricity gen. - Clim. vs. Clim + NoNuc PJ 3 25 2 15 1 5 Solar Wind Biomass CHP NGA CHP NGA CC NGA CC CCS Nuclear Hydro Other 21 Ref Clim Clim + NoNuc
CO 2 -emissions Nuclear phase-out under climate constraint CO 2 emissions - Clim vs. Clim+NoNuc Million tons of CO 2 45 4 35 3 25 2 15 1 5 21 Electricity Transport Residen al Industry Service Agriculture Upstream Ref Clim Clim + NoNuc
Nuclear phase-out under climate constraint Final energy in residential heating and car sector Final energy res. heat. - Clim vs. Clim+NoNuc Final energy car sector - Clim vs. Clim+NoNuc 18 16 14 18 16 14 12 12 PJ 1 8 PJ 1 8 6 6 4 4 2 2 21 21 Ref Clim Clim + NoNuc Ref Clim Clim + NoNuc Savings District heat Oil Electricity Natural gas Biomass Ba ery Natural gas Diesel Hydrogen Gasoline
CCS Electricity supply 35 Electricity gen. - CCS in nuclear replacement and nuclear phase-out PJ 3 25 2 15 1 5 Solar Wind Biomass CHP NGA CHP NGA CC NGA CC CCS Nuclear Hydro Other 23 24 245 23 24 245 23 24 245 23 24 245 Clim Clim+CCS Clim+NoNuc Clim+NoNuc+CCS
CCS Final energy in residential heating and car sector PJ 18 16 14 12 1 8 6 4 2 Final energy res. heat. - CCS w/ & w/o Nuclear 21 Ref Clim + NoNuc Clim + NoNuc + CCS Savings District heat Oil Electricity Natural gas Biomass PJ 18 16 14 12 1 8 6 4 2 Final energy car sector - CCS w/ & w/o nuclear 21 Ref Clim + NoNuc Clim + NoNuc + CCS Ba ery Natural gas Diesel Hydrogen Gasoline
Alternative CO 2 -reduction pathways CO 2 -emissions Million tons of CO 2 Million tons of CO 2 45 4 35 3 25 2 15 1 5 45 4 35 3 25 2 15 1 5 CO 2 emissions CO2 reduction pathways 21 23 24 21 23 24 21 23 24 Clim Cumul A Cumul B CO 2 emissions CO2 reduction pathways with CCS 21 23 24 21 23 24 21 23 24 Clim + CCS Cumul A + CCS Cumul B + CCS Electricity Transport Residential Industry Service Agriculture Upstream OcCC Total CCS Electricity Transport Residential Industry Service Agriculture Upstream OcCC Total
System costs 5.% Incremental total discounted system costs (rel. to Ref) 4.5% no CCS 4.% CCS 3.5% 3.% 2.5% 2.% 1.5% 1.%.5%.% Ref Clim Clim + NoNuc Cumul A + NoNuc Cumul B + NoNuc
Summary and conclusion Changes over time across entire energy system (supply and end-use). Climate-, nuclear policy constraints have system-wide effects (e.g. interplay between end-use and power sectors) Car sector: Trends towards higher efficiency (across all scenarios) and low carbon intensity (climate scenarios). However, fossil fuels will play major role during the next 4 years. Residential heating: Implementation of energy saving options and low carbon heatings systems attractive across wide range of scenarios (with and without climate targets)
Summary and conclusion (cont.) New renewables become attractive towards the end of time horizon. Climate targets and nuclear phase-out promote earlier deployments. CCS only attractive under nuclear phase-out and stringent climate targets. First, new renewables are deployed. CCS has effects on end-use sectors: Residential heating: Electrification of energy system more heat pumps, less saving measures Car sector: Decarbonisation of electricity sector lower efficiency and more fossil fuels in car sector Costs: Nuclear phase-out increase in system costs. CCS could reduce costs for climate mitigation under nuclear constraint (dependent on stringency of climate target).
Outlook Improvements and extension of technology detail in services and industrial sectors (including energy efficiency options) Sensitivity analysis on crucial model input parameters (technology costs, discount rate) Extension of CCS module in Swiss MARKAL model and analysis of additional CCS scenarios Energy service demand update (to be implemented in Swiss MARKAL and Swiss TIMES models)
References ETS (29), Energie-strategie - impulse für die schweizerische energiepolitik. grundlagenbericht, Tech. rep., Energietrialog Schweiz, URL <http://www.energietrialog.ch/cm_data/grundlagenbericht.pdf>. Labriet, Maryse (23), Switzerland markal: Structure and assumptions, Tech. rep., University of Geneva (Logilab), updated version 2.. Schulz, Thorsten Frank (27), Intermediate steps towards the 2-Watt society in Switzerland: An energy-economic scenario analysis, Ph.D. thesis, Eidgenössische Technische Hochschule ETH Zürich, URL http://dx.doi.org/nr.17314,doi:1.3929/ethz-a-5478373, nr. 17314, DOI: 1.3929/ethz-a-5478373. Schulz, Thorsten Frank, Leonardo Barreto, Socrates Kypreos, andsamuel Stucki (27), Assessing wood-based synthetic natural gas technologies using the swiss-markal model, Energy, 32(1), 1948 1959. Schulz, Thorsten Frank, Socrates Kypreos, Leonardo Barreto, andalexander Wokaun (28), Intermediate steps towards a 2 watt society in switzerland: An energy-economic scenario analysis, Energy Policy, 36 (4), 133 1317. Weidmann, Nicolas, Ramachandran Kannan, andhal Turton (211), Swiss climate change and nuclear policy: a comparative analysis using an energy system approach and a sectoral electricity model, Swiss Journal of Economics and Statistics, Special issue on Swiss energy modeling. Weidmann, Nicolas, Hal Turton, andalexander Wokaun (29), Case studies of the swiss energy system - sensitivity to scenario assumptions assessed with the swiss markal model. studie im auftrag des energie trialog schweiz (www.energietrialog.ch)., Tech. rep., Paul Scherrer Institut, Villigen PSI, Switzerland.
Thank you for your attention Acknowledgements: Prof. A. Wokaun, Dr. S. Hirschberg, Dr. H. Turton Members of Energy Economics Group, Laboratory for Energy Systems Analysis CARMA (Carbon management in power generation) - Project