swiss energy perspectives

Transformation of the Swiss Energy System for aNet-Zero Greenhouse Gas Emission Society

Results from the Joint Activity Scenarios & Modelling

Schweizerische Eidgenossenschaft

Confédération suisse

Confederazione Svizzera

Confederaziun svizra

Swiss Confederation

Innosuisse – Swiss Innovation Agency

Transformation of the Swiss Energy System for a Net-Zero Greenhouse Gas Emission Society

Impressum

PublisherETH Zurich

EditorsAdriana Marcucci, Gianfranco Guidati, Domenico Giardini (ETH Zurich)

AuthorsEvangelos Panos, Tom Kober, Kannan Ramachandran, Stefan Hirschberg, Christian Bauer, Tilman Schildhauer(PSI); Kai Nino Streicher, Selin Yilmaz, Jibran Zuberi, Martin Patel (UNIGE); Ingmar Schlecht, Rebecca Lordan-Perret, Hannes Weigt (UNIBAS); Xiang Li, Rahul Gupta, Theodoros Damartzis, Francois Marechal, MarioPaolone (EPFL); Andrew Bolliger, Portia Murray (EMPA); Matthias Berger (HSLU); Dani Carbonell Sanchez(HSR); Vanessa Burg (WSL)

ContactGianfranco Guidati ([email protected])

Editorial and LayoutBarbara Naegeli, Silvia Passardi (ETH Zurich)

Title ImagesTop left: Mariana Proença for Unsplash (https://unsplash.com/photos/_h0xG4s6NFg).Top right: CHUTTERSNAP for Unsplash (https://unsplash.com/photos/xJLsHl0hIik).Bottom left: Hoval AG (https://www.hoval.ch/Die-leiseste-Luft-Wasser-Wärmepumpe-für-zuhause/reference/schiblibaldingen).Bottom right: Alberta Carbon Trunk Line (https://actl.ca/whats-new-actl2020/actl2020/).

CitationMarcucci, A., Guidati, G., Giardini, D. (eds.), Bauer, C., Berger, M., Bolliger, A., Burg, V., Carbonell Sanchez, D.,Damartzis, T., Evangelos, P.,Gupta, R., Hirschberg, S., Kober, T., Li, X., Lordan-Perret, R., Marechal, F., Murray,P., Paolone, M., Patel M., Ramachandran, K., Schildhauer, T., Schlecht, I., Streicher, K. N., Weigt, H., Yilmaz,S., Zuberi, J. (2021): Transformation of the Swiss Energy System for a Net-Zero Greenhouse Gas EmissionSociety – Results from the Joint Activity Scenarios & Modelling, Synthesis Report, ETH Zurich, 2021.

Date of Issue01.09.2021

The JASM project was a joint activity of the eight Swiss Competence Centers for Energy Research(SCCER). The continuous exchange with researchers from the SCCER was vitally important and is thankfullyacknowledged. JASM is financially supported by the Swiss Innovation Agency Innosuisse.

ii

mailto:[email protected]

https://unsplash.com/photos/_h0xG4s6NFg

https://unsplash.com/photos/xJLsHl0hIik

https://www.hoval.ch/Die-leiseste-Luft-Wasser-W�rmepumpe-f�r-zuhause/reference/schiblibaldingen

https://www.hoval.ch/Die-leiseste-Luft-Wasser-W�rmepumpe-f�r-zuhause/reference/schiblibaldingen

https://actl.ca/whats-new-actl2020/actl2020/


Executive Summary

Switzerland aims at reducing its greenhouse gasemissions (GHG) to net-zero by the middle of thecentury. Reaching this ambitious target requires im-portant changes to the energy system. In the JointActivity Scenarios and Modelling (JASM), modellingteams from the eight Swiss Competence Centers forEnergy Research (SCCER) worked together to ana-lyze alternative configurations of the energy systemand possible pathways to reach this goal. This ap-proach is different from other efforts to define a longterm energy strategy for Switzerland, as it is basedon the combined output of the Swiss energy researchcommunity. To achieve this, we developed and used aframework that soft-links a variety of models from theproject partners.

Future configurations of the Swiss energy systemare influenced by uncertainties on demographicand economic growth, technological developmentand acceptance, market designs and global climatechange. However, despite these uncertainties, wewere able to derive a robust narrative for a net-zeroSwitzerland, that identifies those elements andtechnologies that will very like be a part of our futureenergy system. This narrative includes the followingspecific recommendations for policy measures andactions today.

Heating. The heating sector will largely abandonthe use of fossil fuels. The dominant technology for do-mestic heating are heat pumps, aided by the combus-tion of wood. Thermal grids will grow strongly and arefed by waste incineration plants and large scale heatpumps. Alternatives are district heating and coolingsystems with decentralised small scale heat pumps.For industrial heat, we see a switch to medium andhigh-temperature heat pumps, electric heaters, andhydrogen for high temperature levels. Additionally,we find that medium temperature heat sources suchas geothermal or solar thermal will play an importantrole for all these applications. Generally, there is atrade-off between a switch to new energy sources andefficiency measures that directly reduce heat demandin the residential and industrial sectors. We find thatin an overall cost optimization, these efficiency mea-sures are generally cost-effective to reduce relatedCO2 emissions.

Mobility. Private passenger transport must belargely electrified. Incentives will be needed tofoster the installation of charging stations in theprivate and public space. Electrification becomesalso increasingly important for light duty vehiclesfor freight transport services. If battery-electricmobility is not possible due to heavy load, range orconsumer preference limitations, hydrogen fuel cellvehicles must be deployed or alternatively synthetichydrocarbon fuels. Clearly, direct electrificationof transport and electricity-based fuels representthe majority of electricity consumption growth in future.

CCS and negative emissions. To reach net-zeroGHG emissions, the energy sector must avoid CO2

emissions where possible and compensate emis-sions from other sectors where abatement is morechallenging, such as agriculture or some industrialprocesses. This requires the application of CO2

capture and storage (CCS) on waste incineration andcement plants, and the deployment of technologiesto produce negative emissions, such as biomasscombined with carbon capture and storage (BECCS).BECCS technologies include anaerobic digestion,wood gasification to methane or hydrogen, or woodcombustion with CCS to produce electricity and heat.Without CCS the net-zero ambition of Switzerlandcannot be achieved.

Electricity supply. Electricity demand increasesdue to the electrification of heating and mobility,reaching 70–90 TWh/a in 2050. After the nuclearphaseout, the electricity that was produced withnuclear power plants will mainly come from renewablesources, mostly photovoltaics (15–30 TWh/a) andwind, plus some thermal power plants and imports.The last two will be especially relevant for the wintermonths when solar generation is low. The relevanceof energy imports will highly depend on the marketdesign, the climate policies abroad and politicaldecisions concerning security of supply.

Electricity storage. Switching from reliablenuclear power to fluctuating renewables poses chal-lenges to the energy system. This can be alleviated tosome extent by storage and flexibility technologies.

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First priority will be electricity storage, from batteriesat the lowest voltage level to pumped hydro powerstations. Given the limited storage volume, thesetechnologies can tackle the day-night cycle, especiallyin the summer months. Flexible regulated hydropowerplants that can complement PV generation are alsorequired. Increasing the volume of hydro reservoirs bydam heightening will help to increase winter electricityproduction.

Flexibility and sector coupling. Coupling theheating demand with the electricity production givesadditional flexibility and storage options to deal withthe fluctuation of renewable electricity. These include:Large scale heat pumps at district heating level thatcharge a seasonal thermal energy storage during thesummer months; or electrical heaters with short-termthermal storage that supply process heat. Also theconversion of electricity to hydrogen via electrolysis,coupled with short-term or seasonal storage, willplay a role. In mobility, the efficient integration ofGrid-to-Vehicle and Vehicle-to-Grid schemes providesa number of advantages to the power system. Theneed for flexibility would also require a market opening,which entails a variety of opportunities for centralisedstorage (including new solutions based on hydrogenand e-fuels), for flexible consumers (individual onesor those collectively offering their capacities throughaggregators) with decentralised storages and smart

demand technologies, and for energy producers whocan be integrated via peer-to-peer trading.

The future energy system. Despite the impor-tance of electrification for heating and mobility, thefuture is not simply all-electric. Biomass plays animportant role as a source of chemical energy andto produce negative CO2 emissions via BECCStechnologies. Hydrogen can help to decarbonizetransport, power and heat, and can generate negativeemissions when produced from biomass. CO2

needs to be captured and stored wherever possible.Since domestic storage options have not yet beenidentified at the required scale of 10–20 MtCO2 /a,an integration with an European CO2 transport andstorage infrastructure is of paramount importance.

Continued research on holistic analyses on therestructuring of the energy system. Given the am-bitions of the energy transition, which involves techni-cal, economical, environmental, political and societalchallenges, further collaborative research addressingthese challenges in a systematic and integrated wayis needed to support decision-making. Energy mod-elling and holistic scenario analyses play a pivotal rolein this not only by providing quantitative insights butalso by connecting various research domains which isessential to address the fundamental changes of theenergy system ahead.

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Acronyms and Abbreviations

ARE Amt für Raumentwicklung (Federal Office for Spatial Development)BAFU Bundesamt für Umwelt (Federal Office for the Environment)BAU Business As Usual ScenarioBFE Bundesamt für Energie (Swiss Federal Office of Energy)BFS Bundesamt für Statistik (Federal Statistical Office)CCS CO2Capture and StorageCDD Cooling Degree DaysCHP Combined Heat & PowerCLI Climate Policy ScenariosEMPA Eidgenössische Materialprüfungsanstalt (Swiss Federal Laboratories for Materials

Science and Technology)EPFL École Polytechnique Fédérale de Lausanne (Swiss Federal Institute of Technology

in Lausanne)EPOL Energy Policy ScenariosERA Energy Reference AreaETH Eidgenössische Technische Hochschule Zürich (Swiss Federal Institute of

Technology in Zürich)GDP Gross Domestic ProductGHG Greenhouse GasesGSHP Ground Source Heat PumpGVA Gross Value AddedJASM Joint Activity Scenarios & ModellingHDD Heating Degree DaysHP Heat PumpHSLU Hochschule Luzern (Lucerne University of Applied Sciences and Arts)PSI Paul Scherrer InstitutPV PhotovoltaicsRCP Representative Concentration PathwaySCCER Swiss Competence Center for Energy ResearchSCCER-SoE SCCER Supply of ElectricitySES Swiss EnergyscopeSTEM Swiss TIMES Energy System ModelUNIBAS Universität Basel (University of Basel)UNIGE Université de Genève (University of Geneva)

kWh kilowatt-hourGWh gigawatt-hour, 1 GWh = 106 kWhTWh terawatt-hour, 1v TWh = 109 kWhPJ peta-joule, 1 PJ = 0.277 TWh, 1 TWh = 3.6 PJ

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Table of ContentsImpressum ii

Executive Summary iii

Acronyms and Abbreviations v

1 Joining forces: the JASM Framework 11.1 Swiss Climate Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 The JASM Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3 Energy System Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.4 Sectoral Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.5 Harmonized Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2 JASM Scenario Definition 52.1 Climate Policy Dimension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.2 Technology Dimension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.3 Market Integration Dimension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62.4 Scenario Variants and Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3 Sectoral Models in JASM: Key Results and Inputs to the JASM Framework 73.1 Impact of Climate Change on Hydropower Generation . . . . . . . . . . . . . . . . . . . . . . 73.2 Effect of Climate Change on Heating and Cooling Demand . . . . . . . . . . . . . . . . . . . . 73.3 Hourly Load Curves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.4 Energy Efficiency in Buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.5 Energy Efficiency in Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93.6 Photovoltaics Hosting Capacity of Distribution Grids . . . . . . . . . . . . . . . . . . . . . . . 9

4 Scenario Results from Energy System Models 114.1 STEM - Optimal Transition Pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114.2 System Adequacy Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164.3 SES-EPFL - Optimal Technology Mix under Uncertainty . . . . . . . . . . . . . . . . . . . . . 174.4 SES-ETH - Optimal Technology Mix under Uncertainty . . . . . . . . . . . . . . . . . . . . . . 194.5 Energy Hub Optimization Baden Nord . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

5 Conclusions 245.1 Annual Electricity Use and Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245.2 Energy Imports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255.3 Carbon Capture and Storage and the Role of Biomass . . . . . . . . . . . . . . . . . . . . . . 255.4 Hydrogen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255.5 Electro-Mobility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255.6 Efficiency Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255.7 System Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

6 Recommendations 28

References 30

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1 Joining forces: the JASM Framework

JASM is a joint activity of several modelling teams within the eight Swiss Competence Centers forEnergy Research (SCCER). The aim of JASM is to define and analyze scenarios for reaching net-zerogreenhouse gas (GHG) emissions in Switzerland by the middle of the century. The JASM frameworkconsists of energy-system and sectoral models using a consistent set of drivers and scenarios defini-tions. Whenever possible, we used the latest insights and results from the respective SCCER.

1.1 Swiss Climate Goals

In summer 2019, the Swiss Federal Council an-nounced its ambition to reduce Swiss greenhousegas (GHG) emissions to net-zero by 2050 (Swiss Fed-eral Council, 2019). This includes emissions fromthe energy system, agriculture, waste and LULUCF(land use, land-use change, and forestry). On 9thDecember 2020 Switzerland submitted its revised Na-tional Determined Contribution to the United Nations.However, the net-zero GHG emissions target – andthe question of whether part of the emissions can becompensated abroad – is still under discussion in thepolitical arena. Nevertheless, the objective of JASMwas to find options on how Switzerland can realize thisnet-zero GHG emissions target from the perspectiveof the energy system.

The Swiss CO2 emissions from the energy sector(fuel combustion for energy conversion, manufactur-ing, transport, commercial and residential sectors plusthe emissions from the calcination process in cementplants) amounted to 38.3 MtCO2 /a in 2015. The totalGHG emissions (including CH4, N2O and others) were47.9 MtCO2eq/a (BAFU, 2020). The largest contributionto the difference of 9.6 MtCO2eq/a is from agriculturewith 6 MtCO2eq/a. A recent report by the Swiss FederalOffice of the Environment estimates that by 2050 thenon-energy emissions that are difficult to avoid are2 MtCO2 /a for cement production and 4.8 MtCO2eq/a foragriculture/food production (BAFU, 2020). Therefore,we analyzed targets on energy-related CO2 emissionsbetween 0 MtCO2 /a (assuming some compensationabroad) and -6 MtCO2 /a (without any compensation).

1.2 The JASM Framework

Energy system models are the core of the JASMframework. They represent consider the interdepen-

dencies between supply and demand for the sectorselectricity, heat and transport (Section 1.3). Energysystem models are informed by the results of sectoralmodels that represent certain sectors in greater detail(Section 1.4). Examples are models of the residen-tial and the industrial sector, which give investmentcosts for energy efficiency measures, or hydrologicalmodels that estimate the impact of climate change onhydropower generation. In Figure 1 we map the JASMmodelling framework, data inputs, and the contribu-tions from each modelling group.

For both energy system and sectoral models, wedeveloped a set of harmonized assumptions (Sec-tion 1.5):

• drivers of energy use, i.e. population, economicgrowth, and climate

• resource availability (photovoltaics, wind, hy-dropower, and biomass)

• and technology characteristics (investment costs,conversion efficiency, etc.)

We calculated energy demand exogenously frommacro-economic drivers. Here we made the simpli-fying assumption that the end-use demand (i.e. theuseful or energy service demand) is not elastic to en-ergy prices, i.e. it does not react to changing prices.In a second step, we determined endogenously theoptimal renovation levels needed to reduce these de-mands by applying energy efficiency cost curves forthe residential and industrial sectors (Section 3.4). Inthis step the energy-system models determine the op-timal level of investment on renovation measures andthe corresponding demand reduction.

Using the JASM framework, we evaluated scenar-ios that are defined along different policy dimensionsincluding technology availability, market integration,and climate policy (Section 2).

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Hydropower

Impact climatechange (UniBasel)

Solar potential

Wind potential

Biomass(Guidati et al., 2021a)

Imports of gas, oil,biofuels and hydrogen

(3) Resources(Marcucci et al.,

2021b, Chapter 3)

Conversiontechnologies

HydropowerSolar PV

WindGeothermal

CCGT

.

ElectrolysisReforming

Electricity

Biomass

Hydrogen

Storage

ElectricityHeat

HydrogenGas

Imports

Natural gasOil

ElectricityHydrogen

Electricity

Naturalgas

Liquids

Hydrogen

Demandtechnologies

BoilerSolar

thermalHeat pump

Elec. heaterGeothermal

GasolineDiesel

Natural GasHybridElectric

HydrogenTrolleyTrain

Heat

Mobility

Commercialand residential

Industry

(5) Energyefficiency(Zuberi etal., 2020)

Electricity demand

Space heat:buildings

(5) Retrofitting(Streicher

et al., 2020a))

Space heat:commercial

and industrial

Hot water

Process heat

(5) Energyefficiency(Zuberi etal., 2020)

Heat demand

Heat

Passenger

Freight

Mobility demand

(1) Energy System ModelsSTEM (PSI) - SES (EPFL) - SES (ETH)

Marcucci et al.(2021b, Chapter 4)

Technologycharacteristics

Available technologies

Market integration:Electricity imports

(UniBasel)

Climate policy

(6) JASM scenarios(Policy dimensions,

Marcucci et al.(2021b, Section

1.7))

Climate change

1980 2000 2020 2040 2060 2080 2100−2

0

2

4

6

8

Tem

per

atu

re(d

egre

es)

RCP2.6

RCP4.5

RCP8.5

(CH2018, 2018)

Heating andcooling de-gree days

Population

2000 2020 2040 20607

8

9

10

11

12

Po

pula

tion

(M

illio

n)

GDP

2000 2020 2040 2060400

600

800

1000

1200

1400

GD

P (

Bill

ion C

HF

)

Building stock

2000 2020 2040 2060400

500

600

700

800

ER

A (

Mm

2)

(2) Drivers (Marcucci et al., 2021b, Chapter 2)

Electricity loadcurves (Yilmaz

et al., 2020)

Electricity:Lighting, cooling,cooking, appli-ances, motors

Space heatdemand load

curves (Yilmazet al., 2020)

Space heat

Hot water

Process heat

Mobility

2000 2020 2040 20600

50

100

150

200

Passenger

(Bpkm

)

(ARE (2016))

(4) Demands

Energy production bytechnology and time

Final energy useby sector and time

End-use technolo-gies: cars, heating

Energy effi-ciency measures

System costs Emissions

System adequacy -transmission (Schlecht

and Weigt, 2020)

System adequacy -distribution (Gupta

et al., 2020)

Baden case study(Bollinger, 2020)

Impacts for thesociety and the

economy (Lordan-Perret et al., 2021)

Outputs (7) Analysis

EPFL–IPESE EPFL-DESL ETH Zurich EMPA PSI Unibasel U. Geneva Biosweet

Figure 1: The JASM framework.

1.3 Energy System Models

The JASM framework has 3 energy system models:

1. Swiss TIMES Energy system Model (STEM, PSI)(Panos et al., 2019; Kannan and Turton, 2014),

2. Swiss Energy Scope (SES) from EPFL (Moret,

2017)3. and ETHZ (Marcucci et al., 2021a).

STEM models the transition pathways in the2020–2050 time horizon, combining long-term invest-ment decisions with short-term operational constraints,

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and includes a significant level of technical details. TheSES models are snapshot models, i.e. they provideresults for one single year in the future (e.g. 2050)with a simpler representation of the energy system.We use the SES models to do uncertainty analyseswith a large number of scenarios.

We intentionally use models with different capabili-ties in order to evaluate stable, large structural trendsin technology deployment, that allow us to formulate arobust narrative of the future Swiss energy system.

1.4 Sectoral Models

The sectoral models in the JASM framework allowus to model in detail important aspects of the energysystem:

Impact of climate change on hydropowerproduction: Using Swissmod from the University ofBasel (UNIBAS), we determined the effect of climatechange on the inflow to hydropower plants for thelatest representative concentration pathways (RCP2.6, 4.5, 8.5) of the Swiss climate scenarios (CH2018,2018) (Section 3.1). This work was aligned withresearchers from SCCER-SoE.

Impact of climate change on heating and cool-ing demand: Berger and Worlitschek (2019), fromthe Lucerne University of Applied Sciences and Arts(HSLU), calculated the future heating degree days(HDD) and cooling degree days (CDD) for the threeclimate scenarios in CH2018 (2018) (Section 3.2).

Hourly load curves: Our energy system modelsneed the hourly demand profile for energy services (inthe residential, commercial, industrial and transportsectors) as input. In our JASM framework, the SwissFederal Laboratories for Materials Science and Tech-nology (EMPA), University of Geneva (UNIGE), andEastern Switzerland University of Applied Sciences(HSR Rapperswil) (Yilmaz et al., 2020) estimatedthese hourly profiles for different sectors and weatherconditions (Section 3.3).

Energy efficiency: We model the reduction ofthe energy demand from gains in energy efficiencybased on the energy efficiency curves from UNIGEand EMPA (Sections 3.4 and 3.5). We use energy effi-ciency curves as inputs into our energy system modelsto relate potential energy savings with their cost forthe industry (Zuberi et al., 2020) and the buildingsin the residential and commercial sectors (Streicher

et al., 2020a). This work was closely related to theSCCER Future Energy Efficient Buildings & Districts(SCCER-FEEB&D) and SCCER Efficiency of Indus-trial Processes (SCCER-EIP).

1.5 Harmonized Assumptions

An important value added by JASM is the factthat we harmonized our assumptions concerningmacro-economic drivers, resources and energydemands (Marcucci et al., 2021b) (available athttps://data.sccer-jasm.ch).

Macro-economic drivers: The JASM drivers arefactors that affect energy-use but are not sensitive todomestic policies or changes in individual behavior:population, economic growth, global climate change,and technology characteristics. In the JASM frame-work, we define variants for the drivers to capture therange of possible futures for Switzerland: three vari-ants (reference, high and low) for population, GDP,energy reference area, and three variants for globalclimate change developments (RCP 2.6, 4.5 and 8.5,based on the CH2018 (2018) climate scenarios) (Mar-cucci et al., 2021b, Chapter 2).

From a STEM analysis of these variants, we obtaindistinct, deterministic pathways resulting from thecombinations of these variants – a sensitivity analysisof the drivers on the results. The SES models insteadmodel these variants as uncertain parameters withparticular probability distributions, and conduct anuncertainty analysis with a Montecarlo samplingmethod.

Resources: In addition to the common drivers,we also harmonized assumptions concerning theavailability of domestic resources, including hy-dropower, solar photovoltaics, wind, biomass, and theprices of imported fuels (i.e., gas, oil, biofuels andhydrogen). Whenever available, the latest insightsfrom the respective SCCERs are used (Marcucciet al., 2021b, Chapter 3). This was especially thecase for the SCCER Biomass for Swiss Energy Future(SCCER-BIOSWEET) on biomass resources, as wellas SCCER-SoE for hydropower and domestic CO2

storage potentials.

Technologies: The assumptions of costs andefficiencies for key energy supply and demandtechnologies have been also harmonized. The mainsources used are Bauer et al. (2019) and Baueret al. (2017) for electricity generation technologies,

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https://data.sccer-jasm.ch


Christensen (2020) for electrolysis, IEA (2019) forhydrogen production technologies, Radov et al.(2009) for end-use boilers and heat pumps, andthe SCCER Efficient Technologies and Systems forMobility (SCCER Mobility) for the transport tech-nologies (Sacchi et al., 2021). The characterizationof the biomass-related technologies in the energyconversion sectors, as well as the identification of thevarious biomass conversion routes considered in thecontext of JASM, are based on the collaboration withthe SCCER-BIOSWEET as it is described in Guidatiet al. (2021a).

Energy demands: We calculate the future energyservice demands in the different end-use sectors witha reduced-form econometric model based on the har-monized drivers (Panos et al., 2021; Marcucci et al.,2021a):

• Space heat demand in the residential sector isrelated to the future energy reference area (ERA)that we estimated using population as the maindriver. To calculate the ERA, we project the evo-lution of the building stock until 2060 by buildingtype and age group following a building stockmodel. We then determined the heating demandusing the estimations from UNIGE regarding thespecific heating demand per building type and

age, as well as the new building standards (Mar-cucci et al., 2021b).

• Space heat demand in the industrial and com-mercial sectors is also related to ERA, which isassumed to be linked to GDP, GVA and produc-tion index.

• Warm water and electricity demand in the residen-tial sector is linked to population, while it followsthe development of GDP, GVA and productionindex for industrial and commercial sectors.

• Process heat demand in industry is linked to eco-nomic development (GDP or GVA) and to physicaloutput (i.e. production index).

• Finally, the future demand of transport (person-and ton-kilometer) is based on the Transport Out-look 2040 (ARE, 2016). We used the historicaldata from the BFS (2019b), BFS (2019c), andBFS (2019a) and the ARE (2016) growth ratesof passenger demand per capita and freight de-mand per GDP. We then determined the demandsusing the JASM reference, high, and low variantsof population and GDP. For the projections after2040, we assumed a decreasing growth rate inthe demand per capita and the demand per GDPfor the passenger and freight demand, respec-tively.

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2 JASM Scenario Definition

The JASM scenarios are defined along dimensions on which citizens and policymakers can exertinfluence, including climate policy, technology development and market integration. Studying a largevariety of scenarios within our JASM framework allows us to distill those trends on technology usethat are stable and, therefore, most likely part of a future energy system.

The STEM and SES models evaluate scenariosdefined along three dimensions:

1. climate policy,2. available technologies,3. and market integration (with the EU or within

Switzerland).

We selected these dimensions firstly because eachdirectly influences energy-use or energy generationand secondly because each dimension is a lever onwhich citizens and policymakers can exert influenceto achieve net-zero emissions in Switzerland. As men-tioned in Section 1.5, we considered other externaldrivers, that can not be influenced – population andGDP, global climate change, and technology charac-teristics – in combination with these three dimensions.

As explained in Section 1.3, the energy system mod-els are very different in structure and scope. Therefore,the translation of these scenario dimensions into con-crete inputs is very model-specific, and explained inthe different reports (Panos et al., 2021; Li et al., 2020;Marcucci et al., 2021a; Guidati et al., 2021b).

2.1 Climate Policy Dimension

In the climate policy dimension, we explored climatechange mitigation targets, ranging from existing poli-cies to the more ambitious net-zero CO2 targets estab-lished by the Swiss Government. In 2015, Switzerlandannounced a long-term target of reducing GHGs by70–85 % in 2050 compared to 1990 levels (Swiss Fed-eral Council, 2015). Later, in August 2019, the FederalCouncil decided that Switzerland should reduce itsGHG emissions to net-zero by 2050 (Swiss FederalCouncil, 2019), and an updated NDC (Nationally De-termined Contribution) was submitted on 9 December2020 to the United Nations (UN). In both cases, thetarget states that part of the reduction can be achievedby measures abroad.

We therefore considered three climate policy trajec-tories/targets:

1. Business as Usual (BAU)2. Energy Policy (EPOL)3. Climate Policy (CLI)

In BAU, we assume that all policies in place todaywill continue are their current stringency. In EPOL,we adopt the multiple objectives and measures of theSwiss Energy Strategy 2050 without a specific CO2

target. Applied to the JASM framework, the EPOLscenario is exploratory and BAU is used to compareand benchmark the developments and to showcaseupcoming challenges in long-term scenarios relatedto the energy system transition. Both BAU and EPOLare analyzed by STEM only.

The last climate policy in our JASM scenarios isthe ambitious objective of reaching net-zero emissions("CLI"). As explained in Section 1.1, unavoidable emis-sions in agriculture and industry require either a com-pensation outside Switzerland or the net removal ofCO2 from the atmosphere within the energy system.CLI was analyzed as a normative scenarios by STEMand SES-EPFL with a target of 0 and -6 MtCO2 /a insidethe energy system, respectively, whereas SES-ETHused a sweep of CO2 targets from +20 MtCO2 /a to thelowest value that can be achieved for the given as-sumptions.

2.2 Technology Dimension

Along this dimension, we assume different states oftechnology availability due to both technology devel-opment and public acceptance. Starting from a statein line with current technology availability (conserva-tive) to a final state that assumes accelerated technol-ogy development, increased social acceptance, andgreater infrastructure investments (progressive).

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At the conservative starting point, we assume cur-rent technologies are available at currently estimatedpotentials and costs but that no significant changesto existing infrastructure or expanded public accep-tance occur. In contrast, in the final progressive op-tion, we include a larger set of technologies availablein Switzerland at competitive prices due to technologi-cal breakthroughs and or increased acceptance.

2.3 Market Integration Dimension

Integrating into the European energy market is cur-rently a topic of intense debate for consumers, policy-makers, and market actors. The level of integrationthat Switzerland decides on will have important impli-cations for energy prices and "energy independence".

In our scenarios, moderate integration mirrors thecurrent situation: balancing electricity imports and ex-ports during the year without an electricity agreementand importing fossil fuels with limited access to interna-tional markets for biofuels, synthetic e-fuels, hydrogen,or captured carbon. High integration assumes thatthere is an electricity agreement between Switzerlandand the EU (as a result, the transmission capacity canbe fully used), and an international market of biofuels,hydrogen, and captured carbon.

We model this dimension by changing the net trans-fer capacities and imports prices of electricity, as well

as of other imported energy carriers. The STEM modelis able to model consumers in great detail, thus, forSTEM, this dimension also models "internal" integra-tion within Switzerland. That is, prosumers participat-ing in energy sales, both residential and commercial,forming also local energy markets. Thus, STEM canestimate the influence of these more progressive mar-ket developments that influence market integration ofrenewables, distributed generation, and sector cou-pling.

2.4 Scenario Variants and Synthesis

Each energy system model generated extra scenariovariants to better work out the effects of certain key pa-rameters on the resulting mix of technologies. Theseare described in detail in the respective reports and inSection 4.

Based on the individual model results, we identifiedthe trends that are common to all three models. Thiscomparison allowed us to identify technologies thatare very likely part of the future mix and the ones thatmost likely will not play a role (see Section 5). Basedon these insights we are able to formulate specificrecommendations for policy measures and actionstoday; and to define the market drivers and the engi-neering and technical changes necessary to integratetechnologies together to transform the energy systemwhile achieving climate commitments.

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3 Sectoral Models in JASM: Key Results and Inputsto the JASM Framework

Full energy system models have a representation of the whole energy system, and are naturally limitedin their capabilities to model the specific sectoral details. On the contrary, sectoral models focus oncertain key aspects but do not include linkages with the rest of the energy sector. In JASM, we soft-linked sectoral and energy-system models. In this section we present selected outputs that are furtherused in the energy-system models.

Climate change will impact the future hydropowergeneration heating and cooling demand. We basethis assessment on the latest Swiss climate scenarioswhich were generated for the Representative Con-centration Pathways RCP 2.6, 4.5 and 8.5 (CH2018,2018).

3.1 Impact of Climate Change on Hy-dropower Generation

To determine the effect of climate change on the in-flow to hydropower plants, we used discharge datafrom hydrologic modelling and passed it to the Swiss-mod model of UNIBAS (Schlecht and Weigt, 2014/04),which represents 96 % of Swiss hydropower stations.The hydrology dataset was generated by the hy-drologic precipitation-runoff-evapotranspiration modelPREVAH (Viviroli et al., 2009). It includes data from 39climate model chains and comes at a 500 m x 500 mspatial resolution (Brunner et al., 2019).

To calculate inflows to hydropower stations, we firstmapped the raster data to the Federal Office for the En-vironment (FOEN)’s catchment area GIS dataset. Asa second step, we used the Swissmod GIS databaseof catchment areas to map inflow to individual hy-dropower cascades. Subsequently, we calculated in-flows based on historical production patterns and cal-ibrated historical annual inflows to match expectedtotal yearly hydropower production of individual hy-dropower stations. Savelsberg et al. (2018) describesthe data processing approach in more detail.

The resulting monthly inflow patterns are visual-ized in Figure 2 in energy units (available at https://data.sccer-jasm.ch/climate_hydro_inflows/). Theyrepresent the sum of inflows to run-of-river powerplants and to storage lakes. The latter is turned into

actual production by the regulated hydro power plants.Especially in the RCP 8.5 scenario, clear trends canbe observed, with a decline of total inflow but also ashift from summer to winter. The RCP 2.6 and 4.5scenarios show similar changes, yet to a smaller ex-tent. These monthly patterns are directly used by theenergy system models with the RCP scenario as aparameter of an external driver.

3.2 Effect of Climate Change on Heating andCooling Demand

To determine the impact of the climate on the heat-ing demand we used the simple but widely knownapproach of Heating Degree Days (HDD), using themost common definition HDD 20/12. For every day atwhich the average temperature is below the heatinglimit Tl = 12 ◦C we computed the difference of thattemperature to an assumed building interior temper-ature Ti = 20 ◦C. Similarly, we determined the effecton the cooling demand by considering the changes ofcooling degree days (CDD), which are the number ofdegrees that a day’s average temperature is above acertain threshold (Tmax = 18.3 ◦C).

Berger and Worlitschek (2019) calculated the fu-ture HDDs and CDDs for the three aforementionedclimate scenarios (CH2018, 2018) using a GIS-basedapproach combining the spatial distribution of temper-ature (and therefore HDDs) and population. Figure 3presents the median and the first and third quartilesof the HDD (available at https://data.sccer-jasm.ch/climate-data/). All full energy system models in JASMconsidered the impact of changing HDD on the heat-ing demand, whereas only STEM modelled also theimpact on cooling demand.

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J F M A M J J A S O N D0

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Figure 2: Inflows to hydropower plants (run-of-river and storage lakes) under different RCPs and climaticperiods.

1980 2000 2020 2040 2060 2080 21002000

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Figure 3: Population weighted heating degree daysin RCP 8.5, RCP 4.5 and RCP 2.6.

3.3 Hourly Load Curves

Our energy system models have as an input the hourlydemand series for energy services (in the residential,commercial, industrial and transport sectors). In ourJASM framework, EMPA, the UNIGE, and HSR Rap-perswil (Yilmaz et al., 2020) estimated these hourlyprofiles for different sectors and weather conditions.UNIGE collaborated with the local utility company Ser-vice Industriels de Genève (SIG) and developed theElectroWhat platform that decomposes the yearly elec-tricity consumption of every Swiss municipality intoestimated load curves per activity and per electricappliance. EMPA used different simulations with theCESAR model to calculate the hourly profiles for com-mercial and residential buildings for today’s buildingstock and future buildings with different retrofitting lev-els. HSR Rapperswil estimated the load curves forthe space heating demand of single and multi-familyhouses using the TRNSYS model.

3.4 Energy Efficiency in Buildings

The insulation level of walls, windows and other partsof the building envelope changes the energy efficiencyof the building. For this reason, renovations are par-ticularly important in the residential and commercialsectors.

Residential sector. Streicher et al. (2020a) de-termined a relationship between energy savings andinvestment costs for the residential building stock us-ing two different models. First, Streicher et al. (2020b)used the SwissRes model to calculate the investmentcosts of the renovation packages for the 2016 buildingstock using three different approaches. The first ap-proach (full) includes all investment costs (related andnot-related to energy efficiency improvements). Thesecond approach (depreciation) accounts for the costsof the energy efficiency improvements plus a residualvalue to each building element. The third approach(improvement) accounts only for the cost of energy ef-

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Figure 4: Energy efficiency cost curves for the Swissresidential sector.

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Figure 5: Energy efficiency cost curve for the Swisscommercial sector.

ficiency improvements. SwissRes looks at retrofittingpackages as opposed to single measures as packageretrofitting is an optimal way to realize efficiency gainsand costs savings. That is, retrofit packages containcomplementary measures. Second, EMPA used theCESAR model (Murray et al., 2020) to calculate an-nual heating energy savings and the investment costsassociated with different retrofit scenarios for a set ofresidential building archetypes in Switzerland.

Figure 4 compares the resulting energy ef-ficiency investment curves for the CESARmodel and the scenarios of the SwissRes sim-ulations (available at https://data.sccer-jasm.ch/energy-efficiency-residential-swissres/ andhttps://data.sccer-jasm.ch/retrofit-savings-cesar/).The costs with the CESAR model correspond tothe Full cost approach of the calculation with theSwissRes model. Both models find similar totalsaving potentials of around 25 TWh for the currentresidential building stock with investment costs ofaround 100–200 Billion CHF, depending on themethod of economic evaluation. Note, that the effectof building retrofits on the future cooling demand wasnot considered.

Commercial sector. For the commercial sector,the CESAR model was used to calculate the savingpotentials and the corresponding investment costs forhospitals, offices, schools and shops including ninearchetypes for each building type (Streicher et al.,2020a). The buildings covered by these archetypes ac-count for 66 % of the total ERA in 2013, the remainingERA corresponds to restaurants, hotels, agriculturebuildings, transport buildings and other commercialbuildings. To get the energy efficiency curve for thewhole commercial sector we first upscaled, for each

building type, the estimation from the nine archetypesto the full building stock. Second, we assumed thatthe missing building types have savings potentialsper area (in kWh/m2) and investment costs per en-ergy saved (in CHF/kWh) that correspond to the av-erage of the rest of the buildings. Finally, we addedthe temporarily used buildings assuming a distribu-tion into age classes that corresponds to that in theresidential sector. Figure 5 depicts the energy effi-ciency curve (available at https://data.sccer-jasm.ch/retrofit-savings-cesar/). The total saving for today’scommercial sector are around 7 TWh with total invest-ment costs of 50–60 Billion CHF.

The results of both the CESAR and the SwissResmodel show that an energy retrofit of the buildings inboth the residential and the commercial sectors couldachieve a reduction of roughly 50 % (32 TWh/a) of thetotal final energy demand of space heating. Note, thatthis saving assumes constant climate, reductions dueto climate change are considered separately in themodels (see Section 3.2).

3.5 Energy Efficiency in Industry

Zuberi et al. (2020) (based on Zuberi and Patel (2019),Zuberi et al. (2018), Zuberi et al. (2017), Zuberi andPatel (2017), Bhadbhade et al. (2019), and Bhadb-hade and Patel (2020)) calculated energy potentialsavings and costs for various industrial sectors inSwitzerland. The estimation is done using techno-economic data on energy efficiency measures frommultiple sources which mainly include the EnergyAgency of the Swiss Private Sector (EnAW), theProKilowatt scheme by Swiss Federal Office of En-ergy (SFOE) and individual companies. The analy-sis considered the four most energy consuming sec-tors and systems, i.e. chemicals and pharmaceuti-cals, food and beverages, cement, metals, and pro-cess heat and electric motor driven systems. Pro-cess heating and electric motor systems correspondto approx. 50 % and 30 % of the Swiss industrial finalenergy demand. Figure 6 presents the energy effi-ciency curves for heat and electricity (available at https://data.sccer-jasm.ch/energy-efficiency-industry/).

3.6 Photovoltaics Hosting Capacity of Distri-bution Grids

Our scenario results indicate that photovoltaics (PV) isindeed a crucial element of the future electricity gen-eration mix (see Section 4). However, the majorityof small- and commercial-scale PV plants will likely

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Figure 6: Energy efficiency cost curve for the Swissindustry.

be connected to electrical distribution grids, whichwere not designed to host a significant power gen-eration. Modeling the existing electrical distributioninfrastructure’s technical constraints is, therefore, criti-cal to ensure the feasibility and economic viability ofthe overall net-zero scenarios. One dedicated sectoralmodel was developed at EPFL to address this issue(Gupta et al., 2020).

Estimating the PV generation hosting capacity ofexisting electrical distribution grids requires the infor-mation on network topologies and line parameters ofthe distribution systems for Switzerland. As this data isnot publicly available, we first inferred a country-widemodel of the medium-voltage distribution networksbased on spatially distributed information of the elec-trical demand, leveraging information freely availablefrom the Federal Office of Topography (swisstopo),land-use constraints, location of the extra-high-voltagenodes, and distributed solar irradiance potential.

We then estimated the PV generation hosting capac-ity for all Switzerland with a state-of-the-art and com-putationally tractable method based on a linearizedoptimal power flow. We ultimately investigated theeconomically optimal deployment of PV power plants

across Switzerland, including the placement and siz-ing of battery energy storage systems to increase thegeneration hosting capacity of those distribution gridswith significant solar radiation levels.

Thanks to the developed grid model, we could esti-mate that up to 15 GW of PV could be installed in theexisting grid infrastructure without the need of signif-icant upgrades of the electrical distribution grid. Wealso computed the amount of energy storage requiredto increase the PV generation capacity beyond thishosting capacity limit.

Figure 7 shows the energy capacity and power rat-ing requirements of battery storage as a function ofthe installed PV generation capacity. The need for stor-age increases approximately linearly beyond 15 GW.Assuming a final target in the order of 25 GW, whichis found in our scenario results, Switzerland wouldneed some 50–60 GWh of installed battery capacity.At prices of approx. 400 CHF/kWh this would result inextra investments of 20–25 BCHF, which is a similarrange as the investment costs of the PV generationitself.

Figure 7: Battery Energy Storage System (BESS)power rating and energy capacity for different levels ofinstalled PV generation capacity.

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4 Scenario Results from Energy System Models

The full scenario models STEM, SES-EPFL and SES-ETH have different characteristics that lead tointeresting and complementary results for the design of the energy system in a net-zero emissionsworld. STEM has the capability of analyzing the transition pathways while the SES models focus onthe impact of uncertainty on the design of the future energy systems. We also show results of aspecific case study for the city of Baden. In the following Section 5 we synthesize these results intocommon takeaways for the realization of the net-zero emissions target.

4.1 STEM - Optimal Transition Pathways

The Swiss TIMES Energy systems Model (STEM)(Panos et al., 2019; Kannan and Turton, 2014) has along-term horizon (2010–2100) with 288 intra-annualoperating hours (four seasons and three typical daysper season with 24 h resolution). It covers the wholeSwiss energy system with a broad suite of energy andemissions commodities, technologies and infrastruc-ture, from resource supply to energy conversion andusage in 17 energy demand (sub-) sectors. STEMaims to supply energy services at minimum overallsystem cost (more accurately at a minimum loss ofsurplus) by simultaneously making equipment invest-ment and operating, primary energy supply, and en-ergy trade decisions (Figure 8).

Three core scenarios are examined reflecting differ-ent transition pathways regarding energy and climatepolicies. All scenarios implement a gradual phase outof nuclear power plants, by considering a lifetime of 60years (with the exception of Mühleberg). The Baseline(BAU) scenario assumes a continuation of existingtrends in energy consumption and supply, as well asin the technology developments for energy production,distribution and use. It does not enforce specific long-term targets regarding renewables’ deployment, en-ergy efficiency measures or climate change mitigation.BAU is primarily used to compare and benchmark thedevelopments and showcase upcoming challenges inthe long-term scenarios related to the energy systemtransition.

The Energy Policy (EPOL) scenario considers themeasures and targets of the Swiss Energy Strategy(BFE, 2018). It implements both the targets on renew-able energy deployment and energy efficiency, includ-ing the indicative target in electricity consumption percapita, as defined in the Swiss Energy Strategy. While

EPOL does not impose a specific target in reducingemissions, it implements the new energy act on mo-bility. EPOL is an explorative scenario, evaluating thelevel of emissions abatement achieved primarily viathe energy efficiency measures described in the Swissenergy strategy.

The Net-Zero (CLI) scenario aims at achieving net-zero emissions in the energy system and industrial pro-cesses, i.e. within the scope of STEM1. Consideringemissions outside the energy system from agricultureand waste treatment (other than fuel combustion), theresulting CO2 emission level within the CLI scenariowill still be in the order of +5 to +6 MtCO2 /a. The CLIscenario implements emissions standards for build-ings and vehicles, and it assumes the strengtheningof the Swiss and EU emission trading schemes.

Besides the CLI core scenario, variants addressingkey dimensions of the energy transition, such as re-source availability, technical progress, and market inte-gration, are also assessed. The ANTI variant assumesa fragmented international climate policy, slow techni-cal progress, weak integration of energy markets, andlow exploitation of domestic renewable energy. TheSECUR variant builds on ANTI, but it assumes that theSwiss society is keener in fully exploiting the sustain-able potential of domestic renewable resources, to min-imize the import dependency.The MARKETS variant

1 Referring to the GHG inventory of Switzerland submittedto UNFCCC, the emissions within the scope of STEM arefrom 1A to 5A (i.e. emissions from fuel combustion in energysector, manufacturing, transport, services, agriculture andresidential) and 2 (i.e. non-energy related emissions fromindustrial processes including mineral industry, chemical industry,metal industry, non-energy products from fuels and solventuse and other manufacturing), see Sheet "Summary1.As1" inSwitzerland’s national GHG inventory reports which can bedownloaded from the Federal Office for the Environment (FOEN).

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https://www.bafu.admin.ch/bafu/en/home/topics/climate/state/data/climate-reporting/latest-ghg-inventory.html


assumes high access to domestic renewable energysources as in SECUR, and it also considers a higherintegration of the Swiss and international markets, be-yond the levels of CLI. The INNOV variant builds onMARKETS, and it also assumes globally coordinatedR&D spending to reduce the costs of low-carbon tech-nologies. The CLI100 variant does not implementthe efficiency and emissions standards/targets in thedemand sectors of CLI beyond 2030.

Finally, a variant of the EPOL scenario is also con-sidered in the analysis that enables higher electrifica-tion of the demand by not implementing the reductionin the electricity per capita indicated in the Swiss En-ergy Strategy (variant EPOL-E).

Figure 9 highlights important aspects of thetransition pathway towards net-zero within the energysystem with a focus on the CLI scenario.The fullSTEM report can be found in (Panos et al., 2021).The most important insights from STEM modelling are:

Achieving the Swiss energy and climate goalswould require scaling up clean energy technolo-gies. The ambition to reach the net-zero CO2 emis-sions objective by 2050 requires a radical transforma-tion of the way energy is supplied, transformed andused. It is necessary to deploy solar PV, electric andhydrogen cars, heat pumps, and energy savings mea-sures on a far greater scale and more rapidly thantoday.

In electricity supply, the installed capacity of solar

PV needs to double every decade from now to 2050.The electricity from solar PV is ten times higher in 2050than today. The contribution of non-hydro renewableenergy electricity in total supply increases to 45 % in2050, with much of this expansion occurring in thepost-2040 period.

The private car fleet will need to be mostly basedon electric drive trains by 2050, which implies that onein every three new car registrations must be electricalready by 2030s. In CLI, the period from now until2050 is divided into three principal stages:

a) the period until 2030 is characterized by a transi-tion with many options competing

b) the period 2030–2040 sees a rapid introductionof electric vehicles

c) the period 2040–2050 in which fuel cell cars gainshare in the market

In the public and freight road transport, the transi-tion is characterized by strong hybridization until 2040,while afterwards battery and fuel cell drivetrains be-come increasingly competitive and start gaining mar-ket share. The fuel mix in transport shifts away fromfossil fuels towards electricity, hydrogen, and zero-carbon fuels (mostly imported bioliquids or synthetice-fuels produced with renewable electricity and CO2

capture).The deployment of heat pumps needs to accelerate

in both services and residential sectors so that, by

Figure 8: Overview of the STEM model structure and concept.

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(a) Total final energy consumption by fuel in CLI (excl.international aviation and CHPs), PJ/a.

(b) Electricity supply mix in the CLI scenario, TWh/a.

(c) CO2 emissions from fuel combustion and indus-trial processes – on-site CHPs are accounted to theemissions from the end-use sectors (MtCO2 /a).

(d) Cumulative direct policy costs 2020–2050, dis-counted at 2.5 % social discount rate, BCHF2010.

Figure 9: STEM main results.

2050, heat pumps would cover close to three quartersof the space and water heating demand in buildings.It would also be necessary to reap efficiency gainsby rolling out energy-saving measures through ac-celerated renovation the deployment of which needsto start from now and increase in the post-2030 period.

Electricity – a key energy carrier in reachingnet-zero emissions. The total electricity consump-tion in the end-use sectors increases by 11 TWhin 2050 compared to 2019. There is acceleratedelectrification of the demand until 2030, driven byheat pumps and electric vehicles. However, in thepost-2030 period transport is the main driver of thecontinuing electrification of the demand, as efficiencygains and energy conservation measures lead to aplateauing of electricity consumption in stationarysectors. Electrification and efficiency improvements indemand enable a reduction of the total final energyconsumption per capita by 55 % in 2050 compared to2000 levels, slightly higher than the long-term targetof the Swiss Energy Strategy. It should be notedthat the overall electricity supply needs to increaseby around 20 TWh between 2019 and 2050, as asignificant amount of electricity is needed also toproduce hydrogen after 2040.

Electrification alone cannot decarbonize theentire energy system. Hydrogen penetrates theindustry and mobility sectors for applications wherethe direct use of electricity is challenging or associatedwith very high costs. In 2050 more than 10 TWh ofhydrogen are used, directly in fuel cells CHPs, fuelcell vehicles and hydrogen boilers, or indirectly viaconversion of hydrogen to synthetic fuels. The uptakeof hydrogen mainly accelerates in the post-2030period. Besides hydrogen, imported biofuels andsynthetic e-fuels of about 10 TWh are needed in 2050,which are used in the hard-to-electrify sectors oflong-distance public and freight road transport andheavy industry.

CO2 capture and bioenergy play an importantrole. Achieving the net-zero goal in a cost-efficientway would require capturing about 8.6 Mt CO2 in 2050from the energy system and industrial processes.About half of the captured emissions are fromnegative emissions technologies such as bioenergywith CO2 capture and direct air capture. Bioenergyconversion with CO2 capture can become vital not

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only for removing CO2 from the atmosphere but alsofor producing hydrogen, which is also directly used toreplace fossil fuels. Failing to harvest the remainingexploitable sustainable potential of bioenergy wouldentail high climate change mitigation costs. Moreover,given that storing captured CO2 in Switzerlandis a major challenge, the access to internationalCO2 transport and storage infrastructure would beessential to avoid a drastic increase in mitigation costs.

Achieving the net-zero goal is technicallyfeasible but requires coordinated efforts acrossall sectors. In 2050, the remaining emissions are inindustry and relate to processes that need gaseousand solid (such as waste) fuels. The penetrationof alternative vehicles, heat pumps and efficiencymeasures via renovation to fully decarbonize transportand buildings implies that more than two-thirds ofthe emissions reduction required to achieve thenet-zero emissions goal stem from technologiesthat are already commercially available or underdemonstration. However, to scale-up their deployment,energy companies and industry would need clearlong-term strategies. Transforming the entire energysystem will require progress across a wide rangeof technologies and action across all sectors, notjust electricity. Long-term policy targets need to bebacked up by detailed, clean energy technologystrategies that involve measures tailored to localinfrastructure and technology integration needs, andthat achieve high levels of social acceptance of thenew technologies.

Cost-efficient deep decarbonization needs allthe options to be on the table, including access tointernational energy markets. The cost of the transi-tion of the Swiss energy system to net-zero emissionsin 2050 depends on the resource availability, socialacceptance, technology progress, and the level of inte-gration of local, national and international markets. It isalso affected by the mitigation level already achieved inthe reference scenario, against which the policy cost iscalculated. The developments in the aforementionedfactors reveal a large cost range, which indicates theuncertainty range of the abatement effort.

The lowest mitigation cost occurs when decar-bonization can be achieved based on the availabil-ity of all possible least-cost mitigation options, andif research and innovation succeed in improving theperformance and reducing the costs of low-carbontechnologies. Under favourable conditions, the com-plete decarbonization of the energy system requires

cumulative system costs of 59 billion CHF2010 from2020 to 2050 discounted at a 2.5 % social discountrate (or, 97 billion CHF2010 undiscounted).

The highest mitigation costs occur when the tran-sition to a low-carbon economy faces fragmented na-tional and international policies, low level of cooper-ation and market integration, a low exploitation rateof renewable resources, slow technical progress andlimited social acceptance. In such an extreme case,the cost can be as high as 257 billion CHF2010 from2020 to 2050 discounted at 2.5 % discount rate (426billion CHF2010 undiscounted).

The core net-zero scenario evaluated in this study(CLI scenario) shows cumulative costs of 97 billionCHF2010 over the period of 2020–2050, discountedat 2.5 %, or 163 billion CHF2010 undiscounted. Thetransport sector has the lion’s share in the incrementalinvestment needs in CLI, with an additional cumulativediscounted investment expenditure of 46 billionCHF2010 when compared to BAU, due to the shiftto alternative drivetrains. In terms of average percapita cost per year, the policy cost in CLI translatesto 330 CHF2010/a discounted, or 540 CHF2010/aundiscounted from now until 2050. It should benoted that the per capita costs are averaged overthe investigated time horizon until 2050, which ischaracterized by a fundamental transformation ofthe energy system and new technology and fuelmixes. The associated annual policy costs increaseexponentially over the projection period, meaningthat by 2050 we have built a more expensive energysystem, which will require endured investmentsand expenditures for low carbon energy supply anddemand also beyond 2050.

The transition to net-zero entails both chal-lenges and opportunities in all sectors of theSwiss energy system. The analysis of the corescenarios and their variants shows that if energysavings and key technologies for the transition, accessto zero-carbon energy carriers and development of thecorresponding transport and distribution infrastructurefail to scale up, then the feasibility of reaching thenet-zero target would be challenged, or the targetwould only be achieved at higher costs. The aboveaffects each sector of the energy system.

In the building sector , the rate of renovation anddeployment of new efficient heating and electricalequipment needs to be significantly increased. Thesebuilding technologies need to support future fullrenewable energy supply through demand side

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management (DSM). Still, their current payback timesand the "split incentives" between landlords andtenants make investments financially unattractive. Toreap the benefits of the transition, targeted policieswould be needed to lift barriers related to financingor behaviour along with promoting the use of cuttingedge IT solutions to enable smart use of energy.

In industry , the required emission reduction arelinked not only to the use of Best Available Tech-nologies, but also to the development of low-carbonsolutions, including electrification, use of zero-carbonfuels, CO2 capture, and material efficiency. Tofacilitate the transition without jeopardising thecompetitiveness of the Swiss industry, roadmapsshould be developed in combination with newmarket designs that encourage consumption oflow-carbon intensity industrial products. The timelyreplacement of ageing infrastructure and assetswith alternatives that are more compatible with thedecarbonization targets can offer an opportunity toa cost-effective transition if investors receive suit-able long-term price signals from markets and policies.

In the mobility sector , the growing momentum forelectric vehicles needs to be amplified, until otherzero-carbon options, e.g. hydrogen fuel cells, becomeavailable on a larger scale towards mid-century. Biofu-els and synthetic e-fuels have the advantage in theirdirect use in conventional vehicles without alteringthe existing infrastructure. However, biofuels areassociated with land use and food security concerns.E-fuels require substantial amounts of electricityfor their production, while their life-cycle emissionsdepend on the source of carbon used. Therefore, thetransport modes where biofuels and synthetic e-fuelswould be deployed need to be carefully considered.Stronger integration of the mobility sector with the restof the energy system is also essential. For instance,grid-to-vehicle and vehicle-to-grid schemes can turnvehicles into multi-purpose assets that generate costsavings for owners and provide flexibility to the energysystem.

The domestic bioenergy potential needs tobe unlocked, and the infrastructure for bioenergydistribution needs to be further developed. Thedemand for bioenergy in 2050 is twice today’s levels,and it cannot be met by only using renewable waste,agricultural and wood residues. The exploitation ofthe sustainable potential of manure and forest woodwould need to be intensified. To unlock scale effects

in manure for biogas production, financial obstaclesneed to be overcome, and technical barriers to itscollection need to be lifted. At the same time, theavailability of wood largely depends on the intensityof forest wood management and a balance withnon-energetic uses of forests needs also to beachieved.

Hydrogen produced from low-carbon sourcesgains growing importance in a climate-neutral Swisseconomy in 2050. As such, strong climate policy is aprerequisite for hydrogen deployment. Besides, thefuture success and timing of a hydrogen economyare highly dependent on technological developmentsand targeted measures. The mid-term horizonuntil 2030/40 is crucial for the wider deployment ofhydrogen in the long term. As investment cycles inthe energy conversion sector run for about two tothree decades and the time needed for new energytechnologies to penetrate existing markets is long,stimulating commercial demand and supply of cleanhydrogen requires various forms of support. Duringthe transition phase of the hydrogen infrastructuredevelopment, policy support should prevent creatingstranded assets and discourage investments inhydrogen production technologies that do not meetlong-term environmental criteria.

The electricity supply shifts from demand-following to largely weather-driven production andfaces the need for additional system flexibility. Theelectricity market needs to open and create activeparticipation opportunities for centralised storage(including new solutions on Power-to-X, hydrogenand e-fuels), for flexible consumers (individual onesor those collectively offering their capacities throughaggregators) with decentralised storages and smartdemand technologies, and for electricity producerswho can be integrated via peer-to-peer trading. Theregulatory framework needed to support this majorchange in the electricity market structure will alsorequire stronger and closer cooperation acrossTransmission and Distribution System Operators(TSO) than today.

The district heating and cooling network op-erators also have an essential role in the energytransition because district heating systems provideflexibility for integrating different renewable energysources. By 2050 district heating systems largelyrely on a range of low- and zero-carbon options suchas solar, biomass, geothermal, and heat storages.

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This implies a transformation of the network itself,building on smart integration of energy systems andprosumers’ involvement. District heating networkswould need to be embedded in an overall plan acrossmultiple infrastructures (including electricity and gasgrids) with coordination between local authorities andservice providers, as well as alignment with otherinfrastructure developments.

Negative emission technologies are essential forthe transition towards a net-zero CO2 energy systemin order to offset the remaining emissions that aremost difficult to abate in transport, in industry and fromwaste management. If storing CO2 in Switzerland isuncertain or limited, Switzerland would need to obtainaccess to infrastructures transporting CO2 abroad,participate in establishing a consistent framework toaccount correctly for emission removals, and signinternational agreements for delivery contracts.

Overall, an affordable transition to decarboniza-tion is built around three main pillars. The first pillar isthe exploitation of the remaining sustainable domesticrenewable energy potential, including keeping hydroat least at the current level and securing access tothe sustainable bioenergy potential to deliver negativeemissions. The second pillar is the integration of en-ergy markets, especially those involving the tradingof new energy carriers such as hydrogen and syn-thetic fuels. The third pillar is technology innovationand R&D worldwide on low carbon technologies, to re-duce their costs and improve the overall performance.The transition to a low carbon energy economy canbe accelerated by technological progress and circulareconomy practices that reduce the cost of materials,renovation costs and costs of implementing energyconservation schemes.

4.2 System Adequacy Assessment

Transmission system adequacy is key for the function-ing of the future energy system. The Swissmod model(Schlecht and Weigt, 2014/04) was used to calculatedifferent adequacy indicators for some of the afore-mentioned scenarios analyzed by the STEM model(Schlecht and Weigt, 2020). For this purpose, PSIand UNIBAS soft-linked the two models by mappingtechnologies and translating the STEM results to thedifferent intra-annual timescale used in Swissmod.

Our analysis shows that Switzerland is wellequipped on the capacity side until 2040 and can

successfully manage the critical short-term situationsarising. Only very small loss of load can be observedin the CLI scenario for 2040, which considers alreadythe larger demand due to electro-mobility and elec-trolysis. A detailed analysis shows that this is dueto transmission grid constraints and likely in a rangethat could be managed by the TSO using short-termswitching actions or by allowing temporary violationsof the 20 % grid security margin that we consider in ourmodel. The adequacy assessment highlights the im-portance of European developments and thereby theimportance of both sufficient cross-border transmis-sion capacities as well as an integration of the Swissenergy system into the European market and systemstructure. While the existing and projected transmis-sion and generation capacities are large enough to en-sure system adequacy, the ongoing negotiations aboutthe electricity agreement between Switzerland and theEuropean Union (which has impacts on Switzerland’selectricity exchange possibilities with its neighbors)put the main focus of the Swiss system adequacy intothe political dimension and not the physical energydimension.

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Figure 11: Optimized power consumption in a -6 MtCO2 /a scenario.

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4.3 SES-EPFL - Optimal Technology Mix un-der Uncertainty

Swiss Energyscope (SES) was developed by IPESEat EPFL for exploring optimal investment and oper-ation strategies of the Swiss energy system in longterms subjected to various techno-environmental con-straints. The model is a snapshot of prospective sce-narios with monthly time resolution, resulting in a goodperformance of the trade-off between modeling con-tents, which include all key areas in the energy system,and computational complexity. Apart from conven-tional analysis on the energy demand-supply coveringelectricity, heat and mobility, special attention waspaid on the carbon flows contributing to modelling thecircular economy in the context of increasing advo-cacy for CCUS, especially for BECCS. Typical chem-icals/plastics are also considered in order to have amore holistic view on the whole system.

In this study, a normative scenario is defined aimingat realizing -6 MtCO2 /a emission autonomously in theenergy system in order to compensate unavoidableemission in non-energetic sectors, particularly agricul-ture (Li et al., 2020). The model demonstrates that car-bon neutrality is achievable with a quasi 100% penetra-tion of renewables except 5–10 % from non-biogenicwaste incineration, where domestic hydro, solar, windand biogenic resources are fully exploited (see Fig-ure 10). In total, 78 TWh/a electricity are producedwhere 37 TWh/a feeds the base load (including thegrid losses), and the remaining are consumed withinthe energy system, predominantly by heat pumps andelectric vehicles (see Figure 11).

Strong seasonality is witnessed in the power gener-ation, which has to be balanced by around 11 TWh/aof seasonal storage, where hydro storage in form ofthe alpine reservoirs contributes the largest part, withhydrogen and synthetic natural gas storage as majorbackups (see Figure 12). Mobility is highly electrifiedwith penetration rate around 90 %. In terms of heatdemand, waste CHP plants contribute the most (55 %)to the process heat supply, and decentralized heatpumps account for 56 % for space heating and hotwater supply.

Concerning the emissions, Figure 13 describes thecarbon flows quantitatively for both biogenic and non-biogenic sources/sinks within the energy system andexchanges with atmosphere and the underground.From the optimization results, around 0.8 MtCO2 /a are

used for generating synthetic fuels and plastics, wherethe latter serve as a carbon sink while the former cir-culate in the energy system. In total, 5 MtCO2 /a stemfrom fossil sources and 11 MtCO2 /a is sequestratedunderground, leading to +6 MtCO2 /a net bio-capture,demonstrating how the -6 MtCO2 /a emission target isachieved.

Subsequently, we performed a Monte Carlo simula-tion on the energy efficiency improvements (buildingrenovation, heat recovery and innovative process in-tegration in industry, and mobility electrification), keytechnologies’ potentials and importing prices of fu-els respectively, leading to various uncertainty rangesfor key technologies in the energy transition. Figure14 shows the multiple solutions towards the negativecarbon emission objective driven by efficiency uncer-tainties, with corresponding probability quantiles. Theresults illustrate that energy efficiency improvementswould result in considerable savings in the heatingdemand, reflected by the large variation of utilizationof heat pumps and geothermal.

Electrification is proved to be vital in realizing thecarbon neutral objective. The system cost presentslarge fluctuation in different scenarios. Biomass ismainly used for green fuel generation across the solu-tion space, despite some distinctions of specific con-figurations in different scenarios. Instead, PV, windand hydro power generation are robust against uncer-tainties that are supposed to be developed in priority.From our results, around 11 MtCO2 /a needs to be se-questrated, which calls for logistics to be planned fromnow on. Biomass-based plants, waste incineration andcement are the core areas to deploy carbon capturetechnologies. Pilot projects are necessary to further-more demonstrate the techno-economic feasibility ofthe solutions.

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Figure 13: Circular carbon flow (MtCO2 /a) in a complex energy system for achieving -6 MtCO2 /a.

Figure 14: Multiple-solutions towards carbon neutrality driven by the uncertainty of energy efficiencies.

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4.4 SES-ETH - Optimal Technology Mix un-der Uncertainty

The original Swiss Energyscope (SES) model (Moret,2017) was further developed at ETH, by including atypical day approach with hourly resolution, a moredetailed representation of residential and industrialheat consumption by defining a number of archetypes,and an explicit treatment of different CO2 streamsto better account for the effects of carbon storage(Marcucci et al., 2021a).

Most drivers that influence the future energy systemare uncertain. In our analysis we consider two cate-gories of uncertainty and treat them differently. Thefirst relates to levers on which citizens and policymak-ers can exert influence: the attitude – conservativevs. progressive – towards the deployment of noveltechnologies (e.g. deep geothermal heat, new alpinehydropower plants) and the integration with an EU-wide CO2 transport and storage infrastructure. Weuse these factors to define the dimensions of a fewdiscrete scenario variants (see Table 1). The uncer-tainty on the Swiss climate policy is considered bysimply sweeping through all possible CO2 targets from+20 MtCO2 /a down to the lowest achievable level.

Table 1: Discrete scenario variants of CLI in SES-ETH.

Technology developmentMarket integration Conservative Progressive

no CO2 storage Yesterday Revolution

with CO2 storage Come together Imagine

The second type of uncertainty includes factors thatare not sensitive to domestic policies or individualbehavior, including macro-economic drivers such aspopulation and GDP, global climate change, technol-ogy costs, and the availability and costs of resources.We analyze this uncertainty with continuous probabil-ity distributions using a Monte Carlo simulation. Withthis approach we obtain probability distributions for allresulting characteristics of the energy system, e.g. theamount of photovoltaic electricity generation. Theseresults reveal trends and inter-dependencies whichare more informative than point-estimates alone: wecan identify the developments in the energy systemthat are more or less fixed – that are common to allthe scenario results – and those that vary significantly.These types of insights are essential to inform deci-sion making, since they allow us to formulate robustrecommendations for actions in the fields of research& development, pilot & demonstration and policy mea-

sures.Figure 15 shows the probability distributions of the

stored CO2 emissions, the total electricity generation,and the generation with new renewables for the sce-nario variants against the energy-related carbon emis-sions. Results show the median (white dash), theinterquartile range (colored box) and the minimum andmaximum (the lines above and below the box). Therange of the net-zero GHG emissions target (-4 to-8 MtCO2 /a) is marked in grey.

First, concerning carbon captured, we can see thatthe target range for net-zero emissions (from -4 to-8 MtCO2 /a), can only be reached when CO2 captureand storage (CCS) is deployed. Without CCS, emis-sions from the energy system will stagnate at +6–8 MtCO2 /a which corresponds to a total GHG emissionsof +10–16 MtCO2 /a. Negative emissions are realizedwhen CO2 is captured from waste incineration plants(50 % is biogenic) and especially when wood is gasi-fied to hydrogen that is in turn used for freight mobilityor industrial process heat. In addition, CCS needs tobe applied to cement plants and possible gas turbinepower plants. The total amount of stored CO2 will bein the order of 15–20 MtCO2 /a.

Second, electricity generation and consumption in-creases compared to today’s levels, mainly due to theelectrification of the demand sectors heating and mo-bility. Besides hydropower, the main sources are newrenewables (mostly photovoltaics), and thermal powerplants. CCS needs to be applied on the latter if theyare fueled by fossil natural gas.

Figure 16a shows the time evolution of electricitygeneration and consumption for the Imagine scenariovariant at -6 MtCO2 /a emissions (representing a fullyear in 2050 with 24 typical days). PV generationpeaks in summer at noon. These peaks are absorbedby a number of technologies on the consumption side:

1. pumped hydro storage 1 shifts electricity fromday to night

2. heat pumps 1 generate domestic heat and storeit in short-term or seasonal thermal energy stor-age

3. industrial electric heaters 1 supply process heatto industry, again with the help of thermal energystorage

A further possibility that was not explicitly modelledis the smart charging of electric vehicles.

The top graph shows the level of the alpine stor-age reservoirs which is increased for the progressivetechnology scenario compared to today (see Table 1).This allows to shift more hydropower 1 from summer

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Figure 15: Selected results for the scenario variants.

to winter. The higher demand of electricity in winter issupplied by thermal power plants 1.

Figure 16b shows the supply and consumption ofheat, including space heating, hot water and indus-trial process heat. The dominant technology is heatpumps 1 followed by thermal installations (combus-tion and CHP) burning fossil fuels 1 or biomass andwaste 1. The peaks in the production side for heatpumps and electric process heaters 1 correspond tothe consumption side of electricity (Figure 16a).

Hence, the excess electricity generation (beyondthe demand) 1 is stored in short-term and seasonalthermal energy storage 1. In particular, seasonalthermal storage, helps balancing the electricity system

by avoiding extra demand from heat pumps in winter.Other sources of low temperature heat are solar- 1and geothermal 1 .

The full set of results can be found in Guidati et al.(2021b). The most important recommendations fromthe probabilistic assessment using the SES-ETHmodel are:

We need a CO2 capture, transport and storageinfrastructure. To reach the Swiss net-zero GHGemissions target, the energy sector (electricity, heat,mobility, including emissions from calcination incement plants) will need to reduce its CO2 emissionfrom 38.3 MtCO2 /a in 2015 to negative levels of-4 to -8 MtCO2 /a in 2050. This is only possibleby capturing and storing CO2 from the existing 6cement and 30 municipal waste incineration plants,from possible gas turbine combined cycles, andfrom wood gasification and natural gas reformingplants, that deliver hydrogen and CO2. Since partof the primary energy entering these plants isbiogenic in nature, this approach allows for negativeemissions that can compensate the unavoidableemissions. The total amount of stored CO2 will bearound 15–20 MtCO2 /a (around 1.5–2 tCO2 per capita).Since current studies show that Switzerland doesnot have sufficient domestic storage capacity, thecountry should actively contribute to the growth ofan European CO2 transport and storage infrastructure.

Biomass and hydrogen, two key elements of anet-zero strategy. Hydrogen plays a dual role in thefuture Swiss energy system. It allows to decarbonizethose parts of road transport that cannot be easilyelectrified (e.g. heavy duty freight transport), and itcan supply high temperature process heat to industry.At the same time, it can generate negative emissionsduring production, when using biomass as primaryenergy. This is the case for wood gasification andbiogas reforming, both coupled with CCS. Wood is animportant source of renewable energy and of biogenicCO2. Its potential is not fully exploited by burningit for the purpose of residential heating, instead, itshould be used to generate negative emissions, i.e.to extract CO2 from the atmosphere and to store inin the subsurface. This can be achieved by woodgasification to hydrogen or by wood power plantsequipped with CO2 separation.

We need new sources of primary energy. Deepgeothermal and solar thermal energy are valuableadditions to the energy system and should be devel-

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(a) Electricity production and consumption.

(b) Heat production and consumption.

Figure 16: Time evolution throughout a year in 2050using 24 typical days in the Imagine scenario variantfor a target of -6 MtCO2 /a.

oped for district heating, low temperature industrialprocesses and new processes such as the desorptionstep in CO2 separation.

Industrial process heat will have to completelyabandon the use of fossil oil and gas. For mediumtemperatures, geothermal and solar thermal is aninteresting option to be explored. If the sourcetemperature does not reach the level required forthe process, high temperature heat pumps shouldbe used. High temperature process heat can begenerated using hydrogen or waste. Direct electricalheating is an interesting option that can exploit thestrong photovoltaic generation in summer. It has to becoupled with thermal storage, either short-term (hoursto days) or even better seasonal.

Large scale seasonal thermal energy storagehelps to seasonally balance the energy system.Heat can be collected in summer with solar collectors,large scale heat pumps and industrial electric heatersthat use excess photovoltaic generation. Despite theissue of expensive land in Switzerland, well-developedseasonal storage options like open-pit storage shouldbe demonstrated with private and public partners.

Photovoltaic generation will have to grow bya factor of 10 compared to the levels of 2020. Aclose integration with the other demand sectors andthe use of storage will be needed to properly managethe daily to seasonal fluctuations of PV. Integrating PVin buildings during the design phase will be mandatory,this will require the development of standardizedproducts to be used by architects and civil engineers.

Efficiency measures and the electrification ofheating and mobility is a crucial step in any decar-bonization scenario. Heat pumps must become thestandard to deliver space heat and domestic hot water.Electro-mobility will have to supply the largest shareof mobility services, supported by hydrogen fuel cellvehicles. As a consequence, electricity consumptionwill increase to 70–90 TWh/a. Efficiency measures inthe residential sector and in industry is generally foundto be a cost effective means to reduce CO2 emissions.

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Figure 17: Location of the study site, Baden Nord, Switzerland.

4.5 Energy Hub Optimization Baden Nord

The results of the full energy system models give valu-able insights that must lead to action, however, manyof the specific measures – especially related to heat-ing – have to be adapted to the local circumstances.Within JASM, this step from national to local scale wasdone in an exemplary way for the city of Baden. Theaim was to identify optimal technological scenarios forthe area of Baden Nord (Figure 17), with a focus ontechnical feasibility and costs. This was achieved in atwo step approach:

1. Multi-energy demand modelling to estimate thefuture demand patterns for the area, and

2. energy hub optimization to identify a set of op-timal energy supply solutions for the given site,representing different levels of sustainability per-formance.

For the energy demand modelling, RegionalwerkeBaden (RWB) provided various datasets pertainingto the buildings and energy consumption in the studyarea. Hourly building energy demand profiles weresubsequently calculated using the urban energy simu-lation tool CESAR (Wang et al., 2018). In the energyhub optimization, a multi-energy supply system op-timization was carried out using Empa’s Ehub Tool(Bollinger and Dorer, 2017). Figure 18 shows the tech-nologies, resources and energy demands included inthe analysis. The optimization proceeded in 3 phases:

1. the aggregated analysis identified an optimal en-ergy supply options for the site as a whole, given

the full range of available options2. the sensitivity analysis determined the influence

of different uncertain developments on the futureoptimal energy supply solution for the site

3. the detailed analysis identified the optimal supplytechnology locations and thermal network struc-tures

The following conclusions were drawn from the re-sults of this analysis:

The least cost solution for meeting the heating de-mands of the site is with district heating (SiBaNo),complemented by air-source heat pumps and rooftopPV installations.

If district heating is not a feasible solution (e.g.due to lack of available heating energy in the wintermonths), the least cost solution for meeting heating de-mands is with a combination of technologies, includinga biomass boiler, gas CHP and oil boilers.

A 75 % reduction in operational CO2 emissions withrespect to the least cost solution can be achievedthrough a shift to heating supply primarily based ona biomass boiler. As in the least-cost solution, this iscomplemented by air-source heat pumps and rooftopPV installations. The resulting life-cycle costs arefound to be ca. 7 % higher in comparison with theleast cost solution.

Air-source chillers combined with groundwater-based freecooling is the most cost-effective and sus-tainable solution for meeting on-site cooling demands.If groundwater availability and temperature is sufficient,a purely groundwater-based (free)cooling solution isfound to be most efficient.

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Figure 18: Production & storage technologies and energy pathways considered in the analysis.

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5 Conclusions

Reaching net-zero greenhouse gas emissions in Switzerland is possible but it requires the combina-tion of complementary and relevant policy measures and actions today that will allow the transforma-tion of the energy system from different perspectives. In this section we present the policy recom-mendations derived from the common trends in the results from the energy-system models in JASM.

We used different energy system models to deter-mine how Switzerland can reduce its GHG emissionsto net-zero by 2050. This section presents a synthesisof selected results, highlighting the commonalities andexplaining the differences. We put a spotlight on elec-tricity generation, hydrogen production, the amount ofstored CO2, the total quantity of imported energy andthe use of electricity in the mobility sector. Additionaldetails can be found in the respective scenario reportsof the single models (see also Section 4).

As explained in Section 4.1, STEM modelled theCLI scenario C to determine a cost-optimal trajectoryfor 0 MtCO2 /a within the energy system in 2050. Inaddition, four variants of CLI were considered:

• Fragmented global policy (ANTI A ): This variantassumes an international context with low coop-eration in mitigating climate change, and limitedaccess to domestic renewable resources.

• Energy security (SECUR S ): This variant buildsupon ANTI, by assuming the same fragmentedclimate change policies worldwide but a Swisssociety that is keener in using domestic renew-able resources to reduce the carbon intensity ofthe Swiss economy and minimize import depen-dency.

• Market integration (MARKETS M ): This story-line has a higher global cooperation and integra-tion of the Swiss and international energy marketsbeyond the levels assumed in the core scenar-ios, while it also assumes increased access todomestic renewable resources.

• Technology innovation (INNOV I ): This variantbuilds upon MARKETS by considering the samedevelopments regarding the integration of energymarkets and by additionally assuming that thereis a global effort to mitigate climate change andachieve the Paris Agreements that also results

in increased research and development expendi-tures to improve the performance of renewableand low-carbon technologies.

The SES-EPFL model targeted at -6 MtCO2 /a, with avariation of input parameters as shown in Figure 14 1.SES-ETH developed a Monte Carlo variation of keyparameters for different variants on market integrationand technology development: Yesterday, Revolution,Come Together and Imagine (Table 1) and for a rangeof CO2 targets from 20 to -10 MtCO2 /a (only energy sys-tem). In this synthesis, we combined the two scenariovariants Imagine and Come Together with a variantof Imagine that allows for unlimited electricity importsat 100 CHF/MWh into a single probability distribution1. The figures on the next pages compare the resultsfrom the various models. We also added the 2015status at 38.4 MtCO2 /a as a reference A .

5.1 Annual Electricity Use and Generation

Electricity use will increase due to the electrificationof the transport and heating sectors. Using more ef-ficient appliances and processes is key but does notcompensate for the large increase driven by electricvehicles and heat pumps. Figure 19 (a) shows that thisincrease will be in the order of 10–20 TWh/a comparedto the 2015 level.

Concerning electricity generation, photovoltaics willbe the dominating new electricity source, contribut-ing some 15–35 TWh/a (see Figure 19 (b)). Despitethe significant role of new renewables (mostly photo-voltaics), the strong increase in electricity demand willalso require for thermal power generation and importsthat are especially needed in winter months. When-ever fossil fuels are used, carbon capture and storageis mandatory.

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5.2 Energy Imports

In 2015 Switzerland imported 74 % of its primaryenergy, mostly in the form of oil, nuclear fuels andnatural gas. All models find that the value of morethan 200 TWh/a will drop significantly to 30–50 TWh/a,which means an import share of 15–20 % in total pri-mary energy supply (see Figure 19 (c)).

Imports of oil and nuclear fuels disappear com-pletely by 2050. Natural gas stays at a lower levelthan today. The remaining imports are electricity andsynthetic fuels, either from biological sources or basedon hydrogen electrolysis with subsequent synthesisto hydrocarbons (e-fuels). The SECUR variant S re-sults in almost 0 % import dependency, but it requiresincreased deployment of domestic solar PV also forproducing synthetic e-fuels, which in all the rest ofscenarios and variants are imported. In summary,"simple" energy carriers as nuclear fuel or oil are re-placed by high-value carriers such as electricity orsynthetic fuels.

5.3 Carbon Capture and Storage and theRole of Biomass

All models find that reaching net-zero emissions re-quires carbon capture and storage of at least 9 MtCO2 /a(see Figure 19 (d)). Current studies show that this stor-age potential is not available in Switzerland (Diamond,2019). Therefore, we find it key to create a Swiss CO2

collection network and to link it to a European trans-port network that will transfer the captured carbon tostorage sites in the North Sea or elsewhere.

CO2 capture must be applied to waste incinerationand cement plants, and possibly to gas turbine powerplants. Additional negative emissions need to be gen-erated by using biomass technologies with carboncapture and storage, including wood gasification tohydrogen or synthetic natural gas, or combustion ofbiomass in power plants with tail end CO2 separation.All these technologies have been available for sometime, but were never at commercial scales. This willchange with the drive towards net-zero emissions.

5.4 Hydrogen

Despite a considerable scatter within the various mod-elling results, hydrogen is used by all models for non-electric transport (person and freight) and for powerand heat generation (see Figure 19 (e)). Differencesin the results concern the details of production. Theavailable technologies are electrolysis, gas reformingand wood gasification. These technologies appear indifferent proportions for the three models.

Wood gasification is the dominant technology forSES-ETH, it delivers also negative CO2 emissions.Gas reforming with CCS is also used, whereas elec-trolysis is absent from the mix.

Wood gasification is also present in SES-EPFL,however, not to produce hydrogen but synthetic nat-ural gas. This is driven by the assumption that CO2

can be captured at the tail-end of a combustion pro-cess, making negative emissions possible also withoutthe route via hydrogen. Consequently, the amount ofhydrogen for SES-EPFL is lower, and it is producedmostly through electrolysis.

STEM features a mix of all three technologies withelectrolysis accounting for approx. 50 %. STEM ana-lyzes the 0 MtCO2 /a, which given its lower stringencyrequires fewer negative emissions and, therefore, themodel results in lower levels of wood gasification.

The key takeaway is hydrogen will play a role in thefuture energy system, as an:

• energy source for transportation, power and heat;• to generate negative emissions through biomass

processing;• and as an option to use excess summer electricity

through electrolysis.

We recommend a broad approach of developingalternative hydrogen production technologies insteadof focusing on electrolysis only.

5.5 Electro-Mobility

Figure 19 (f) shows the amount of electricity usedfor the transport sector (passenger and freight). Thisvalue will increase considerably from today’s level andit will reach 15–20 TWh/a. Both the 2015 and the2050 numbers include also rail transport. The valuefor SES-EPFL is slightly lower than for SES-ETH sinceit allows for a larger share of electric public passengertransport that is more energy-efficient than batteryelectric vehicles.

5.6 Efficiency Measures

The results from the energy system models show thatretrofitting the buildings in both the residential andthe commercial sectors is cost-efficient. However, ac-cording to the findings in Streicher et al. (2020a), thecurrent budget allocated to retrofit subsidies, coversjust about 5–7 % of the total investment cost needed toobtain the energy savings potentials. Additional fund-ing programs to overcome the barrier of high upfront

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investment costs for energy retrofitting should be putin place to obtain the needed energy savings.

5.7 System Costs

All three models perform a cost optimization. There-fore, the additional costs that are related to a net-zeroscenario can be estimated, albeit with the caveat thatwe modelled an inelastic demand and did not con-sider the impact on the full economy via a ComputableGeneral Equilibrium (CGE) model.

The STEM model evaluated the extra costs of thenet-zero CLI scenario vs. the business as usual (BAU)scenario. The results show a cost of 97 billion CHF2010

over the period of 2020–2050, discounted at 2.5 % so-cial discount rate, or 163 billion CHF2010 undiscounted.In terms of average capita cost per year this translatesto 330 CHF2010/a discounted, or 540 CHF2010/a undis-counted. By considering the variants of CLI as well,the obtained range of the cumulative cost from STEM

from 2020 to 2050 is 59–257 billion CHF2010 cumula-tive discounted at 2.5 %, or 97–426 billion CHF2010 cu-mulative undiscounted. This translates to an averageper capita cost from 200–860 CHF2010/a discounted,or 330–1430 CHF2010/a undiscounted, over the pe-riod of 2020–2050. It should be noted that the percapita costs are averaged over the investigated timehorizon until 2050, which is characterized by a funda-mental transformation of the energy system and newtechnology and fuel mixes. The associated annualpolicy costs increase exponentially over the projectionperiod, meaning that by 2050 we have built a moreexpensive energy system, which will require enduredinvestments and expenditures for low carbon energysupply and demand also beyond 2050. The SES-ETHsnapshot model estimated the extra costs in 2050 vs.a scenario where no CO2 emissions reduction target isimposed to be 5–7 billion CHF2010/a which correspondto 500–700 CHF/a per capita.

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Figure 19: Results from energy system models; 2015 (38.4 MtCO2 /a) and in 2050 (0 and -6 MtCO2 /a).

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6 Recommendations

The JASM Framework brought together several energy modeling research teams, which can be seenas unique in its kind for Switzerland. The teams joined forces and expertise to define and analyzescenarios for reaching net-zero GHG emissions in Switzerland by 2050, in a highly comprehensiveway profiting from the combination of the wide spectrum of competences and experiences of the par-ticipating teams. The JASM framework proved the importance of cooperation and knowledge sharingamong Switzerland’s research community that increased the quality of the achieved results and pavedthe way for future work to overcome current limitations.

Expanding the framework beyond energysystems and sectoral models. The work in JASMwas primarily carried out using sectoral and bottom-upenergy systems models. These models are verydetailed in the representation of technologies, thedifferent energy sectors and their interdependencies.However, they are limited in capturing endogenouslybroader socioeconomic effects related, for example,to expenditures to human capital and education,reduced health impacts from air pollution, depletionof natural resources, broader economic and labormarket impacts, changes in the welfare, etc. More-over, the energy transition results in implicationsfor agriculture, as well as to forests, lakes andeco-systems. To account for the effects of theenergy transition and perform a rigorous cost-benefitanalysis of tackling climate change, the modellingtoolbox would need to be expanded in future workbeyond energy and techno-economic models andinclude macro- and socioeconomic models, aswell as models addressing non-energy sectors im-pacts such as related to agriculture, forests, water, etc.

Increasing the spatial resolution. JASM made amajor effort to incorporate spatially detailed modelling,for instance, related to modelling of buildings anddistribution grids. The analysis performed in JASMhighlighted the value of spatially disaggregatedanalyses aligned with national modeling. Neverthe-less, continued modeling efforts would be valuableto introduce higher spatial resolution modeling inseveral analytical tools. Besides capturing technicalconstraints related to the availability of the decar-bonization options, location and anchor zones, oraccess to resources, many of the key technologies

deployed to reach net-zero emissions require develop-ing (new) infrastructures and an efficient coordinationin policy planning between the State, Cantons andCommunities. Cost-optimal solutions found at nationallevels need to be concretized and validated at lowerscales, as the city-level case study within the JASMFramework showed. Increasing the spatial resolutionwould also provide a more accurate estimate on theinfrastructure deployment costs.

Assessing European and International energymarkets. One of the main findings in JASM is theneed for imported zero- and low-carbon energycarriers, such as electricity, hydrogen, biofuels andsynthetic e-fuels. These resources will be in highneed in the context of a globally coordinated effortto mitigate climate change, with implications in theiravailability and supply costs to Switzerland. TheJASM research team based the relevant scenarioassumptions on well-established European andinternational outlooks from the IEA and other sources.While this is a valid approach, it would be desirableto expand the Swiss-focused modelling framework toinclude European (and global) energy markets mod-elling to provide energy market boundary conditionsof Switzerland in an international context in a flexibleand fully harmonized setting. In a future continuationof a JASM-type framework, it would be beneficial toimprove consistency and increase the insights gainedfrom the analysis, including the assessment of theuncertainties related to changing international energymarket conditions.

Integrating social norms and consumer be-haviour . Social practices and norms, as well as

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consumer behaviour, have a significant influenceon technology choices and energy consumptionpatterns. The JASM research team tried to integratedifferent levels of social acceptance in the variantsand uncertainty analysis performed with the energysystems models. However, there was a need for astronger representation of the social and human factorin the analysis of the energy transition as key aspectsof it, e.g. rebound effects, social justice or efficientsocial management of costs, could not be fullyassessed. In future work, participation of researchersdealing with the social energy agenda could provideadditional and valuable insights on technology accep-tance, suitable policy measures, and more generallyon social impacts and benefits of the energy transition.

Improving data quality, especially for newtechnologies needed for decarbonization. TheJASM framework established a transparent dataplatform using peer-reviewed data regarding energysupply and demand technologies. Many of theessential technologies for decarbonization are todayeither at a lab-scale or at a demonstration phasewhich indicates significant uncertainties concerningtechnical performance and costs, which ultimatelystrongly affects the overall costs of energy transition.Continued research efforts are needed to improvethe data quality used in the modelling frameworks,focusing on critical options such as CCS, CO2 storagepotentials, storage, synthetic fuels and smart use ofenergy. Moreover, efficiency and energy conservationmeasures play a critical role in decarbonizing theenergy system. Within JASM a particular emphasiswas placed on renovation in residential buildings andenergy conservation in key industries.

Integrating international aviation. The JASMwork did not deal with the developments in interna-tional aviation as this sector is currently excluded fromthe national climate protection goals and falls underthe responsibility of ICAO (International Civil AviationOrganization) of the UN, which sets emissionsstandards and offsetting measures. In contrast,

domestic aviation is captured under the NDCs. Incase of the future inclusion of the international aviationto NDCs, the options to decarbonize the sector oroffset its emissions with negative emissions projectswould need to be assessed.

Emphasizing resilient energy systems. Sustain-able and resilient energy systems will be the keytopic in future analyses of deep decarbonizationpathways. While the JASM framework included anadequacy study, more research is needed addressingresilience by anticipating new energy uses and shiftingdemands. Also, more detail in addressing the securityof supply is required and across several dimensions,i.e. reliability of domestic infrastructure (partiallyaddressed in JASM) and diversification and availabilityof energy imports (which has not been performedin JASM). Adaptation measures were assessed toa limited extend in JASM via climate impacts onheating/cooling demands and hydropower availabilitythat required deployment of alternative measures andtechnologies from the models. Adaptation measurescould be on focus on the political agenda in the yearsto come and relevant to the topic of resilience andrecovery from a climate change shock.

Emphasizing sustainability in energy transition.The energy transition may potentially generate bene-fits within and beyond the energy system. Regardingsustainability, the JASM framework did not addressexternalities of the energy system related to impactson ecosystems and human health, resource depletionor accident risks. Thus, the implications of energy tran-sition on externalities were not accounted for in thequantification of costs; this should be included in thefuture holistic model-based analyses. Quantificationof external and total costs is a prerequisite for carryingout cost-benefit analysis while Multi-criteria DecisionAnalysis (MCDA) enables broader inclusion of socialaspects in sustainability assessment of technologiesand scenario-based pathways as well as accountingfor different stakeholder preferences when evaluatingsustainability.

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