The toolbox consists of seven different models, tools, or platforms that the project will use. A systematic overview describes the specifications (e.g. functions, coverage and resolution, inputs and outputs) as well as their current functions and planned extensions.

Calliope and Euro-Calliope work hand-in-hand. Calliope is an open-source tool for modelling high-resolution energy systems. Euro-Calliope is a set of data and workflows to build Calliope-based models of the European energy system.

Prof. Stefan Pfenninger (TU Delft)

  • Analytical approach: bottom-up
  • Purpose: scenario analysis and backcasting
  • Methodology: optimisation
  • Deterministic or stochastic: deterministic
  • Static or dynamic: dynamic
  • User interface: yes 
  • License: open source (Apache 2.0 license for Calliope, MIT for Euro-Calliope)
  • Developer(s): Imperial College London, University of Cambridge, ETH Zürich, TU Delft
  • Spatial coverage: all European countries
  • Temporal coverage: 2007-2016
  • Sector coverage: electricity, household and commercial heat, passenger and freight transport
  • Spatial resolution: the basic configurations are entire countries or 98 sub-country nodes (but other choices are possible)
  • Temporal resolution: hourly, with the ability to run at reduced resolution to reduce the computational effort


  • Regions/locations and possible transport/transmission connections [lines, nodes]
  • Energy service or energy carrier demand [GW]
  • Energy generation (e.g., wind, PV, hydropower) [GW]
  • Technology performance [GW]
  • Technology costs [CHF]
  • Policy constraints [emissions caps or renewable targets]



  • Technology capacities [GW]
  • Investment and variable costs [CHF]
  • Levelised costs [CHF]
  • Carbon emissions [tCO2]
  • Technology operation decisions
  • Energy transport and transmission decisions
  • Consumed resources
  • Capacity factors

Future development:
Use Calliope and Euro-Calliope to build custom models to assess pathways for Switzerland in the context of decisions taken across Europe.

Lunch talk: presentation (PDF, 2.1 MB) and presentation recording

Model website:

GitHub repository:
– Calliope:
– Euro-Calliope:

References: a selection of publications using Calliope is available at



CESAR-P (Combined Energy Simulation and Retrofitting) is a tool for modelling energy transformation scenarios to assess the current and future energy demands of buildings in districts.

Kristina Orehounig (Empa)

  • Analytical approach: bottom-up
  • Purpose: scenario analysis
  • Methodology: simulation (including building stock simulation)
  • Deterministic or stochastic: deterministic (and also Monte Carlo version)
  • Static or dynamic: dynamic
  • User interface: no
  • License: open source (AGPL)
  • Developer(s): Empa for CESAR-P and ETH Zurich for CESAR
  • Spatial coverage: Switzerland
  • Temporal coverage: annual (for multiple years possible)
  • Sector coverage: electricity, heating, cooling, domestic hot water
  • Spatial resolution: buildings, districts, cities and overall building stock
  • Temporal resolution: hourly
  • Passive and active retrofit scenario assessment
  • Indoor temperature assessment
  • Heating and cooling load assessment
  • Domestic hot water consumption assessment
  • Electricity consumption assessment
  • Comfort assessment
  • Operational energy demand assessment
  • Emissions (including embodied emissions) estimation


  • 2.5D building data (e.g., Swisstopo) 
  • TMY weather files (e.g., Meteonorm) 
  • Building construction year [year]
  • Building usage [type of usage]
  • Carrier/system for domestic hot water and heating 
  • Internal conditions (SIA 2024)


  • Indoor air temperature [°C]
  • Energy demand profiles per retrofit scenario [kWh/h]
  • Primary energy and greenhouse gas emissions per retrofit scenario (operational) [tCO2]
  • Embodied emissions for retrofit measures per retrofit scenario [tCO2]
  • Investment costs per retrofit scenario [CHF]

Future development:

  • Develop a methodology to evaluate energy flexibility potentials of buildings.
  • Increase the spatial coverage to other European countries.
  • Increase the flexibility of the input data (for geometry).


CESAR-P & ehub:
Hourly energy profiles generated with CESAR-P are used to model the demand in the ehub optimisation tool.

ehub (Energy Hub) is a tool for planning and control of multi-energy systems for buildings, neighbourhoods, districts and cities. Sympheny is its commercial deployment as a web application.

Andrew Bollinger (Empa) 

  • Analytical approach: bottom-up
  • Purpose: forecasting and scenario analysis
  • Methodology: optimisation
  • Deterministic or stochastic: deterministic
  • Static or dynamic: dynamic
  • User interface: no (ehub), yes (Sympheny)
  • License: closed source (shareable with research partners upon agreement) 
  • Developer(s): Empa
  • Spatial coverage: unlimited
  • Temporal coverage: unlimited
  • Sector coverage: electricity, heating, cooling, gas, H2
  • Spatial resolution: building to district to city (single hub or multi-hub)
  • Temporal resolution: hourly (full-horizon / typical days)

ehub core features (desktop tool):

  • Multi-energy optimisation
  • Multi-objective optimisation
  • Multi-stage optimisation
  • Thermal networks and multi-energy grids optimisation
  • Daily and seasonal storage
  • Design and/or operational optimisation
  • Sensitivity analysis
  • Modular structure / extensible code base


Sympheny core features (web application):

  • Cloud optimization
  • Built-in databases
  • Browser-based GUI
  • Automated model verification
  • Results visualization dashboards
  • Multi-mode technologies
  • Seasonal constraints on technology operation
  • Complex tariff structure


  • Technology data (e.g., efficiency, investment costs, O&M costs)
  • Energy demand profiles [kWh/h]
  • Solar radiation profiles [kWh/h]
  • Energy imports/exports [CHF/kWh kg-CO2/kWh]



  • Optimal system operation [kWh/h per technology]
  • Optimal system design [kW per technology]
  • CO2 emissions [kg-CO2/year]
  • Life-cycle costs [CHF]

Future development:

  • Enhance representation of flexibility sources:
    • Electric vehicles and vehicle-to-grid technology.
    • Demand-side flexibilities, considering e.g., demand response automaton and IoT.
    • Interaction with ancillary services markets.
  • Integrate financial and sustainability assessment for optimal utilization of existing flexibility sources and for investment in new flexibility sources.
ehub & CESAR-P:
CESAR-P provides building heating, cooling and electric demand profiles for different retrofit scenarios. Ehub uses these profiles for the calculation of optimal building envelope and system retrofitting solutions.


EXPANSE (Exploration of Patterns in Near-optimal Energy Scenarios) is a model for investigating cost-optimal and near-optimal scenarios of the Swiss electricity system.

Prof. Evelina Trutnevyte (UNIGE)

  • Analytical approach: bottom-up
  • Purpose: scenario analysis
  • Methodology: optimisation 
  • Deterministic or stochastic: deterministic (stochastic version also available)
  • Static or dynamic: static (dynamic version also available)
  • User interface: no
  • License: open source (after publication)
  • Developer(s): Renewable Energy Systems Group, University of Geneva (UNIGE)
  • Spatial coverage: Switzerland
    (Europe also available in European EXPANSE model at NUTS-2 resolution)
  • Temporal coverage: single year, 2035 and 2050
  • Sector coverage: electricity (including generation, storage, and transmission)
  • Spatial resolution: municipalities
  • Temporal resolution: hourly
  • Sub-national spatially-explicit modelling of the electricity system
  • Cost-optimal and near-optimal scenario assessment
  • Regional impacts assessment associate with the capacity planning and operation of electricity system infrastructure


  • Technology characterisation (e.g., capital and operational costs, efficiency, lifetime, availability and capacity factors)
  • Renewable energy resource potential
  • International energy and import prices (e.g., natural gas, oil) [CHF]
  • Electricity demands [GW]
  • Policies (e.g., nuclear phase out, emission targets, energy security objectives)
  • Discount rate
  • Maximum deviation in total system costs (slack) to calculate near-optimal scenarios [CHF]



  • Installed generation capacity [GW]
  • Generated and supplied electricity [TWh]
  • Primary energy demand [TWh]
  • Fuel use in the electricity sector [TWh]
  • Renewable electricity generation [TWh]
  • International electricity trade volume: import and exports [TWh]
  • Hourly dispatch of electricity supply
  • Electricity system cost (e.g., fuel, investment) [CHF]
  • CO2 emissions [Mt-CO2]
  • Regional impacts regarding direct jobs, investment, electricity prices, greenhouse gas and particulate matter emissions, and land use

Future development: 
Extension of spatially-explicit EXPANSE to include flexibility measures and sector coupling (heat, transport).

EXPANSE & Nexus-e:
A two-way interaction loop will be set up between EXPANSE and Nexus-e to benefit from complementarity of the models (high spatial resolution of EXPANSE and whole systems approach in Nexus-e).

Nexus-e is a tool for modeling energy systems and assessing the impacts of future developments. It provides an interdisciplinary framework of modules that are linked through well-defined interfaces.

Marius Schwarz (ETH Zurich) 

  • Analytical approach: hybrid
  • Purpose: scenario analysis
  • Methodology: optimisation and  simulation
  • Deterministic or stochastic: deterministic (optimisation models) and stochastic (simulation models)
  • Stochastic: agent-based model
  • Static or dynamic dynamic
  • User interface: yes (web-viewer to assess scenarios)
  • License: closed source (model code on GitLab and accessible on request), open source (planned for 2021)
  • Developer(s): ETH Zurich
  • Spatial coverage: countries either represented in full detail (i.e., Switzerland), aggregated (i.e., neighbouring countries) or as fixed electricity flows (i.e., all other European countries)
  • Temporal coverage: unlimited, including path dependency
  • Sector coverage: electricity systems in full detail on transmission level
  • Spatial resolution: national, cantonal, nodal, municipal
  • Temporal resolution: hourly
  • Centralized electricity system optimization 
  • Decentralized electricity system optimization
  • Electricity market optimization
  • Grid security assessment
  • Macroeconomic assessment


  • Electricity demand [GW]
  • Transmission network [lines, nodes]
  • Generators (existing, potentials and outlook) [GW]
  • Generator and fuel cost [CHF]
  • Weather [Wind, Irradiation]
  • PV investment subsidies [CHF]
  • Injection tariff [CHF]
  • CO2 tax [CHF]



  • Electricity system – installed capacity [GW]
  • Electricity system – capacity distribution [GW]
  • Electricity system – electricity generation [GWh]
  • Electricity system – prices [CHF/MWh]
  • Electricity system – import / exports [TWh]
  • Grid security – demand not served [expected outages]
  • Grid security – grid expansion [lines]
  • Social and environmental impacts – investments & GDP [CHF]
  • Social and environmental impacts – carbon emissions


Future development:

  • Transform Nexus-e from an electricity system to an energy system model, which allows to
    • model the industrial sector, transportation sector, and gas network, and
    • assess Swiss energy system pathways.
  • Develop new methods to link models and depict cross-scale interactions.


Nexus-e & Euro-Calliope:
Calliope provides the developments of the European energy system. Nexus-e uses these developments as boundary conditions for a more detailed assessment of the Swiss energy system.

Nexus-e & EXPANSE:
Nexus-e provides the developments of the Swiss energy system. EXPANSE uses these developments as boundary conditions for an assessment of the Swiss energy system with a higher spatial resolution.

ReMaP (Renewable Management and Real-Time Control Platform) is platform for developing and validating new control concepts and components in a seamless process from a pure software environment – the Simulation framework (SFW) – to a hardware environment – the Control framework (CFW).

The hardware environment uses two existing research and development platforms: the Energy System Integration (ESI) platform at the Paul Scherrer Institute (PSI), and the ehub platform (including NEST and move) at the Swiss Federal Laboratory for Materials Science and Technology (Empa).

Gianfranco Guidati (ETH Zurich) 

  • Analytical approach: bottom-up
  • Purpose: scenario analysis
  • Methodology: simulation
  • Deterministic or stochastic: deterministic
  • Static or dynamic: dynamic
  • User interface: no
  • License: open-source (planned for 2022)
  • Developer(s): ETH Zurich, Smart Grid Solutions, Supercomputing Systems, Adaptricity, PSI, Empa
  • Spatial coverage: unlimited
  • Temporal coverage: unlimited
  • Sector coverage: unlimited (depending on the components the user wants to add)
  • Spatial resolution:  local neighborhood
  • Temporal resolution: sub-hourly  (generally > 1 second)

Simulation framework:

  • Contains a library of different components (including electricity network, battery storage, combined heat and power, electrolyser, fuel cell, heat pump, hydrogen storage, thermal energy storage, methanation reactor, generation and load time series) 
  • Allows to build an energy system based on these components and run simulations in time
  • Connects external components / modules
  • Allows to test and validate control algorithms


Control framework:

  • Based on the Venios platform
  • Allows to interface the simulation framework with real world experiments at Empa and PSI
  • Runs hardware-in-the-loop experiments


  • Description of configuration (e.g., technical elements, electrical grid)
  • Demand und generation data
  • Control algorithms



  • Level of self-sufficiency
  • CO2 emissions
  • Feasibility of control algorithms
  • Capabilities and value of technologies (e.g., storage, generation)

Future development:
Extension of the Simulation Framework to allow simulations of energy systems at district, village and city level. 

Lunch talk: presentation (PDF, 2.2 MB) and presentation recording

Model website:

Note: Intermediate reports are not published yet but can be requested at

SecMOD is a model for exploring and analysing decarbonisation strategies of sector-coupled energy systems.


André Bardow (ETH Zurich) 
  • Analytical approach: bottom-up
  • Purpose: forecasting and scenario analysis
  • Methodology: optimisation
  • Deterministic or stochastic: deterministic
  • Static or dynamic dynamic
  • User interface: yes (GUI for result visualisation)
  • License: open-source (planned for 2021)
  • Developer(s): RWTH Aachen University and ETH Zurich
  • Spatial coverage: flexible from sites to countries
  • Temporal coverage: multi-period for long-term projections (e.g., 2050)
  • Sector coverage: electricity, building and industrial heat, private transportation, CCU, CCS
  • Spatial resolution: flexible (from single to hundreds of nodes)
  • Temporal resolution: flexible (with integrated time series aggregation)
  • Optimisation of transition pathways
  • Integrated time series aggregation
  • Consideration of life-cycle assessment in optimization and evaluation
  • Sector-coupling and power-to-X strategies
  • CCU and CCS
  • Flexible spatial & temporal resolution
  • Flexible extension with new sectors & technologies
  • SecMOD models for the energy transitions in Germany, Switzerland, and Europe (in progress)


  • Nodes and edges
  • Nodal demands [MWh, vkm]
  • Nodal availabilities of technologies [%]
  • Nodal capacity limits [MWh]
  • Nodal existing capacities [MW, vehicles]
  • Import prices [CHF/MWh]
  • Environmental impact constraints [maximum emissions in Mt-CO2eq]
  • Technology performance and cost parameters [CHF/MW, CHF/MWh]



  • Nodal capacity expansion [MW, vehicles]
  • Nodal operation [MWh, vkm]
  • Imports/exports [MWh]
  • Environmental impacts [Mt-CO2eq]
  • Annualised system cost [CHF]

Future development:

  • Develop aggregation methods
  • Develop technical detail (e.g., modelling of sector-coupling technologies)
  • Extend to other sectors
SecMOD & Nexus-e:
SecMOD will be linked to Nexus-e to provide information on additional sectors contributing to the Swiss energy system (e.g., heating), and Nexus-e will feed information to SecMOD on the electricity sector.

*Description of terms in the section “Classification” 

© 2021 SWEET PATHFNDR Project