CROSS / CROSS catalog / E-hub tool
E-hub tool
Developers
Empa: Andrew Bollinger, Julien Marquant, Boran Morvaj, Carlos Pacheco, Youssef Sherif, Mashael Yazdanie, Robin Mutschler, Leonie Fierz, Binod Koirala
Empa: Andrew Bollinger, Julien Marquant, Boran Morvaj, Carlos Pacheco, Youssef Sherif, Mashael Yazdanie, Robin Mutschler, Leonie Fierz, Binod Koirala
Contact
Andrew Bollinger, Empa
Binod Koirala, Empa
License
Open Source
SWEET Project
DeCarbCH - WP 3
PATHFNDR - WP 2
Ehub is a tool for planning and control of multi-energy systems for buildings, neighborhoods, districts and cities.
Features
ehub core features
- 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
- 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
Facts
| Class | Energy System |
| Type | Deterministic |
| Spatial regions | Unlimited |
| Spatial resolution | Building to district/city (single hub or multi-hub) |
| Time coverage | Single year (for multiple years possible) |
| Time resolution | Hourly (full-horizon / typical days) |
Sectors | Electricity, heating, cooling, gas, H2 |
Category | Inputs | Outputs |
|---|---|---|
| Socioeconomy | Climate policy measures Managerial (strategical, business models) Psychological (revealed or stated preferences, willingness to pay, intentions) Sociodemographic (household, age, income, gender..) Legal | |
| Infrastructure | Electricity - transmission network Electricity - distribution network Thermal network Gas network Hydrogen network Captured CO2 network | |
| Environment | CO2 emissions from energy system CO2 emissions from electricity production CO2 emissions in industry | Total CO2 emissions Captured CO2 emissions |
| Energy demand | Space heating Space Cooling Industrial heating Industrial cooling Hot water Total electricity Electricity - appliances Passenger mobility | |
| Energy supply/production | Space heating Space cooling Industrial heating Industrial cooling Heat storage Cold storage Hot water Electricity - production Electricity - storage Electricity - installed capacity Passenger mobility | |
| Resource potential | Solar Water Wind Biomass Hydropower potential Geothermal Artificial thermal sources (e.g. waste heat) | |
| Direct demand of resources | Gas as feedstock in industry (i.e. non-heating demand) | |
| Trade | Electricity imports/exports Electricity import/export price Fossil fuels (i.e. gas, gasoline, diesel) imports/exports Fossil fuels import/export price Biomass and biofuels imports/exports Biomass and biofuels import/export price Hydrogen imports/exports Hydrogen import/export price | Electricity imports/exports Hydrogen imports/exports |
| Technologies Inv: Investment costs Eff: Efficiency OM: Operation and Maintenance costs LCA: Life cycle assessment indicators | Batteries (Inv,Eff,OM) CHPs (Inv,Eff,OM) Electricity generation (Inv,Eff,OM) Electricity storage (Inv,Eff,OM) Heat production (Inv,Eff,OM) Heat storage (Inv,Eff,OM) Hydrogen production (Inv,Eff,OM) Vehicles (Inv,Eff,OM) | Batteries (LCA) CHPs (LCA) Electricity generation (LCA) Electricity storage (LCA) Heat production (LCA) Heat storage (LCA) Hydrogen production (LCA) Pyrolysis (LCA) Vehicles (LCA) |
| Prices | ||
| Others |
References
- A. Bollinger and V. Dorer (2017). The Ehub Modeling Tool: A flexible software package for district energy system optimization. Energy Procedia. https://doi.org/10.1016/j.egypro.2017.07.402
- J. Marquant et al (2017). A holarchic approach for multi-scale distributed energy system optimisation. Applied Energy. https://doi.org/10.1016/j.apenergy.2017.09.057
- B. Morvaj et al (2017) Decarbonizing the electricity grid: The impact on urban energy systems, distribution grids and district heating potential. Applied Energy. https://doi.org/10.1016/j.apenergy.2017.01.058
- R. Wu et al (2017). Multiobjective optimisation of energy systems and building envelope retrofit in a residential community. Applied Energy . https://doi.org/10.1016/j.apenergy.2016.12.161
- K. Orehounig et al (2014). Towards an energy sustainable community: An energy system analysis for a village in Switzerland. Energy and buildings. https://www.sciencedirect.com/science/article/pii/S0378778814006549
- A. Bollinger at al (2019). Optimization-based planning of local energy systems - bridging the research-practice gap. SBE19 Graz. https://www.dora.lib4ri.ch/empa/islandora/object/empa%3A20769
This page was last modified on 2022.02.22, 13:16