TradeRES scenario database

Dataset for TradeRES scenarios

The TradeRES project created four central scenarios of the future European power system. “Scenario” within TradeRES refers to a structured input data collection that encapsulates certain properties of the underlying future energy system. The four scenarios, abbreviated S1, S2, S3 and S4, are carbon-free by assumption and vary in terms of the flexibility of the demand-side, the variability of the supply-side and the degree of sector-coupling. In addition, TradeRES created a scenario S0 to represent an intermediate energy system on the path to decarbonisation. This scenario S0 with a 60% non-thermal renewables penetration, is considered in some case studies as a departing scenario for reference. It considers exogenous electricity generation capacities based on 2030 national energy and climate plans.

In addition, TradeRES created scenarios for additional analysis where, for example, the weighted average cost of capital (WACC) of technologies was varied.

The common data on the scenarios are given in the supplementary data file D2.1_TradeRES_Scenario_data_v3.xlsx. The table below describes the data items that are included in the data file. The report D2.1_TradeRES_A-database-of-TradeRES-scenarios_Ed3.pdf describes in more detail the scenarios and data files.

Description

Emission factors

Kg of CO2 equivalents emitted from burning 1 MWh of fuel

Commodity prices

Price assumptions for commodities

New technology data

Projected cost and technical parameters of new energy conversion (production, consumption, storage) technologies

Wind potential

Wind (offshore and onshore) potential in European countries

Solar potential

Solar (different PV categories and CSP) potential in European countries

Transmission capacities

Electricity and hydrogen transmission capacities in the scenarios

Initial technology capacities

“Initial” electricity generation capacities in the scenarios

Aggregated demand

Assumptions on aggregated electricity demand by sector and bidding zone

Demand time series

Load consumption time series

Renewable time series

Capacity factor time series, hydro inflow time series

Building data

Main assumptions used in the model for heating and cooling of buildings

EV data

Main assumptions for the private passenger vehicles and their electrification