WP1 – Optimal Mix of flexibilities

Key figures/key points
Partners involved:


Workforce: 259 people months
Contact: Jens WEIBEZAHN, Technische Universität Berlin

What is flexibility ?
Flexibility is understood as a power system’s ability to cope with variability and uncertainty in demand, generation and grid, over different timescales.
Why different interacting models?
Flexibility assessment covers a wide range of temporal and geographical issues that cannot all be addressed in one simulator due the mathematical complexity. Different simulators are thus necessary and interfaces have to be created in-between to model the various constraints.




  • Quantify the needs of flexibilities in different long-term scenarios
  • Define the most adequate sources of flexibilities in the scenarios
  • Create advanced tools and methodologies to analyse flexibility






Key achievements until june 2019
Deliverable 1.1 “European Long-Term Scenarios Description” introduces three scenarios: Current Goals Achieved, Accelerated Transformation and Neglected Climate Action. The models Genesys and Dynelmod are presented, as well as the assumptions and input data. First simulations results are discussed: the urge to reduce CO2 emissions leads to a deeper electrification of the energy system (heat and transport are particularly concerned) which creates new needs and also new opportunities of flexibility. Moreover, Power-to-X becomes crucial at high decarbonization targets.
Deliverable 1.2 “Flexibility cost and operational data” describes technologies that can serve as sources of flexibility for the electricity system and includes, electrochemical, mechanical, and chemical storage systems as well as flexible thermal power plants. This report is accompanied by a comprehensive data set of technical parameters and cost data.
A flexibility requirements methodology has been published to quantify flexibility needs at different time scales (annual, weekly and daily). It has been tested on French and European scenarios to assess the flexibility needs depending on: the degree of network interconnection, the penetration of wind power, solar power, electric heating and cooling.

 Next steps by June 2020

  • Run the detailed models (Antares, DESPLAN, Mora, Digsilent)
  • Create the interactions between the models
  • First analysis of the needs and sources of flexibility



This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement n°773406