Project Details
Projekt
Multi-Objective Optimisation for the Inverse Analysis of Design Requirements for Carnot Batteries from an Energy System Perspective (MOIn Carnot)
Applicant
Professor Dr. Valentin Bertsch
Subject Area
Technical Thermodynamics
Energy Process Engineering
Energy Process Engineering
Term
since 2023
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 526062606
The affordable, location-independent and resource-conserving storage of electrical energy at large scale is one of the highly relevant and unsolved challenges in the transition to variable renewable energy sources. The emerging technology of Carnot batteries, converting electricity into heat by means of high-temperature heat pumps, using inexpensive materials as heat storage, and converting the heat back into electricity, e.g., by means of steam turbines, could potentially contribute to solving this challenge. Like all storage technologies, Carnot batteries must fit in the overarching energy system and any commercial investment must be economically feasible. Energy system modelling and analysis can provide a comprehensive view on the role of different technologies, including storage, in future energy systems and markets while considering the many interdependencies within such complex systems. Energy system models (ESMs) have been developed and are typically used for considering energy (storage) technologies with relatively high technology readiness levels (TRLs). They require, among other things, costs and efficiencies as input parameters for all technologies considered. In the case of emerging technologies with low TRLs such as the Carnot battery, however, estimations of costs and efficiencies are usually not possible or poorly verified and therefore highly uncertain. This uncertainty often creates a barrier for the collaboration between technical disciplines and energy system analysis in the case of low TRL technologies. To overcome this barrier, fundamental research is needed to develop a new methodology. In order to make ESMs usable for the analysis and assessment of emerging technologies at low TRLs, for which cost and efficiency estimates are difficult or impossible, the ESMs must be inverted. This means that, for instance, costs and efficiencies of technologies should no longer be provided as model input parameters, but the models are to be inverted in such a way that they are turned into variables and thus can be used as an optimization objective. This research proposal therefore aims for developing an inverse ESM to provide support to and intensify the collaboration with technology developers. Using multi-objective optimization, the inverse ESM will provide results in the form of a Pareto front (e.g., a trade-off curve between system-level costs and a technology performance indicator like efficiency or even between two conflicting technology performance indicators) to identify combinations of technical and economic performance indicators that must at least be achieved for a technology to prevail in the system. It is expected that the development of such a novel methodology will enable a closer collaboration between energy system analysis and operations research on the one hand and the technical disciplines on the other, opening up new synergy potentials.
DFG Programme
Priority Programmes
