This project aims at investigating promising CB configurations, the potential role of CBs in future energy systems, as well as economic incentives and barriers for a successful market entry. As technical CB development is still in progress, energy economics can provide an orientation towards promising directions. This motivates a novel inverse approach to investigate the role of CBs in future energy markets. Such an inverse approach is new to energy market modellers and brings challenges with it. Hence, we aim at depicting CBs in an agent-based market model depicting Germany and its neighbours to identify economically attractive technical configurations and their use in the system, to derive potential profit-risk structures for CBs as an investment option, and to assess inevitable techno-economic trade-offs from a market perspective.

The major challenge consists of the adequate depiction of the market functioning through individual economic decisions. A working programme consisting of six working packages addresses this challenge and thereby deploys an agent-based electricity market simulation. Whereas optimisation approaches usually identify desirable investment and dispatch decisions in a normative manner taking a central planner perspective, the agent-based approach is not dependent on generally assuming perfect foresight and perfect coordination. It is able to depict the market structure and market participants’ individual decisions.

The key objectives of the project are threefold: On the one hand, the goal is to integrate the inverse engineering character into agent-based energy system modelling by modelling techno-economic characteristics as decision variables of the agents. This requires extensive methodological developments, both in the short- and in the long-term decision-making of agents. On the other hand, the technical representation of the CB’s characteristics requires model enhancements. Particularly the differentiation, interplay and potential profit cannibalisation of competing flexibility options lead to challenges, as many degrees of freedom complicate convergence, if the techno-economic properties are very similar or agents face immanent uncertainties in their strategic decisions. The third objective is to develop a framework for assessing profit-risk structures of promising technical configurations, based on mean-reverting and path-dependent energy system uncertainties. Path-dependent uncertainties such as the development of new technologies or renewable capacity expansion require endogenous treatment in the simulation model. We propose extension of the existing agent-based model to derive, among others, dispatch curves for different CB configurations under varying market circumstances, as well as profit-risk structures for CBs from an individual market participant’s perspective.

Professor Dr. Wolf Fichtner
Karlsruher Institut für Technologie
Institut für Industriebetriebslehre und Industrielle Produktion
Lehrstuhl für Energiewirtschaft

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 optimisation 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 optimisation, the inverse ESM will provide results in the form of a Pareto front (e.g., a trade-off curve between systemlevel 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.

Professor Dr. Valentin Bertsch
Ruhr-Universität Bochum
Fakultät für Maschinenbau
Lehrstuhl für Energiesysteme und Energiewirtschaft