DFG Priority Programme 1984
Hybrid and multimodal energy systems: System theoretical methods for the transformation and operation of complex networks
The electric power system is a complex assemblage of interconnected components of different types, organised in geographically distributed structures of high complexity, which are required to meet highest reliability and security standards to enable a secure, stable and uninterrupted electric power supply. Currently, due to the politically enforced decarbonisation of the energy sector, the electric power system is undergoing a drastic transformation, which will have a fundamental impact on the way the system is organised and operated. In this context, according to current development trends, it can be expected that the system of the future will become distributed, multimodal, hybrid and smart:
Distributed: Due to the decommissioning of conventional power plants and the large-scale integration of renewables within transmission and distribution networks, the system will be characterised by distributed and mainly converter-dominated generation. Further, the large-scale integration of storage devices all over the system is expected.
Multimodal: The grid will be interlinked with other energy networks – such as heat and gas networks – via multimodal interfaces. This will enable multimodal power and energy interactions in a coordinated way transforming the system into a highly interdependent multimodal energy system.
Hybrid: The integration of HVDC links into the AC-grid will enable coordinated power exchange over long distances in a controlled way and will transform the system into an AC/DC hybrid electric power system.
Smart: The system will be pervaded by information and communication technologies over all voltage levels and multimodal domains enabling integrated monitoring, protection and control in real-time.
This transition towards a Distributed, Multimodal, Hybrid, and Smart (DMHS) system does not only require significant changes in the established infrastructure. In fact, it can be expected that the complexity of the system will substantially increase and its dynamic behaviour will fundamentally change making the development of new planning, control and operation strategies and concepts a matter of urgency.
The Priority Programme targets on new system theories, concepts and methods for the future DMHS system to guarantee a secure, stable, resilient and efficient operation. The programme’s key objective is the research on new operational concepts, system architectures and monitoring and control schemes for future DMHS power systems. Besides, the programme also targets on research topics like suitable modelling, analysis and optimisation approaches which can be applied in the DMHS power system context.
The Priority Programme covers the following areas:
- systems theory for structuring, planning, design and operation of complex DMHS power systems
- system architectures for DMHS systems, e.g. cellular structures, multimodal active distribution networks and HVDC super grids
- strategies and methods for resiliency, security and stability enforcement of DMHS systems, e.g. joint DMHS emergency control and contingency plans, prevention and mitigation of controller conflicts in DMHS systems
- provision of ancillary services in DMHS systems, e.g. black-start and DMHS system restoration, grid forming converters for frequency enforcement, cross voltage level congestion management and voltage control, flexibility harvesting across DMHS domains
- control and optimisation methods for DMHS systems, e.g. multi-agent-systems, self-organised distributed controllers, distributed machine-learning-based control, game-theoretic approaches, non-linear multi-objective optimisation
- modelling and simulation of DMHS systems, e.g. joint modelling of ICT-, multimodal and hybrid energy systems under consideration of multiple voltage levels in the electric domain
- approaches for deterministic and probabilistic steady-state and dynamic modelling of DMHS systems, e.g. nonlinear and hybrid model order reduction, nonlinear and hybrid system identification, artificial-intelligence-based modelling