AWETRAIN
Airborne Wind Energy TRAining for Industrialization Network
The overarching objective of AWETRAIN is training the next generation of researchers to further advance the integration of airborne wind energy into the industrial energy system. The aim is to maximize the impact of airborne wind energy technology by focusing on the engineering and socio-political transformations that are needed in the difficult transition from prototype to commercialization.
DC8: Reliable and Functional Electrical Systems for AWE
Objectives
The focus of DC8 is on improving reliability and functionality of the electrical (sub)systems of AWE – such as electrical machines, machine and grid side power converters and grid filters. By intelligent and real-time fault detection and diagnosis (FDD), fault-tolerant control and condition monitoring/predictive maintenance, their reliability and functional safety will be boosted to reduce the levelized costs of energy and to harvest as much energy as possible even under faults. By adding additional features such as grid-supporting, grid-forming or black start capabilities, the functionality of the electrical systems will meet future grid requirements for frequency and voltage stability in order to (i) allow for inertia emulation, (ii) to mimic virtual synchronous generators and (iii) to minimise power fluctuations. Moreover, external faults of the power grid such as short circuits, unbalanced loading or harmonic pollution affect the AWE in form of significant distortions (e.g., during grid synchronisation). Faults might lead to over-voltages or over-currents which risk (partial) destruction and proper operation and functionality, without adequate countermeasures and/or safety features. The DC will analyse the main faults, resulting failures and proper counter measures to achieve real-time FDD, reconfiguration, fault-tolerant control and condition monitoring strategies. Finally, to ensure optimal operation and to reduce power fluctuations, the different single AWE of an AWE farm must be considered, operated and controlled together in a distributed manner to be capable of contributing to grid stability.
Expected Results
- Improved reliability of electrical (sub)systems of AWE by intelligent and real-time fault detection and diagnosis (FDD), fault-tolerant control and condition monitoring/predictive maintenance
- Enhanced functionality of electrical (sub)systems of AWE such as grid-supporting, grid-forming or black start capabilities and inertia emulation or virtual synchronous generators
-> Link to the official Awetrain DC8 page
DC9: The mutual impact of AWE based plants on the electricity grid
Objectives
AWE will produce electrical power, which must be fed into the power grid. The distribution grid, where the feed-in usually takes place, is already facing several challenges with fluctuating generation from existing wind power plants or PV. This behaviour will intensify in the future, as the ratio of renewable (and often volatile) generation to conventional and schedulable generation increases. AWE has a different feed-in characteristic and several ways it can provide grid services. This DC will investigate the mutual impact of grid stability issues, increasing AWE penetration and AWE based grid services. As a first step, the research will look at distinctive configurations of different electricity grids in Europe and the different requirements they would impose on AWE based plants. Second, given the power generation characteristic of the different AWE concepts, and individual plant configurations (range of plant power and number of aircraft), the research will look at how increasing the penetration will impact grid stability on these different grids. The optimal power classes, cluster sizes, or distribution will be derived. The research will also look at how different AWE based grid services can be used to strengthen the grid. These will be applied in network calculations on real grid topologies to evaluate the potential of AWE to support grid stability.
Expected Results
- Feed-in characteristic of AWE depending on environmental and design parameters
- Parameter set to trigger a grid-serving behaviour of AWE
- Potential to balance power consumption or generation peaks in existing distribution grids
-> Link to the official Awetrain DC9 page
General Information:
Duration: 01.12.2024 - 30.11.2028
Institutions:
- Fakultät für Elektrotechnik und Informationstechnik
- Institut für nachhaltige Energiesysteme (ISES)
Project management:
- Prof. Dr.-Ing. Christoph M. Hackl
- Prof. Dr. Stephanie Uhrig
Funding program: Horizon Europe
Project funding: European Union
Project partners:
