A review of federated learning in renewable energy applications: Potential, challenges, and future directions

Federated learning has recently emerged as a privacy-preserving distributed machine learning approach. Federated learning enables collaborative training of multiple clients and entire fleets without sharing the involved training datasets. By preserving data privacy, federated learning has the potential to overcome the lack of data sharing in...

A Brief Climatology of Dunkelflaute Events over and Surrounding the North and Baltic Sea Areas

In the coming decades, the European energy system is expected to become increasingly reliant on non-dispatchable generation such as wind and solar power. Under such a renewable energy scenario, a better characterization of the extreme weather condition ‘Dunkelflaute’, which can lead to a sustained reduction of wind and solar power, is important....

Wind Turbine Design for a Hybrid System: with the emphasis on generation complementarity

The global issue on global warming leads nations to reduce their carbon emission, and one way to do it is by decarbonising the power system and employing higher penetration of renewable energy technology. However, due to the variable nature of renewable energy, their integration to the power system poses challenges to the utilities and system...

Assessing Renewable Resources at the Saronikos Gulf for the Development of Multi-Generation Renewable Systems

Decarbonisation of any energy system implies that more renewables will have to be incorporated into the grid. This requires a thorough assessment of available resources to properly estimate potential contributions and identify opportunities. This work focuses on the Saronikos Gulf, which is part of the most crowded urban coastline in Greece....

Implications of diurnal and seasonal variations in renewable energy generation for large scale energy storage