Towards Designing Robust and Resilient Hybrid Renewable Energy Systems

Hybrid Renewable Energy Systems (HRESs) consist of renewable energy sources, storage facilities, and fuel-based generators as backup. In the current phase of the energy transition, nearly every power grid comprises these components, thus making it a HRES. Sizing these systems is essential in order to be able to supply enough energy while also keeping costs as low as possible. This paper gives an overview of HRES optimization by describing common optimization goals, techniques, and ways to model and simulate the systems. It also shows that the optimization process has not yet considered resilience and robustness properties. We address this research gap by proposing an approach to include robustness and resilience in optimizing these systems using Adversarial Resilience Learning (ARL).