Authors:
Sarah Braun
1
;
Sebastian Albrecht
1
and
Sergio Lucia
2
Affiliations:
1
Siemens AG, Otto-Hahn-Ring 6, 81739 München, Germany
;
2
TU Dortmund University, August-Schmidt-Straße 1, 44227 Dortmund, Germany
Keyword(s):
Robust Control, Attack Identification, Mathematical Modeling, Nonlinear Model Predictive Control, Distributed Control.
Abstract:
With the growing share of renewable energy sources, the uncertainty in power supply is increasing, on the one hand because of fluctuations in the renewables, but on the other hand also due to the threat of deliberate malicious attacks, which may become more prevalent due to the growing number of distributed generation units. It is thus essential that local microgrids are controlled in a robust manner in order to ensure stability and supply security even in the event of disturbances. To this end, we introduce a mathematical model for interconnected, physically coupled microgrids with renewable generation that are exposed to the risk of attacks. For optimal energy management and control, we present a resilient framework that combines a model-based method to identify occurring attacks and a model predictive control scheme to compute robust control inputs. We demonstrate the efficiency of the method for microgrid control in numerical experiments.