Distributed Flexibility Fitness Landscape Analysis for Parameterization of Algorithms in Multi-Agent Energy Systems

Malin Radtke, Stefanie Holly and Astrid Nieße
IDC 2023
Optimizations in the energy system often rely on the aggregated flexibility of the assets involved. This paper addresses the challenge of assessing the aggregated flexibility of a set of energy resources. To this end we propose a novel approach that utilizes fitness landscape analysis to explore the characteristics of power system optimization problems based on asset flexibility. To demonstrate the practical application of our approach, we present a use case involving the distributed optimization of energy resource scheduling using the COHDA.Our results demonstrate the potential of flexibility fitness landscape analysis in improving the scheduling strategies for energy resources by leveraging their inherent flexibility.
September / 2023