Modeling and Control of Multi-Energy Dynamical Systems: Hidden Paths to Decarbonization

TL;DR

This paper identifies limitations in current energy system modeling and control for decarbonization and proposes a structure-preserving, multi-layered approach with nonlinear control to enhance system flexibility and integration.

Contribution

It introduces a novel multi-layered energy modeling framework and nonlinear control strategies that reveal hidden system structures to facilitate decarbonization efforts.

Findings

Enhanced information exchange enables better system understanding.

Multi-layered models improve interaction management among energy modules.

Nonlinear control supports adaptive and feasible system operation.

Abstract

This paper points out some key drawbacks of today's modeling and control underlying hierarchical electric power system operations and planning as the hidden roadblocks on the way to decarbonization. We suggest that these can be overcome by enhancing today's information exchange and control. This can be done by revealing and utilising inherent structure-preserving features of complex physical systems, and, based on this, by establishing multi-layered energy modeling. Each module (component, control area, non-utility-owned entities) can be characterized in terms of its interaction variable, and higher level models can be used to understand the interaction dynamics between different modules. Once the structure is understood, we propose nonlinear energy control for these modules which supports feed-forward self-adaptation to ensure feasible interconnected system. Based on these technology agnostic structures it becomes possible to expand today's Balancing Authorities (BA) to multi-layered interactive intelligent Balancing Authorities (iBAs) and to introduce protocols for flexible utilization of diverse technologies over broad ranges of temporal and spatial conditions.