Towards Network-Aware Operation of Integrated Energy Systems: A Comprehensive Review

TL;DR

This paper reviews network-aware modeling, optimization, and control methods for integrated energy systems, emphasizing the importance of network constraints and topology in improving efficiency, flexibility, and scalability of multi-energy systems.

Contribution

It provides the first comprehensive analysis of network-aware approaches for IES, highlighting methodological limitations and outlining future research directions.

Findings

Network constraints and topology shape feasible operating regions.

Current methods face challenges in tractability and scalability.

Future directions include distributed optimization with guarantees.

Abstract

Integrated Energy Systems (IES) are systems of interconnected electricity, gas, heating, and cooling networks, where the carriers interact and depend on one another. Beyond these core vectors, IES may also incorporate additional infrastructures, such as hydrogen, transportation and water networks, whenever sector coupling or cross-vector exchanges are relevant. Although modern cities already function as multi-energy systems, these networks are still planned and operated in isolation, which leads to inefficiencies and unused flexibility. As distributed energy resources (DERs) grow, local coupling among electricity, heating, and gas networks becomes stronger, so coordinated operation across carriers and infrastructures is essential. IES can improve efficiency, flexibility, and renewable integration, yet operation is challenging because of complex interdependencies, non-convex behaviors, and multi-scale dynamics of the energy networks. A key point that the literature often overlooks is the explicit role of network constraints and topology, which shape feasible operating regions, affect scalability, and determine how uncertainty and formal guarantees can be addressed. This review provides a first comprehensive analysis of network-aware modeling, optimization, and control methods for IES. We identify methodological limitations related to tractability, feasibility guarantees, and scalability. Building on these insights, we outline research directions that include distributed optimization with theoretical guarantees and control approaches informed by operational data. The review offers a foundation for scalable, network-aware operational frameworks for future low-carbon energy systems.