A Graph-Based Technique for the Automated Control-Oriented Modeling of District Heating Networks

TL;DR

This paper introduces a graph-based automated modeling framework for district heating networks that accurately captures system dynamics and supports topology optimization to improve energy efficiency.

Contribution

It presents a novel graph-based algorithm for automated, adaptable system modeling and demonstrates its effectiveness in optimizing network topology for reduced heat losses.

Findings

Achieved an average normalized RMSE of 0.39 in mass flow rate predictions.

Validated model accuracy against experimental data from a laboratory network.

Topology optimization reduced heat losses by 15%.

Abstract

Advanced control strategies for delivering heat to users in a district heating network have the potential to improve performance and reduce wasted energy. To enable the design of such controllers, this paper proposes an automated plant modeling framework that captures the relevant system dynamics, while being adaptable to any network configuration. Starting from the network topology and system parameters, the developed algorithm generates a state-space model of the system, relying on a graph-based technique to facilitate the combination of component models into a full network model. The accuracy of the approach is validated against experimental data collected from a laboratory-scale district heating network. The verification shows an average normalized root mean square error of 0.39 in the mass flow rates delivered to the buildings, and 0.15 in the network return temperature. Furthermore, the ability of the proposed modeling technique to rapidly generate models characterizing different network configurations is demonstrated through its application to topology optimization. The optimal design, obtained via a branch and bound algorithm, reduces network heat losses by 15% as compared to the conventional length-minimized topology.