New Co-Simulation Variants for Emissions and Cost Reduction of Sustainable District Heating Planning

TL;DR

The paper tackles the challenge of reducing energy use and carbon footprints in residential heating by presenting a Modelica-based digital twin of a district heating network. It introduces a co-simulation workflow to evaluate four heating-center variants—ranging from conventional natural-gas to bio-methane, hydrogen, and heat-pump options—against economic and environmental KPIs. Key findings show bio-methane can cut emissions by about 70% versus natural gas, hydrogen with a heat pump achieves around a 77% reduction, and ground-source heat pumps offer strong economic viability when benefits are accounted for. The work demonstrates the value of flexible, early-stage planning using modular, parameterizable models to inform sustainable and cost-efficient urban energy infrastructure decisions.

Abstract

Classical heating of residential areas is very energy-intensive, so alternatives are needed, including renewable energies and advanced heating technologies. Thus, the present paper introduces a new methodology for comprehensive variant analysis for future district heating planning, aiming at optimizing emissions and costs. For this, an extensive Modelica-based modeling study comprising models of heating center, heat grid pipelines and heating interface units to buildings are coupled in co-simulations. These enable a comparative analysis of the economic feasibility and sustainability for various technologies and energy carriers to be carried out. The new modular and highly parameterizable building model serves for validation of the introduced heat grid model. The results show that bio-methane as an energy source reduces carbon equivalent emissions by nearly 70% compared to conventional natural gas heating, and the use of hydrogen as an energy source reduces carbon equivalent emissions by 77% when equipped with a heat pump. In addition, the use of ground source heat pumps has a high economic viability when economic benefits are taken into account. The study findings highlight the importance of strategic planning and flexible design in the early stages of district development in order to achieve improved energy efficiency and a reduced carbon footprint.

Figures (6)

• Figure 1: New methodology of the economic and sustainability analysis with multi-physics model variants of heating centers in a co-simulation setup.
• Figure 2: Residential area heat grid model in Dymola using Modelica language.
• Figure 3: Modular building model built in Dymola using the Modelica language.
• Figure 4: Schematic diagram of heating center variants f.l.t.r. Variant-1, Variant-3 and Variant-4.
• Figure 5: The deviation between the actual indoor temperature and the set temperature of the three Modelica buildings within one week in K (bottom) and the sensible heat output from the radiator to the indoor in W (top).