Optimizing district heating operations: Network modeling and its implications on system efficiency and operation

Abstract

Efficient utilization of local heat sources in urban areas necessitates integrating various suppliers into District Heating Systems (DHSs), considering the diverse ownership and physical characteristics of these sources. This study addresses the challenges in operational planning and pricing through local heat markets, emphasizing the importance of accurately representing the District Heating Network (DHN) physics for reliable market matching. We explore different DHN modeling approaches for day-ahead operational planning, balancing between numerical efficiency, economic viability, and operational feasibility. Our models, ranging from mixed-integer linear to non-linear, aim to maximize social welfare under steady-state conditions and are tested on small scenarios to highlight potential synergies between Heatpumps (HPs) and Combined Heat and Power Units (CHPs). Assuming regulations enable cost-competitive operations between HPs and CHP units, we anchor our energy price assumptions in 2030 forecasts for Germany. This approach allows us to highlight the techno-economic advantages of leveraging non-linear model flexibility during the transition to sustainable heat supply. The model’s operational schedules are further validated through detailed physical simulations in Modelica, revealing the impact of transient effects on actual performance, particularly the risks associated with thermo-hydraulic oscillations. The study concludes by discussing the required model complexity for effective DHS scheduling.