Renewables, storage, intelligent control: how to address complexity and dynamics in smart district heating systems?. (September 2018)

• Record Type: Journal Article
• Authors: O'Donovan, Keith; Falay, Basak; Leusbrock, Ingo
• Is Part Of: Energy procedia. Volume 149(2018)
• Page Start: 529
• Page End: 538
• Publication Date: 2018-09
• Subjects: District Heating -- Modelling -- Dynamic Simulation -- Dymola -- Modelica -- Storage -- Solar Thermal -- Control -- Low Temperature Networks; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2018.08.217
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: The design of future district heating network will focus on two major aspects: The first of which is boosting the share of renewable heat in overall energy mix, and the second of which is to achieve lower network operating temperatures, thus increasing the potential for integrating new alternative heat sources. Renewable heat sources by their nature are highly fluctuating and require thermal storage and sophisticated control strategies to be utilized efficiently. Static modelling and simulation tools are incapable of capturing the dynamic effects and necessary control strategies that come with such complex systems. The work in this paper will outline how Dymola, a Modelica based simulation tool is capable of handling such complexity. The first section will outline an automated workflow to translate CAD drawings into functioning Dymola models. The next sections will upgrade a small heating network model to a future system with the addition of a large thermal storage tank, solar collectors and prosumers. The last section will demonstrate a concept to achieve lower network operating temperatures by simulating the network with a branch supplied by the return pipeline. The addition of the storage tank and solar showed an increase of the combined biomass and solar from 82% to 93% over the reference time frame. The second use case demonstrated a 12% reduction in network heat losses for a given week by implementing the lower temperature branch.