A multi-rate dynamic analysis method of individual-based district heating system

Changrui Xu, Xiaosheng Xu, Mengshi Li, Qinghua Wu, Jiehui Zheng and Wenting Xiao

Energy, 2024, vol. 295, issue C

Abstract: The new generation of the district heating system (DHS) has attracted much attention due to its high efficiency. A precise and fast dynamic simulation is the foundation of the optimization and control strategy of a DHS. As a type of heterogeneous system, the DHS has internal components with multiple time scales, which limits accuracy of simulations. However, current studies have either chosen pseudo-dynamic models or have not considered the effect of the internal time scale on the simulation. To solve above problems, a dynamic multi-rate simulation method based on the individual-based model (IBM) is proposed in this paper. According to IBM, a complex system is decoupled into individuals, who interact with each other to form the whole system from bottom-up. During the process of modeling, equations of individuals indicating their dynamic behaviors are all converted into a system of ordinary differential equations (ODEs). And then the ODEs are solved from system level using multi-rate simulation methods. The case study illustrates that the proposed method takes 36.59 s for the 72 h long-term simulation of the DHS containing three components commonly involved and a district heating network, which provides good decision-making information for the optimal control of the system.

Keywords: District heating system; Dynamic model; Individual-based; Dynamic simulation; Multi-time scale (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S036054422400745X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:295:y:2024:i:c:s036054422400745x

DOI: 10.1016/j.energy.2024.130973

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().