Dynamic thermal simulation of a tree-shaped district heating network based on discrete event simulation
The computational complexity involved in modelling district heating (DH) networks impedes the integration of network operations into comprehensive DH system studies. We developed a flexible, accurate, and fast dynamic thermal simulation model utilising discrete event simulation (DES). This model is versatile, suitable for any tree-shaped DH network with a central heating plant and can estimate node temperatures and calculate pipe heat losses. The speed of the model is improved via using variable time steps and by incorporating two advanced techniques: lazy evaluation and a customised priority queue. To further improve the computational speed, we developed a technique to eliminate redundant sampling points. This model was tested and demonstrated excellent consistency with actual measurements. Remarkably, reducing sampling points can speed up the simulation by a factor of three without compromising the temperature accuracy. A 72-day simulation of a network with 102 pipes was completed within 0.219 s. Our findings highlight the significant potential of the DES model for large-scale dynamic network simulations and offer a promising solution for DH network simulations and system optimisation. • Novel, fast and accurate dynamic thermal simulation of district heating networks • Lagrangian approach using the Discrete Event Simulation with variable time steps • Efficient C++ implementation with customized data structure and advanced techniques • Flexible trade-off between speed and accuracy • Validated by 72-day measurement data from real 24 customer network
Authors
- Pengmin Hua (ORCID: https://orcid.org/0000-0001-9095-1069)
- Risto Lahdelma (ORCID: https://orcid.org/0000-0001-7882-2918)
- Zichan Xie (ORCID: https://orcid.org/0000-0002-6386-707X)
- Haichao Wang (ORCID: https://orcid.org/0000-0002-0313-5643)
- Maximilian Björkstam
Institutions
- Dalian University of Technology (CN)
- Shriners Hospitals for Children (US)
- Aalto University (FI)
Publication Details
- Journal
- Energy
- Published
- 2024-11-08
- DOI
- https://doi.org/10.1016/j.energy.2024.133775
- Citations
- 5
- Primary Topic
- Integrated Energy Systems Optimization
- Type
- article
- Field-Weighted Citation Impact
- 1.04