Zichan Xie , Haichao Wang , Pengmin Hua , Maximilian Björkstam , Risto Lahdelma
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引用次数: 0
摘要
区域供热(DH)网络建模所涉及的计算复杂性阻碍了将网络运行纳入全面的 DH 系统研究。我们利用离散事件仿真(DES)开发了一种灵活、准确、快速的动态热仿真模型。该模型用途广泛,适用于任何带有集中供暖设备的树状 DH 网络,可估算节点温度并计算管道热损失。通过使用可变时间步长并结合两种先进技术:懒惰评估和定制优先队列,该模型的速度得到了提高。为了进一步提高计算速度,我们开发了一种消除冗余采样点的技术。经过测试,该模型与实际测量结果具有极佳的一致性。值得注意的是,在不影响温度精度的情况下,减少采样点可将模拟速度提高三倍。我们的研究结果凸显了 DES 模型在大规模动态网络模拟方面的巨大潜力,并为 DH 网络模拟和系统优化提供了一个前景广阔的解决方案。
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.
期刊介绍:
Energy is a multidisciplinary, international journal that publishes research and analysis in the field of energy engineering. Our aim is to become a leading peer-reviewed platform and a trusted source of information for energy-related topics.
The journal covers a range of areas including mechanical engineering, thermal sciences, and energy analysis. We are particularly interested in research on energy modelling, prediction, integrated energy systems, planning, and management.
Additionally, we welcome papers on energy conservation, efficiency, biomass and bioenergy, renewable energy, electricity supply and demand, energy storage, buildings, and economic and policy issues. These topics should align with our broader multidisciplinary focus.