Author
Listed:
- Ke Xu
(Electric Power Research Institute of State Grid, Tianjin Electric Power Company, Tianjin 300010, China
State Grid Smart Internet of Vehicle Co., Ltd., Beijing 100052, China)
- Dengxin Ai
(Electric Power Research Institute of State Grid, Tianjin Electric Power Company, Tianjin 300010, China)
- Changlong Sun
(Center for Joint Quantum Studies, Department of Physics, Tianjin University, Tianjin 300350, China)
- Yan Qi
(Electric Power Research Institute of State Grid, Tianjin Electric Power Company, Tianjin 300010, China)
- Jiaojiao Wang
(Center for Joint Quantum Studies, Department of Physics, Tianjin University, Tianjin 300350, China
Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, Department of Physics, Tianjin University, Tianjin 300350, China)
- Fan Yang
(Center for Joint Quantum Studies, Department of Physics, Tianjin University, Tianjin 300350, China
Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, Department of Physics, Tianjin University, Tianjin 300350, China)
- Hechen Ren
(Center for Joint Quantum Studies, Department of Physics, Tianjin University, Tianjin 300350, China
Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, Department of Physics, Tianjin University, Tianjin 300350, China
Joint School of National University of Singapore and Tianjin University, International Campus of Tianjin University, Binhai New City, Fuzhou 350207, China)
Abstract
In this paper, we introduce a mathematical framework for analyzing and optimizing district heating networks by leveraging the Green’s function method. Traditional numerical methods for simulating district heating networks often face computational challenges and lack transparency in revealing cause-and-effect relationships in heat propagation. By treating temperature as a scalar field, we employ Green’s function methods to derive analytical solutions that provide a more transparent and intuitive understanding of how heat propagates through the network in response to various inputs. We demonstrate the application of this framework through two numerical examples involving heating networks. Comparative results show that, under identical hardware conditions, the Green’s function method requires only about one-fifth of the computational time compared to the finite element method for the same case. This approach offers distinct advantages in terms of computational efficiency, accuracy, and interpretability, enabling more effective design, optimization, and control of sustainable district heating systems.
Suggested Citation
Ke Xu & Dengxin Ai & Changlong Sun & Yan Qi & Jiaojiao Wang & Fan Yang & Hechen Ren, 2025.
"Green’s Function Approach for Simulating District Heating Networks,"
Energies, MDPI, vol. 18(10), pages 1-13, May.
Handle:
RePEc:gam:jeners:v:18:y:2025:i:10:p:2627-:d:1659472
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