A hierarchical and categorized algorithm for efficient and robust simulation of thermal systems based on the heat current method. (15th January 2021)

• Record Type: Journal Article
• Authors: Zhao, Tian; Chen, Xi; He, Ke-Lun; Chen, Qun
• Is Part Of: Energy. Volume 215(2021)Part A
• Publication Date: 2021-01-15
• Subjects: Heat current method -- Thermal systems -- Hierarchical and categorized algorithm -- Calculation robustness -- Computational efficiency; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.119105
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: A novel algorithm for thermal system simulation named hierarchical and categorized (H&C) algorithm is proposed based on the physical and mathematical categorization of system constraints, and the iterations for nonlinear implicit constraints can be minimized. Besides, it includes not only energy and mass balance equations but also the constraints of heat transfer, heat-work conversion, and fluid flow processes. The algorithm is first presented using an example of the Brayton cycle. Next, a complex and practical triple-pressure heat recovery power generation system is simulated using both the proposed algorithm and conventional methods to validate the H&C algorithm and present its advantages. The calculation performance comparison shows the calculation using the H&C algorithm only requires 14 initial values while using the simultaneous equations method (SEM) requires 80 initial values. Besides, the H&C algorithm also has a much larger convergence range of initial values (deviation of 10%) comparing to SEM (0.5%). Moreover, the level of nested iterations using the H&C algorithm is reduced to 4, while using the sequential modular method is 14. That is, the H&C algorithm presents both much higher efficiency and robustness, and hence it offers a powerful tool for the simulation and optimization of complex thermal systems. Highlights: Propose a hierarchical and categorized algorithm for thermal system simulation. Solve linear topology constraints directly using matrix-based elimination methods. Iterations for nonlinear implicit constraints are reduced to the most degree. The algorithm converges fast with a high robustness for a T-HRPG system. Initial values are reduced by 82.5% compared to the components-oriented approach.