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㶲流作为将耗散拉格朗日流体力学应用于综合能源系统的统一物理量。

Exergy Flow as a Unifying Physical Quantity in Applying Dissipative Lagrangian Fluid Mechanics to Integrated Energy Systems.

作者信息

Xu Ke, Qi Yan, Sun Changlong, Ai Dengxin, Wang Jiaojiao, He Wenxue, Yang Fan, Ren Hechen

机构信息

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.

出版信息

Entropy (Basel). 2024 Sep 14;26(9):791. doi: 10.3390/e26090791.

Abstract

Highly integrated energy systems are on the rise due to increasing global demand. To capture the underlying physics of such interdisciplinary systems, we need a modern framework that unifies all forms of energy. Here, we apply modified Lagrangian mechanics to the description of multi-energy systems. Based on the minimum entropy production principle, we revisit fluid mechanics in the presence of both mechanical and thermal dissipations and propose using exergy flow as the unifying Lagrangian across different forms of energy. We illustrate our theoretical framework by modeling a one-dimensional system with coupled electricity and heat. We map the exergy loss rate in real space and obtain the total exergy changes. Under steady-state conditions, our theory agrees with the traditional formula but incorporates more physical considerations such as viscous dissipation. The integral form of our theory also allows us to go beyond steady-state calculations and visualize the local, time-dependent exergy flow density everywhere in the system. Expandable to a wide range of applications, our theoretical framework provides the basis for developing versatile models in integrated energy systems.

摘要

由于全球需求不断增加,高度集成的能源系统正在兴起。为了掌握此类跨学科系统的基本物理原理,我们需要一个统一所有能源形式的现代框架。在此,我们将修正的拉格朗日力学应用于多能源系统的描述。基于最小熵产生原理,我们重新审视了存在机械和热耗散情况下的流体力学,并提出使用火用流作为跨越不同能源形式的统一拉格朗日量。我们通过对一个一维电 - 热耦合系统进行建模来说明我们的理论框架。我们在实空间中绘制火用损失率,并获得总火用变化。在稳态条件下,我们的理论与传统公式一致,但纳入了更多物理考量,如粘性耗散。我们理论的积分形式还使我们能够超越稳态计算,并可视化系统中各处局部的、随时间变化的火用流密度。我们的理论框架可扩展到广泛的应用领域,为开发集成能源系统中的通用模型提供了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/12bf/11431294/9210adfcf6d1/entropy-26-00791-g001.jpg

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