Nodal-pressure-based heating flow model for analyzing heating networks in integrated energy systems

被引:12
作者
Chen, Dongwen [1 ]
Hu, Xiao [2 ]
Li, Yong [1 ]
Wang, Ruzhu [1 ]
Abbas, Zulkarnain [1 ]
Zeng, Shunqi [3 ]
Wang, Li [3 ]
机构
[1] Shanghai Jiao Tong Univ, Inst Refrigerat & Cryogen, Shanghai 200240, Peoples R China
[2] Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Shanghai 200240, Peoples R China
[3] Guangzhou Power Supply Grp, Syst Operat Dept, Guangzhou 510060, Peoples R China
基金
国家重点研发计划;
关键词
Nodal-pressure-based model; District heating networks analysis and planning; Heating flow; Unified nodal pressure model; Energy transmission loss; Integrated energy system; OPTIMAL POWER-FLOW; NATURAL-GAS; COORDINATED DISPATCH; ELECTRICITY; OPTIMIZATION; OPERATION; STORAGE;
D O I
10.1016/j.enconman.2020.112491
中图分类号
O414.1 [热力学];
学科分类号
摘要
District heating technology has prompted the development of integrated energy systems, where energy flow models have been widely used. However, as heating networks become complicated, the traditional mass flow model fails to provide efficient solutions. This study proposes a novel heating flow model based on nodal pressure in heating networks. First, transmission models based on nodal pressure are formulated. Subsequently, nodal conservation models of mass and heating flow are developed. Further, the transmission and nodal conservation models are combined, and thereby nodal pressure and user load are directly correlated. As the number of variables depends only on the nodes, the resulting model is more efficient at adapting to new network connections when the nodes do not change. Moreover, as loop pressure conservation equations are omitted in this model, fewer iterations are required. Owing to the small relative fluctuations of nodal pressure, initial iteration values can be set more effectively in the solution of the proposed model. A case study was conducted, and it was demonstrated that compared with the traditional mass flow model, the proposed model is more effective in adapting to varying network topologies, and the computational burden is significantly reduced. Moreover, the proposed model can be efficiently applied for analyzing energy transmission loss as well as system planning in integrated powergasheat energy systems.
引用
收藏
页数:16
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