Topological partition based multi-energy flow calculation method for complex integrated energy systems. (1st April 2022)

• Record Type: Journal Article
• Authors: Hu, Qinran; Liang, Yiheng; Ding, Haohui; Quan, Xiangjun; Wang, Qi; Bai, Linquan
• Is Part Of: Energy. Volume 244(2022)Part B
• Publication Date: 2022-04-01
• Subjects: Integrated energy system -- Multi-energy flow calculation -- Topological partition; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.123152
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Multi-energy flow (MEF) calculation is essential for analyzing integrated energy systems (IES) with electricity, gas, and heat. However, for some hybrid-topology IES, conventional MEF calculation methods are hard to converge due to the complex topological structure. To this end, this paper proposes a topological partition based MEF calculation method. First, based on topological structure, the proposed method divides the original system into multiple blocks with only radial or looped topologies, and solves each block with suitable algorithms. This improvement can accelerate the calculation process and broaden the initial solutions range. Second, the proposed method sets the proper balance node of each block such that the convergence of each block becomes independent. This enables the non-convergent blocks can be identified easily. Third, the proposed method sets isobarometric nodes to get equivalent topology reconstruction, which makes the MEF calculation applicable for certain complex systems. Finally, a case study on the IES of Yangzhong City shows the effectiveness of the proposed method. Highlights: This paper proposes a topological partition based multi-energy flow (MEF) calculation method. Complex integrated energy system is partitioned into smallest possible blocks with unique topology. Proper algorithms are determined based on the type of blocks which accelerate MEF calculation. Compared with previous works, the proposed method holds better feasibility for complex systems.