Open AccessIntelligent modeling method of energy hub based on directed multi-graph
Author(s) -
Qingsen Cai,
Xingqi Luo,
Chunyang Gao,
Peiyu Zhao,
Peng Wang
Publication year - 2022
Publication title -
thermal science/thermal science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 43
eISSN - 2334-7163
pISSN - 0354-9836
DOI - 10.2298/tsci210223251c
Subject(s) - adjacency matrix , computer science , multigraph , energy (signal processing) , electricity , thermal energy , graph , simulation , electrical engineering , theoretical computer science , engineering , mathematics , statistics , physics , quantum mechanics
An energy hub, consisting of a combination of electricity, heat power, cooling power, natural gas, and other energy sources, is considered a key component of the energy internet. It requires quick and accurate optimization and control as well as a standardized and programmable model. This study proposes an intelligent modelling method based on a directed multigraph. This method starts from an input-output model and then establishes a directed multigraph in which a vertex indicates energy and an edge indicates energy conversion equipment and its parameters. Then, an adjacency matrix is obtained by processing and simplifying the directed multigraph. This adjacency matrix is searched using an intelligent algorithm to obtain the coupling matrix model of the energy hub. A hydrodynamic laboratory consisting of electricity, natural gas, heating, and cooling energy is used as a case study to verify the reliability and accuracy of the modelling process and to provide standardized data for deep learning uses in the energy internet. The obtained results show that the proposed method can quickly and effectively establish the energy hub model. This method is also effective when an energy storage device is added to or removed from the energy hub.