Intelligent modeling method of energy hub based on directed multi-graph

Abstract

An energy hub (EH), 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 (EI). It requires quick and accurate optimization and control as well as a standardized and programmable model. This study proposes an intelligent modeling 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 EH. 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 modeling process and to provide standardized data for deep learning uses in the EI. The obtained results show that the proposed method can quickly and effectively establish the EH model. This method is also effective when an energy storage device is added to or removed from the EH.