GDN-Based Bottlenecks Detection Method for Renewable Energy Integration Within Electric-Thermal Coupling Systems

As the integration of renewable energy into power systems at high proportions increases, the issue of its consumption has become more prominent. However, in complex power systems, there may be various factors restricting the consumption of renewable energy, and quantifying and identifying the bottlenecks within the system becomes a meaningful and challenging task. To address this issue, this paper proposes the use of the Graph Deviation Network (GDN) method to detect consumption bottlenecks in complex power systems. The study focuses on an electric-thermal coupling system that includes Combined Heat and Power (CHP) units and electric boilers. The proposed method can accurately locate the factors that constrain renewable energy consumption among a large number of time-varying variables. Simulation results validate the effectiveness of the proposed method.