Graph-based Key Flowgate Monitoring and Coordinated Control

With a higher proportion of renewable energy sources and increasingly extreme weather conditions, the modern power grid has been confronted with challenges arising from both unstable generation sources and peak demand periods. Various methods have been proposed to identify key flowgates and offer diverse control solutions for instances of overloading. However, there was a lack of research that integrated the entire process, spanning from monitoring key flowgates to implementing corresponding measures. In order to efficiently monitor potential overload issues, this paper presented a method for establishing key transmission flowgates situations and determining appropriate responses at varying levels of overload. Based on a graph database, the study constructed graph models for key flowgates, different sets of strategic responses, and various types of measures such as load shedding, load transfer, and generation adjustments. The measures were specifically ranked based on their types, with sensitivity analyses conducted for each strategy set. To ensure the practicality of each measure, feasibility tests were performed when overload occurred at a key flowgate. By utilizing a graph database, this approach enabled the development of new applications beyond the scope of the traditional power grid database. It provided operators with enhanced monitoring capabilities and coordinated control mechanisms, particularly as problems of key flowgate overloading became more prevalent in the future.