Short Circuit Fault Protection Assisted by Edge Computing for Grid Connected AC Microgrid with Automatic Topological Adaption

With the development of microgrid, the issue of short circuit fault detection and location has become key challenges for the reliable operation of microgrids. Traditional microgrid fault protection schemes often overlook the changes in system topology, but the switching of distributed energy sources (DES) and loads can result in topology change, which impairs the performance of fault detection and location. In this paper, addressing the limitations of existing microgrid fault protection schemes, a microgrid simulation model including a variety of DES is built in MATLAB, and the wavelet energy spectrum transformation is applied for the analysis of short circuit fault with changing microgrid topology. Then, a multi-agent collaborative protection strategy based on edge computing is proposed to achieve short circuit fault detection and location with automatic topology adaption. The concept of edge computing, which is a branch of artificial intelligence (AI) is incorporated for automatic collaboration of agents. Results of simulation experiments with changing topology and multiple types of short circuit fault validate the feasibility of the proposed method.