An Early Warning Algorithm for Operational Reliability of Microgrid Power Systems Based on FCM Clustering and Dubins Path Planning

Abstract

Microgrid is an integrated distributed energy and load energy system, and its operation status is affected by many factors. In order to comprehensively monitor the operation status in the complex and changing microgrid environment and improve the comprehensiveness and accuracy of microgrid power reliability warning, this paper designs a microgrid power system operation reliability warning algorithm based on Fuzzy C-means (FCM) clustering and Dubins path planning. This method uses FCM clustering algorithm to divide the mobile sensing network of microgrid into multiple clustering spaces, calculates node weights by entropy weighting method, and selects cluster heads by combining the residual energy, communication distance and the number of cluster head rounds. In addition, this method utilizes Dubins curve to plan the data collection path between cluster heads to improve the collection efficiency. Experiments show that this method can effectively plan the microgrid data acquisition path and complete the microgrid power reliability warning. At the same time, this method improves the MT capacity and reduces the LOLP and CAIDI of the microgrid, which ensures the reliability of the microgrid.