Introducing a Novel Clustering Method for Distribution Networks to Enhance Network Performance and Ensure Load Supply in the Event of Contingencies: A Fuzzy Function-Based Approach

To improve the resiliency of the distribution system during normal and emergency conditions, approaches for planning and operating are required so that the network can supply more loads during normal and emergency times. Thus, with the cellular approach in network planning, according to the production and consumption, the cellularization of the network to supply more loads can be considered. Consequently, the identification of energy cells and the boundary of energy cells is a challenge in the planning issue. This article achieves and identifies the maximum number of energy cells and the border among energy cells of distribution systems. The proposed objective functions for solving the resilience problem include the number of supplied loads and the number of unsupplied loads in normal or abnormal conditions. Furthermore, the eigenvalues and eigenvectors of the Graph Laplacian matrix of the distribution network are used to identify the maximum number of cells in the distribution network and the boundary among the generated cells, considering the prediction of distributed generation and consumption load based on fuzzy modeling. To show the efficiency of the proposed method, the test systems of 69 and 118 buses have been simulated. The results prove the proper performance of the proposed method.