An integrated ISM fuzzy MICMAC approach for modeling and analyzing electrical power system network interdependencies

Abstract

Despite the attention that the modeling and analyis of infrastructure interdependencies have received over the past two decades, only a small number of methods have been proposed for modeling interdependencies among substations (S/Ss) in electric power system (EPS) networks. For this reason, this paper proposes a novel approach that integrates interpretive structural modeling (ISM) and fuzzy cross-impact matrix multiplication applied to classification (MICMAC). While the ISM provides managers with a holistic visual view of interdependencies among S/Ss, fuzzy MICMAC analysis categorizes the S/Ss in terms of their driving and dependence powers. This categorization offers an advantageous tool for decision makers to distinguish between S/Ss and their mutual associations, which enables them to identify the critical S/Ss. For demonstration, the approach is applied to a model and analyzes the independencies within real EPS S/Ss.