Reinforcement of energy delivery network against natural disaster events

Among all city infrastructures affected by natural disaster events, electric power grid is the most critical one. Most services on which disaster relief efforts depend, rely entirely on the availability of dependable and continuous supply of power. To achieve power grid resiliency against natural disasters, it is first necessary to perform a thorough analysis of interdependencies within the energy delivery network. This paper puts forth a graph-theoretic methodology based on fuzzy cognitive maps that models and analyzes the grid as an interconnected system of elements (i.e., energy resources and loads) that are connected through weighted and directional edges (i.e., lines and feeders). The developed model provides a mathematical framework for the analysis of the power grid during natural disaster events, and is used to devise optimal reinforcement strategies for the grid infrastructure via capacity enhancements and component reinforcement. The problem has been formulated as a constrained quadratic optimization one. The analysis and optimization approach are performed using abstract models so as to ensure the generic nature of the proposed methodology. A case study is presented using the IEEE 34-bus test distribution system. The system is mapped onto the floodplain map of the city of Boulder, CO, and is used to verify the applicability of the proposed methodology for grid reinforcement against flood hazards.