Energy resilience with input-output linear programming model

In this thesis, we develop quantitative frameworks to model the concept of energy resilience in energy-economic systems under an uncertain environment combining linear programming and input-output techniques. First, we propose an energy import resilience index by examining the maximum level of energy imports reduction that the economy can endure without sacrificing domestic demands. A mixed integer programming model is then developed to compute the resilience index efficiently. Second, we develop a target-based optimization model with input-output analysis to study the energy-economic recovery resilience of an economy by evaluating the minimum level of recovery investments required to restore production levels so that total economic impacts are acceptable over a stipulated post-disruption duration. Lastly, we propose a multi-regional input-output linear programming model to study the regional energy resilience of a many-region economy by analyzing the inter-sectoral and inter-regional interdependency among regions under the uncertain production disruptions.