Energy-economic recovery resilience with Input-Output linear programming models

In this work we develop a novel Input-Output linear programming model to study the energy-economic recovery resilience of an economy by analyzing the relationships between energy production disruption, impacts on sectoral production and demands, and post-disruption recovery efforts. The proposed model evaluates the minimum level of recovery investments required to restore production levels so that total economic impacts are acceptable over a stipulated post-disruption duration. It is assumed that disruptions are uncertain and can occur at different sectors and possibly simultaneously. The optimization model is then solved using a cutting plane method which involves computing a small sequence of mixed integer programming problems of moderate dimensions. A case study using China 2012 Input-Output data is performed, and we demonstrate the model's ability to uncover critical inter-sectoral dependencies at different disruption levels. This provides decision-makers with important information in evaluating and improving the energy-economic resilience in a systematic and rigorous manner.

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