Optimization of Resilient Biofuel Infrastructure Systems under Natural Hazards

Abstract

The writers aim to develop a new optimization framework that integrates resilience in biofuel infrastructure systems planning, which provides a proactive solution in mitigating the impacts of natural hazards on infrastructure systems. A novel, multiobjective stochastic mixed-integer programming model is developed to establish a biofuel infrastructure system that is effective and resilient in hedging against potential hazards through integrating four dimensions of resilience, as follows: (1) robustness, (2) rapidity, (3) redundancy, and (4) resourcefulness. As a case study, the model is used to evaluate the infrastructure requirements for cellulosic ethanol production from biomass wastes in California, which is prone to seismic hazards. An average of 19% overall system cost reduction can be achieved under seismic hazards by using the developed model over common engineering methods without resilience consideration.