Climate-Adaptive Planning for the Long-term Resilience of Transportation Energy Infrastructure

Abstract

This paper investigates a long-term planning response to the climate-vulnerability of transportation energy infrastructure in the borough of Manhattan, NY. The proposed model represents a hybrid utility-regret function with increasing relative and decreasing absolute risk aversion. Our formulation features a nonlinear stochastic mathematical program in which two-stage decision variables are simultaneously optimized against the motor fuel supply chain’s maximum resilience when stressed or under attack.

 

The separation of pre- and post-event decision variables leads to a two-stage framework: allocating resources according to various resilience-enhancing strategies (the first stage investment decisions, aka asset prepositioning) to maximize the infrastructure resilience when stressed (the second stage network operation decisions). In fact, second-stage decision variables (i.e. operational decisions in time of disaster) are conditioned on decisions made in the first stage.

 

Our results suggest investments in early- and late-stage solutions as a complementary approach with significant weight on immediate actions, despite ongoing proclamations that municipalities and governments should focus their adaptation fund on supporting the deployment of later-stage solutions. The modeling outputs also suggest a decentralized supply chain formation through an early stage deployment of reservoir tanks within the borough of Manhattan.
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