Effect of trip chaining on microgrid placement and communities' infrastructure service access burden

Natural disasters in recent years have highlighted the importance of, and continuing need for, investment in infrastructure resilience. One way to increase resilience after disasters is to install microgrids so that some services can be provided to local communities during recovery. This thesis describes a mixed integer linear program for equitably siting microgrids according to travel distance and community resources. The travel distances can be calculated using either single-destination naive trips, or optimal solutions to the generalized traveling salesperson problem (GTSP) to support multi-destination trips. However, this microgrid siting method is impractical at scale without access to computing resources currently difficult to access "off the shelf." We propose a heuristic procedure, based on spanning trees, for calculating trip distances and the burden associated with them for a given set of facilities and a graph network. This procedure can be used to evaluate a given candidate microgrid placement scenario. We present a case study showing that this heuristic is a better approximation of GTSP-based distance and burden than the naive procedure when calculating multi-destination trips. Our heuristic presents a more nuanced alternative to the naive procedure without resorting to repeatedly solving the GTSP to underlie calculations of burden.U of I OnlyAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD syste