Discrete optimization of upgrade scheduling

Abstract

A primary objective of the mission to meet climate change goals of reducing greenhouse gas (GHG) emissions is to transition from fossil fuels to zero-emission energy. Fossil fuel production and transportation account for approximately half of the GHG emissions in Canada, making transitioning to zero-emission vehicles (ZEV) a climate action cornerstone. However, a 100% ZEV transportation system is beyond the capacity of Canadian electrical infrastructure in some areas, and the cost to upgrade these systems will be significant. The null hypothesis of this study is that there does not exist an approach to upgrades that optimally reduces the financial burden; conversely, the alternative hypothesis is that such an approach does exist. Mathematical rigour confirms the alternative hypothesis (with assumptions). Computational simulations reject the null hypothesis. The overall average of cost savings within satiable constraints (a subset of generated constraints in proportion to upgrade costs) is 34.5% (m) ± 18.0% (sv).