Discrete optimization of upgrade scheduling

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).

Name thesis:degree_name

Master of Science (MSc)

Discipline thesis:degree_discipline

Modelling and Computational Science

Grantor

University of Ontario Institute of Technology

Year dc:date.issued

2022

Author dc:creator

• Smith, Derick

Advisors dc:contributor.advisor

• van Veen, Lennaert
• Hoornweg, Daniel

• Climate action
• Green transition
• Electrification
• Optimization
• Operational research

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10155/1522

OAI identifier oai:identifier

oai:ontariotechu.scholaris.ca:10155/1522