Date of Award

3-12-2020

Publication Type

Master Thesis

Degree Name

M.A.Sc.

Department

Industrial and Manufacturing Systems Engineering

First Advisor

Ahmed Azab

Keywords

Electric vehicles, Fast charging stations, Industrial-scale wind turbines, Micro-wind turbines, power system planning, stochastic program

Rights

info:eu-repo/semantics/embargoedAccess

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Abstract

With the advent of electric vehicles (EVs), charging infrastructure needs to become more available and electricity providers must build additional power generation capacity to support the grid. In siting and sizing of fast charging stations (FCSs), both the distribution network constraints, as well as the traffic network limitations, must be considered because FCSs exist on both levels. Moreover, the siting and sizing of wind-powered distributed generation (WPDG) is a solution to gradually decarbonizing the grid; therefore, reducing our carbon footprint. In addition to providing capacity, they also have other benefits in the distribution network such as reducing transmission losses. In this thesis, a new framework is proposed which successfully implements a novel scoring technique to rate the attractiveness of FCS candidate locations thus, determining the expected FCS demand in each candidate location and uses WPDGs to support that load. A study has been conducted to compare the suitability of industrial-scale turbines versus micro-wind turbines in an urban area. A method for selecting candidate locations for the later has been developed. A stochastic program is proposed to account for the non-deterministic elements of the problem including generic loads, residential electric vehicle loads, FCS loads, and wind speed where they are accounted for collectively using a method called convolution. This comes hand-in-hand with a mixed-integer non-linear programming model that sites and sizes both FCSs and WPDGs with an objective of maximizing profits to incentivize investments. A list of novel constraints has been introduced that connect the traffic network to the power network. The problem is modeled from the perspective of electric utilities but also considers the perspectives of the urban planners and potential investors. A case study was implemented showing how the scoring technique works and the results show that the math model considered all the parameters and respected all the constraints delivering a holistic set of decisions to site and size both FCSs and micro WPDGs in an urban area.

Available for download on Friday, March 12, 2021

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