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Moradzadeh, Majid

University of British Columbia

Plug-in electric vehicles (PEVs) and renewable energy sources (RESs) based distributed generation systems have increasingly been popular in recent years aiming to decrease the greenhouse gases (GHG) emissions produced by conventional power plants and internal combustion engine vehicles. The large-scale adoption of PEVs, however, still faces several challenges that need to be thoroughly addressed. Specifically, public and individual charging solutions need to be rapidly deployed to meet the charging requirements of the growing PEV penetration. First, Fast charging stations (FCSs) deployment is required to tackle the otherwise long charging time of PEVs. Second, there is a need to provide adequate access to charging facilities along different highway networks. However, many routes on different highway networks are isolated from the main power grid, where in many cases the expansion of existing power grids to feed charging stations located along these routes may be costly and/or impractical. Third, the growing number of PEVs and the increasing deployment of privately owned home and commercial charging stations can have substantial negative impacts on the electric distribution grid. Motivated by the aforementioned challenges, first, a new comprehensive mixed integer linear programing (MILP) model is proposed for determining the optimal capacity and type of renewable generation and energy storage to minimize the energy costs associated with FCSs, while meeting its performance requirements. Second, a new planning model for fully green charging stations (FGCSs) is investigated and a planning model is proposed for energy storage and renewable energy systems to cover the energy demand of stand-alone charging stations for PEVs entirely using green energy generated by RESs. The proposed models account for generation uncertainties and a wide range of technical and operational characteristics of different energy storage technologies and allows for choosing the optimal combination of ESSs and RESs. Finally, a computationally feasible demand response program framework to accommodate the integration of PEVs in residential distribution systems using the flexible loads already existed at the end users is investigated. The proposed strategy is able to schedule appliances with temporal, inter-temporal, and spatial constraints whose models are derived from physics principles and the participants’ information privacy is preserved.

Text

2023-08-31

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/82666

Electrical Engineering

University of British Columbia

UBCO

http://creativecommons.org/licenses/by-nc-nd/4.0/