Minimization of net-load variance using smart EV charging algorithm

Simple item page
dc.contributor.advisorChang, Liuchen
dc.contributor.advisorCardenas Barrera, J.
dc.contributor.authorRahman, Afnan Rudabe
dc.date.accessioned2024-03-20T13:53:17Z
dc.date.available2024-03-20T13:53:17Z
dc.date.issued2023-10
dc.description.abstractElectric vehicles (EVs) are developing faster than ever. With the increasing number of EVs and their uncoordinated charging, the additional electric load significantly impacts the distribution grid for low penetration levels. If the EV penetration level reaches a high degree for a specific regional grid, the EV load will cause more significant risks to the grid. In this research, using localized statistical information and the Dichotomous Search Method, a charging algorithm considering the charging priority is proposed to minimize the net-load variance and the negative impacts of EV load on a medium voltage distribution. The charging priority of EVs is defined according to the State of Charge (SoC), the charging time required of individual EVs, and the power generated by the local grid. Each EV is assigned a specific period to charge. This motivates minimizing the demand peak and the valley filling by shifting the EV load.
dc.description.copyright© Afnan Rudabe Rahman, 2023
dc.format.extentxii, 72
dc.format.mediumelectronic
dc.identifier.oclc(OCoLC)1440129415en
dc.identifier.otherThesis 11394en
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/37766
dc.language.isoen
dc.publisherUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineElectrical and Computer Engineering
dc.subject.lcshElectric vehicles.en
dc.subject.lcshBattery charging stations (Electric vehicles)en
dc.subject.lcshElectric power systems.en
dc.titleMinimization of net-load variance using smart EV charging algorithm
dc.typemaster thesis
oaire.license.conditionother
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.Sc.E.

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Afnan Rudabe Rahman - Thesis.pdf
Size:
895.46 KB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.13 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Open Theses & Dissertations