Return to search

Power grid planning for vehicular demand: forecasting and decentralized control

Temporal and spatial distribution of incoming vehicular charging demand is a significant challenge for the future planning of power systems. In this thesis the vehicular loading is-sue is categorized into two classes of stationary and mobile; they are then addressed in two phases.
The mobile vehicular load is investigated first; a location-based forecasting algorithm for the charging demand of plug-in electric vehicles at potential off-home charging stations is proposed and implemented for real-world case-studies. The result of this part of the re-search is essential to realize the scale of fortification required for a power grid to handle vehicular charging demand at public charging stations.
In the second phase of the thesis, a novel decentralized control strategy for scheduling vehicular charging demand at residential distribution networks is developed. The per-formance of the proposed algorithm is then evaluated on a sample test feeder employing real-world driving data. The proposed charging scheduling algorithm will significantly postpone the necessity for upgrading the assets of the network while effectively fulfilling customers’ transportation requirements and preferences. / October 2014

Identiferoai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/23891
Date03 1900
CreatorsGhias Nezhad Omran, Nima
ContributorsFilizadeh, Shaahin (Electrical and Computer Engineering), Rajapakse, Atula (Electrical and Computer Engineering) Leblanc, Alex (Statistics) Crow, Mariesa L. (Electrical and Computer Engineering, Missouri University of Science and Technology)
PublisherIEEE Transactions on Smart Grid
Source SetsUniversity of Manitoba Canada
Detected LanguageEnglish

Page generated in 0.0024 seconds