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Virginia Tech

Optimal Charging Scheduling for Electric Vehicles Based on a Moving Horizon Approach

Abstract

dc:description.abstract

The rapid escalation in plug-in electric vehicles (PEVs) and their uncoordinated charging patterns pose several challenges in distribution system operation. Some of the undesirable effects include overloading of transformers, rapid voltage fluctuations, and over/under voltages. While this compromises the consumer power quality, it also puts on extra stress on the local voltage control devices. These challenges demand a well-coordinated and power network-aware charging approach for PEVs in a community. This paper formulates a realtime electric vehicle charging scheduling problem as a mixed-integer linear program (MILP). The problem is to be solved by an aggregator that provides charging services in a residential community. The proposed formulation maximizes the profit of the aggregator, enhancing the utilization of available infrastructure. With prior knowledge of load demand and hourly electricity prices, the algorithm uses a moving time horizon optimization approach, allowing an unknown number of arriving vehicles. In this realistic setting, the proposed framework ensures that power system constraints are satisfied and guarantees the desired PEV charging level within the stipulated time. Numerical tests on an IEEE 13-node feeder system demonstrate the computational and performance superiority of the proposed MILP technique.

Degree

thesis:*
Name thesis:degree_name
M.S.
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Electrical Engineering
Department dc:contributor.department
Electrical and Computer Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Sahani, Nitasha
Chair dc:contributor.committeechair
  • Liu, Chen-Ching
Committee members dc:contributor.committeemember
  • Centeno, Virgilio A.
  • De La Ree, Jamie

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
Language dc:language.iso
en_US

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/10919/96544
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/96544

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Sahani, Nitasha. Optimal Charging Scheduling for Electric Vehicles Based on a Moving Horizon Approach. masters thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/96544