Multi-objective optimization control of plug-in electric vehicles in low voltage distribution networks
J. García-Villalobos,
I. Zamora,
K. Knezović and
M. Marinelli
Applied Energy, 2016, vol. 180, issue C, 155-168
Abstract:
The massive introduction of plug-in electric vehicles (PEVs) into low voltage (LV) distribution networks will lead to several problems, such as: increase of energy losses, decrease of distribution transformer lifetime, lines and transformer overload issues, voltage drops and unbalances. In this context, this paper proposes a new multi-objective optimization algorithm in order to reduce the mentioned problems. At the same time, users’ interests in terms of charging cost and privacy have been taken into account. The proposed multi-objective optimization is based on minimizing the load variance and charging costs by using the weighted sum method and fuzzy control. The use of vehicle to grid (V2G) concept and load forecast uncertainties have been also considered. Furthermore, an innovative method for mitigating voltage unbalances has been developed. The effectiveness of this methodology has been tested using real data of a LV distribution network, located in Borup (Denmark). Simulation results show that this approach can reduce both energy losses and charging costs as well as it allows a high PEV penetration rates (PEV-PR).
Keywords: Plug-in electric vehicles; Optimal control; Smart charging; Smart grid; Low voltage distribution networks; Vehicle to grid (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261916310406
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:180:y:2016:i:c:p:155-168
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic
DOI: 10.1016/j.apenergy.2016.07.110
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().