Paper Info
Title
Study on Global Optimization and Control Strategy Development for a PHEV Charging Facility.
Abstract
This paper provides a full study of a photovoltaic (PV)-aided plug-in hybrid electric vehicle (PHEV) charging facility by investigating the two most challenging technical issues: 1) sizing of the local energy storage (LES) unit and 2) control strategies of the facility. First, the paper proposes a method for determining the optimal size of LES for a charging facility. Second, the paper develops a control strategy for the integration of the PHEV charging stations with the proposed LES and PVs. The proposed LES-sizing method, which is based on optimal control theory, minimizes a cost function based on the average value of kilowatt-hour price, irradiance, and PHEVs' usage patterns. A power-loss/temperature-based battery model and a temperature-based charging strategy previously developed by the authors are utilized to determine the optimal LES size. Afterward, with the optimized facility parameters, a detailed circuit model of the charging facility, including PVs, PHEVs, and LES, is constructed with a real-time simulation system. While an experimental setup for this kind of complex and high-cost system was not readily feasible, real-time simulation was carried out to prove the effectiveness of the proposed control strategy. To validate the effectiveness and accuracy of the real-time simulation, control hardware-in-the-loop (HIL) and power-inverter-based experiments have been carried out at the subsystem level.
Year
DOI
Venue
2012
10.1109/TVT.2012.2195787
IEEE T. Vehicular Technology
Keywords
Field
DocType
Batteries,Integrated circuit modeling,Real time systems,Optimization,System-on-a-chip,Equivalent circuits
Energy storage,System on a chip,Optimal control,Global optimization,Electric vehicle,Computer science,Electronic engineering,Sizing,Real-time simulation,Photovoltaic system
Journal
Volume
Issue
ISSN
61
6
0018-9545
Citations 
PageRank 
References 
4
0.95
5
Authors
4
Name
Order
Citations
PageRank
Feng Guo141.97
Ernesto Inoa2182.23
Woongchul Choi3136.67
Jin Wang4264.23