Abstract
Nowadays, the problem of the proper charging of plug-in hybrid electric vehicles (PHEVs) has become increasingly difficult because there is high uncertainty on both the demand and supply sides of microgrid (MG) systems, which may reduce efficiency and increase the cost of MG systems. Available solutions to these challenges are the application of energy storage systems and energy exchange with the upstream utility grid (UUG). However, uncoordinated PHEV charging could have adverse effects on MGs, such as increasing the amounts of energy exchanged between the MGs and the UUG as well as decreasing the battery energy storage systems (BESSs) lifetime. This article proposes a smart charging scheme for PHEVs in ac MGs that can simultaneously minimize the energy drawn from the UUG to charge PHEVs and maximize the lifetime of BESSs based on a multiobjective optimization algorithm. For proving the validity of the proposed power management strategy (PMS), offline digital time-domain simulation studies are conducted based on the modified version of the IEEE 33-bus test system. The obtained results are compared with the results of other previously reported PMSs, which show that by increasing the output power of DER units (even when the penetration level of PHEVs increases), the proposed PMS can ensure proper charging of PHEVs while improving the lifetimes of BESSs and decreasing the energy drawn from the UUG.
Original language | English |
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Pages (from-to) | 4907-4917 |
Number of pages | 11 |
Journal | IEEE Systems Journal |
Volume | 15 |
Issue number | 4 |
DOIs | |
Publication status | Accepted/In press - 2020 |
Keywords
- Batteries
- Battery lifetime
- distributed energy resources
- energy exchange
- Energy exchange
- energy management
- Generators
- grid-to-vehicle
- microgrid (MG)
- multiobjective optimization
- Optimization
- plug-in hybrid electric vehicle (PHEV)
- renewable energy resources (RERs)
- Uncertainty
- US Department of Defense
- Vehicle-to-grid
- vehicle-to-grid
ASJC Scopus subject areas
- Control and Systems Engineering
- Information Systems
- Computer Science Applications
- Computer Networks and Communications
- Electrical and Electronic Engineering