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Reza Hemmati

Reza Hemmati

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: Faculty ofٍٍ Electrical Engineering
Address: Imam Khomeini Highway, Kermanshah, Iran, Postal Code: 6715685420
Phone: 083-38305001

Research

Title
Stochastic model for electric vehicle charging station integrated with wind energy
Type
JournalPaper
Keywords
Battery energy storage system; Electric distribution network; Electric vehicle charging station; Multiple charging infrastructure
Year
2020
Journal Sustainable Energy Technologies and Assessments
DOI
Researchers Hasan Mehrjerdi ، Reza Hemmati

Abstract

This paper designs optimal charging facility and capacity for electric vehicle charging station. The charging facility is modeled containing fast, intermediate, and slow speed chargers. The nominal powers of these chargers are determined. The charging station is linked to the utility grid and it is supplied by wind energy and the energy storage devices. The optimal sizing and operation of storage system are optimized. The electrical grid is strengthened by line reinforcement. The uncertainty of wind power is included and dealt by stochastic programming. The model is expressed as stochastic mixed integer linear programming and solved by GAMS toolbox. The results demonstrate that the rated powers of quick, intermediate, and slow speed chargers are optimized on 116, 84, and 52 kW, respectively. The power of quick charger is 27% more than the intermediate one and the intermediate charger needs about 38% larger power facility compared to the slow speed system. The storage system is designed with rated power equal to 133 kW and it can discharge 85% of its energy during one hour. The lines are reinforced by 183% to supply the energy demand of the charging station. The energy, network reinforcement, and charging facility cover about 70%, 15%, and 12% of total cost. The network without storage system needs about 2% more reinforcement. Reduction of line reinforcement by 30% increases the battery power about 4 times.