A Real-Time EV Charging Scheduling for Parking Lots With PV System and Energy Store System
The problem of electric vehicle (EV) charging scheduling in commercial parking lots has become a meaningful study in recent years, especially for the parking lots near the workplace that serve fixed users. This paper focuses on the optimization of the EV charging in the parking lot integrating energ...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8750840/ |
id |
doaj-31e9cf1f926343259eaa0d297ae41ccf |
---|---|
record_format |
Article |
spelling |
doaj-31e9cf1f926343259eaa0d297ae41ccf2021-03-29T23:22:26ZengIEEEIEEE Access2169-35362019-01-017861848619310.1109/ACCESS.2019.29255598750840A Real-Time EV Charging Scheduling for Parking Lots With PV System and Energy Store SystemWei Jiang0Yongqi Zhen1https://orcid.org/0000-0001-9675-4998College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai, ChinaCollege of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai, ChinaThe problem of electric vehicle (EV) charging scheduling in commercial parking lots has become a meaningful study in recent years, especially for the parking lots near the workplace that serve fixed users. This paper focuses on the optimization of the EV charging in the parking lot integrating energy storage system (ESS) and photovoltaic (PV) system. A smart charging management system is first established. The charging optimization problem is formulated as a cost minimization problem. Then, grey wolf optimizer (GWO) is introduced as a method to find the optimal solution. Considering the constraint conditions in the optimization problem, an improved binary grey wolf optimizer (IBGWO) is proposed, which can improve the convergence speed and optimization accuracy. Finally, a real-time EV charging scheduling strategy based on short-term PV power prediction and IBGWO is proposed. Several cases are simulated to analyze the performance of the proposed strategy. The experimental results show that the proposed IBGWO is superior in solving the proposed charging scheduling problem compared with other meta-heuristic algorithms. Moreover, the proposed strategy can effectively improve the utilization rate of the PV power and reduce the electricity cost of operators.https://ieeexplore.ieee.org/document/8750840/Electric vehiclecharging managementreal-time strategygrey wolf optimizer |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wei Jiang Yongqi Zhen |
spellingShingle |
Wei Jiang Yongqi Zhen A Real-Time EV Charging Scheduling for Parking Lots With PV System and Energy Store System IEEE Access Electric vehicle charging management real-time strategy grey wolf optimizer |
author_facet |
Wei Jiang Yongqi Zhen |
author_sort |
Wei Jiang |
title |
A Real-Time EV Charging Scheduling for Parking Lots With PV System and Energy Store System |
title_short |
A Real-Time EV Charging Scheduling for Parking Lots With PV System and Energy Store System |
title_full |
A Real-Time EV Charging Scheduling for Parking Lots With PV System and Energy Store System |
title_fullStr |
A Real-Time EV Charging Scheduling for Parking Lots With PV System and Energy Store System |
title_full_unstemmed |
A Real-Time EV Charging Scheduling for Parking Lots With PV System and Energy Store System |
title_sort |
real-time ev charging scheduling for parking lots with pv system and energy store system |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
The problem of electric vehicle (EV) charging scheduling in commercial parking lots has become a meaningful study in recent years, especially for the parking lots near the workplace that serve fixed users. This paper focuses on the optimization of the EV charging in the parking lot integrating energy storage system (ESS) and photovoltaic (PV) system. A smart charging management system is first established. The charging optimization problem is formulated as a cost minimization problem. Then, grey wolf optimizer (GWO) is introduced as a method to find the optimal solution. Considering the constraint conditions in the optimization problem, an improved binary grey wolf optimizer (IBGWO) is proposed, which can improve the convergence speed and optimization accuracy. Finally, a real-time EV charging scheduling strategy based on short-term PV power prediction and IBGWO is proposed. Several cases are simulated to analyze the performance of the proposed strategy. The experimental results show that the proposed IBGWO is superior in solving the proposed charging scheduling problem compared with other meta-heuristic algorithms. Moreover, the proposed strategy can effectively improve the utilization rate of the PV power and reduce the electricity cost of operators. |
topic |
Electric vehicle charging management real-time strategy grey wolf optimizer |
url |
https://ieeexplore.ieee.org/document/8750840/ |
work_keys_str_mv |
AT weijiang arealtimeevchargingschedulingforparkinglotswithpvsystemandenergystoresystem AT yongqizhen arealtimeevchargingschedulingforparkinglotswithpvsystemandenergystoresystem AT weijiang realtimeevchargingschedulingforparkinglotswithpvsystemandenergystoresystem AT yongqizhen realtimeevchargingschedulingforparkinglotswithpvsystemandenergystoresystem |
_version_ |
1724189629220913152 |