Optimal Locating of Electric Vehicle Charging Stations by Application of Genetic Algorithm
Abstract
:1. Introduction
2. Charging Modes for EVs Charging Stations
- Mode 1: Charging refers to the connection of an EV to the AC supply network through a single phase AC line not exceeding 250 V AC or a three phase AC line not exceeding 480 V AC at 50–60 Hz, using national plug and socket system not exceeding 16 A with protective earth conductors, depending on the country and standardization. This low power vehicle charging mode is the slowest mode and can refill a battery overnight reaching full capacity before morning. This type of overnight recharge ensures a low electric load for the grid and the car is recharged economically using a low cost night rate power. This recharging mode is mainly used at home and office, since no additional infrastructures are required.
- Mode 2: Charging refers to the connection of an EV to the AC supply network with the same voltage limits as for Mode 1, using standard wall sockets and plugs not exceeding 32 A with protective earth conductors. The difference with Mode 1 consists in the fact that the vehicle inlet and connector present a control pin. The supply network side of the cable does not require a control pin as the control function is provided by an integrated control box with the further function of in cable protection device. This recharging mode is primarily used for dedicated private facilities.
- Mode 3: Charging refers to the connection of the EV to the AC supply network using an Electric Vehicle Supply Equipment (EVSE), not exceeding 63 A, where the control pilot function is extended from Mode 2 to control equipment permanently connected to the AC supply. In this case, connectors with a group of control and signal pins are required for both sides of the cable. This recharging mode is typical of public charging stations and is generally supplied from three-phase AC mains at 50/60 Hz. It is also called “semi-fast” charging solution since it is possible to charge a battery in few hours when the driver is at work or during every day activity.
- Mode 4: It has been implemented by the CHAdeMO consortium and is characterized by the use of off-board chargers where the control pilot function is extended also to the equipment permanently connected to the AC supply. The supply AC power is converted in the charging station to DC and the plug ensures that only a matching electric vehicle can be connected. Typical charging times of Mode 4 are in a range from 20 to 30 min. In this case, the charging time is limited by the allowable current of 125 A and voltage of 500 V of the CHAdeMO standard connector.
3. Description of Genetic Algorithm
4. Optimization Performance by Genetic Algorithm
Objective Function Optimizer
- Mode 2: It is a slow charging mode applied by a household type socket-outlet with an inner cable protection component in AC.
- Mode 3: It is a medium to fast speed charging mode utilizing a specific EV socket-outlet with control and protection function installed in AC.
- Mode 4: It is an ultra-fast charging mode with an external charger in DC.
5. Case Study
6. Distance and Costs Obtained in Different Modes
7. Conclusions
Author Contributions
Conflicts of Interest
Nomenclature
CS | Charging Stations |
EV | Electric Vehicle |
GA | Genetic Algorithm |
ICE | Internal Combustion Engine |
C1 | the cost for clients caused within traveling the path |
C2 | the cost of the power consumed within the path |
C3 | the cost of controlling the populace |
C | total costs |
the average constant cost per kilometre for the clients | |
the constant cost of electricity generating per kWh | |
R | the constant cost of contamination controlling for production of kWh |
P | the power utilization of an EV for every kilometre |
the charging stations coordinate | |
, | the settlements coordinate |
φ | latitude |
λ | longitude |
R | earth’s radius |
D | the summation of distances between settlements and the closest charging station |
N(t) | estimated number of electric vehicles |
calculated number of charging stations | |
W | the acquired electric vehicles’ power consumption per day |
µs | the balancing factor |
Ps | the charging station’s power |
the required average time for recharging | |
the electric vehicle’s average power consumption | |
the average number of charge cycles in a day | |
an electric vehicle’s power consumption | |
the average distance that client travels per day |
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Charging Mode | Max Current per Phase | Charging Time | Vehicle Battery Charger |
---|---|---|---|
Mode 1 | 16 A | 4–8 h | On Board |
Mode 2 | 32 A | 2–4 h | On Board |
Mode 3 | 63 A | 1–2 h | On Board |
Mode 4 | 400 A DC | 5–30 min | Off Board |
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Akbari, M.; Brenna, M.; Longo, M. Optimal Locating of Electric Vehicle Charging Stations by Application of Genetic Algorithm. Sustainability 2018, 10, 1076. https://doi.org/10.3390/su10041076
Akbari M, Brenna M, Longo M. Optimal Locating of Electric Vehicle Charging Stations by Application of Genetic Algorithm. Sustainability. 2018; 10(4):1076. https://doi.org/10.3390/su10041076
Chicago/Turabian StyleAkbari, Milad, Morris Brenna, and Michela Longo. 2018. "Optimal Locating of Electric Vehicle Charging Stations by Application of Genetic Algorithm" Sustainability 10, no. 4: 1076. https://doi.org/10.3390/su10041076
APA StyleAkbari, M., Brenna, M., & Longo, M. (2018). Optimal Locating of Electric Vehicle Charging Stations by Application of Genetic Algorithm. Sustainability, 10(4), 1076. https://doi.org/10.3390/su10041076