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Design+ EV charging capacity through queuing model

Figure 3. Distribution fitting for vehicle arrival interval frequency at Figure 5. Charging power distribution
charging stations
service system are first-come-first-served. The system
does not impose a limit on the queue length of charging
vehicles, provided that the vehicles entering and leaving the
public fast-CS are in equilibrium. Two key parameters of
the queuing system are a random variable describing the
time between customer arrivals and a random variable
describing the service time. In the charging service system,
these two parameters are a random variable describing
the time interval between the arrival of an EV at a public
fast-CS and a random variable describing the time at which
an EV receives charging service, respectively. These two
random variables usually conform to specific probability
distributions. After the statistical analysis of the arrival
time interval and charging duration in the actual operation
data of a CS in Hohhot City as described in Section 2.2, the
time interval for EVs to arrive at the public fast-CS obeys
Figure 4. Distribution of charging duration
the negative exponential distribution, and the time for
EVs to receive charging service obeys normal distribution.
considers various uncertainties in the EV charging process. The number of charging equipment in the public fast-CS
1
The number of charging devices at public fast-CS is limited. is assumed to be s. According to the queuing theory, the
During peak charging hours, EV users may need to queue queuing model of the charging service system is M/G/s. The
up to receive charging services. CS can be considered a schematic diagram of the charging service system is shown
queuing system in which customers are represented by in Figure 6.
EVs, where reception corresponds to charging devices and
The operation indicators of the charging service system
providing service means charging. Its operation logic is: include service intensity, average queue length, average
When the charging vehicle arrives at the CS, if the charging waiting time, and so on. By analyzing the calculation of the
equipment is available, the vehicle directly selects the charging service system service indicators, we can improve
charging equipment for charging. If the charging equipment the structure of the charging service system to optimize the
is all occupied during the peak period, the charging vehicle key indicators of the charging service system and better meet
needs to queue up and wait for the completion of the service the needs of users. The premise of the charging service system
of the vehicle in charging to accept the service. The process is that the number of EVs entering the public fast-CS and the
of charging vehicle accepting service is a queuing process, number of EVs leaving the public fast-CS are equal, that is, the
so the charging service system can be studied according service system can achieve dynamic equilibrium. Equation I
to the queuing theory. The service rules of the charging is the equilibrium equation of the charging service system.

Volume 2 Issue 2 (2025) 5 doi: 10.36922/dp.4225