# Energy Trading with Electric Vehicles in Smart Campus Parking Lots
## 4 Simulation Results
### Electric Vehicle Model  
Real data for vehicles' arrivals and departures were collected on a weekday (Tuesday 15 May 2018) from 6:00 a.m. until 18:30 p.m. at the parking lot of engineering building 2-7 (CBNU-PL3), as shown in Figure 5. CBNU-PL3 serves faculty members, employees, and students. The arrival and departure times were based on working hours and student class schedules.  
Different brands for electric vehicles in South Korea were considered based on Ref. [15]. The specifications of electric vehicles are given in Table 2. The amount of selling/buying energy of each vehicle was considered to be 50 percentage of the battery capacity.  
Table 3 shows the electric vehicle charging tariff by KEPCO. The electric vehicle charging tariff is different based on the time period (off-peak, mid-peak and on-peak) and the season (summer, spring,  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Vehicle Model** & **Battery Capacity** & **Fuel Economy (Km/kWh)** & **Release Year** \\ \hline SOUL & 27 kWh & 5.0 & 2014 \\ LEAF & 24 kWh & 5.2 & 2014 \\ SM3 Z.E. & 22 kWh & 4.4 & 2013 \\ BMW i3 & 18 kWh & 5.9 & 2014 \\ RAY & 16 kWh & 5.0 & 2012 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Electric vehicle specification.  
Figure 4: Campus parking lots at Chonbuk National University, Jeonju Campus, South Korea.  
Figure 5: Typical parking utilization during weekdays (CBNU-PL3), 15 May 2018.  
fall and winter) [14]. We assumed that selling/buying prices were randomly selected based on KEPCO electric vehicle charging tariff in the range of [50, 200] KRW.  
Different scenarios were considered for energy trading with respect to the load profile of engineering building 2-7 shown in Figure 6, and the minimum and maximum power consumption given in Table 4. These scenarios were as follows: (a) Scenario (1)--a standalone parking lot with 10 charging stations and energy trading of 50 kWh, (b) Scenario (2)--two parking lots with 20 charging stations and energy trading of 100 kWh, (c) Scenario (3)--four parking lots with 40 charging stations and energy trading of 200 kWh, and (d) Scenario (4)--eight parking lots with 80 charging stations and energy trading of 400 kWh. Table 5 shows a list of the simulation scenarios. We assumed that the excess energy from electric vehicles could support the peak demand of university buildings. The feeding of excess power from electric vehicles to the grid was not considered in this work.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Day**} & \multicolumn{2}{c}{**Power Consumption (kW)**} \\ \cline{2-3}  & **Min** & **Max** \\ \hline Tuesday & 75 & 152 \\ Wednesday & 77.8 & 144.6 \\ Thursday & 79.7 & 243 \\ Friday & 72.6 & 131.1 \\ Saturday & 78 & 102.5 \\ Sunday & 74.7 & 101.8 \\ Monday & 77.8 & 150.5 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Power consumption of engineering building 2–7 (8 May 2018–14 May 2018).  
Figure 6: Load profile of engineering building 2–7 from 8 May 2018 to 14 May 2018.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Time**} & \multirow{2}{*}{**Classification**} & \multicolumn{4}{c}{**Energy Charge (KRW/kWh)**} \\ \cline{3-5}  & & **Summer** & **Spring/Fall** & **Winter** \\ \hline Off-Peak & & 57.6 & 58.7 & 80.7 \\ Mid-Peak & Low voltage & 145.3 & 70.5 & 128.2 \\ On-Peak & & 232.5 & 75.4 & 190.8 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Electric vehicle charging tariff [16].