## 5 Numerical Simulation Results
### Application of Dynamic Time-Of-Use Pricing Strategy for EVs  
#### 5.2.1 Simulation of Dynamic Time-Of-Use Charging Price and Participation Degree of Different EVs  
The dynamic charging price can reflect the short-term fluctuation of supply and demand in the micro-grid, which can effectively guide the EV users to make arrangement for charging, so as to stabilize load fluctuations in the micro-grid, promote the accommodation of renewable energy, and reduce the purchased electricity. Thus, based on the load curve obtained by guiding the charging behaviors of EVs with peak-valley price, we solve and publish the corresponding charging price in each time period through the proposed dynamic time-of-use pricing strategy, as shown in Figure 6a. In the simulation, the proportions of normal, urgent, and economical EV users in the micro-grid are set to 45%, 25% and 30%, respectively, in order to fitting the actual operation of the micro-grid. Figure 5: Simulation schematic diagram of the micro-grid. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameters** & **Values** & **Parameters** & **Values** \\ \hline \(C_{i}\)/kWh & 21.6 & \(\eta_{ch}\)/\% & 0.9 \\ \(p_{ch,i}\)/kW & 3.6 & \(E_{c}\)/kWh:km\({}^{-1}\) & 0.139 \\ SOC\({}_{\text{max}}\)/\% & 100.0 & \(SOC_{r,j}\)/\% & 0.6 \\ SOC\({}_{\text{min}}\)/\% & 20.0 & \(S\)/km\({}^{-1}\) & 28.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: EV parameters and other relevant parameters. Figure 6: Simulation of dynamic time-of-use charging price and participation degree of different EVs. (**a**) Dynamic time-of-use charging price of the micro-grid in each period, (**b**) the relationship between dynamic time-of-use charging price and EV actual capacity dispatched, (**c**) the relative participation degree of the three types of EV users in the dispatching periods. Meanwhile, since the controllable capacity of EVs changes within 24 h of the day, the electricity grid will give diverse incentives for the same dispatching demand in different time periods. The degree of response of EV users is related to the dynamic charging price. In order to study the relationship between charging price and the controllable capacity of EVs, the dynamic charging price and the corresponding actual capacity of EVs are simulated and analyzed under different dispatching requirements for each period, and the results are shown in Figure 5(b). Additionally, the EV users with different preferences will choose diverse charging strategies in the face of the same incentive from the electricity grid. In addition, making full use of the choice of EV users is conducive to studying the impact of EV cluster charging behavior on grid dispatching. Therefore, we discuss the participation degree of normal, urgent, and economical EV users in the dispatching period, as shown in Figure 5(c). It can be seen from Figure 5(a) that the non-overlapping portion of the dynamic time-of-use price and the peak-valley price represents the time periods in which the micro-grid has dispatching demands, and stimulates the EV users to transfer the charging load at a preferential price. In the time periods \(T_{26}-T_{38}\) are the most concentrated periods of adjusting the charging price, the specific dispatching periods, and the corresponding price, and these are shown in the window of Figure 5(a). The adjusted charging price for EVs lasts for at least 15 min, which can well reflect the current operating state and the imbalance of supply and demand in the micro-grid. Moreover, the dynamic charging price will be more attractive than the constant peak-valley price, and can fully stimulate the participation of EV users, which makes it easy to realize the management of EV charging load, based on the user satisfaction degree. Figure 5(b) reflects that the micro-grid has dispatching demands in the time periods \(T_{19}-T_{38}\) and \(T_{95}-T_{96}\), in which the grid will gradually decrease the charging price, based on the peak-valley price to call for sufficient EVs.