## 5 Numerical Simulation Results
### Application of Dynamic Time-Of-Use Pricing Strategy for EVs
#### 5.2.2 The Economic Research in Three Scenarios  
For the moment, the price mechanism for EV charging mainly includes fixed price, peak-valley price, and dynamic time-of-use price. In order to validate the effectiveness of the dynamic time-of-use price proposed in this paper in guiding the charging behaviors of EVs, the variation of the micro-grid load curves under uncoordinated charging, coordinated charging leaded by peak-valley price, and dynamic time-of-use price scenarios, are studied, as shown in Figure 7. The three charging situations in the figure show the different total charging energy of EVs, which is due to different target setting of the three charging situations, but all of the charging energy can satisfy the daily charging requirements of the EVs. In the uncoordinated charging mode, the EV users charge the batteries according to their own living habits, which will increase the peak-valley difference of the micro-grid and the electricity purchased from the external power system, thus resulting in a significant raise in the operation costs and the low utilization rate of renewable energy. Under the guidance of peak-valley price, the EV cluster aggregator will arrange for EVs to charge at valley-time, in order to reduce the charging fees, but this may cause a surge of load during the centralized charging periods. When the charging behaviors finish, the load will drop sharply, which has a huge impact on the safe and stable operation of the micro-grid. After adopting dynamic time-of-use price, the EV cluster aggregator makes arrangements for the EVs to charge, with the goal of balance between supply and demand of the micro-grid. Simulation results show that the charging behaviors of EV cluster can fully track the output of distributed generators under the guidance of dynamic time-of-use price, aiming to effectively stabilize the load fluctuation, improve the utilization rate of renewable energy, and reduce the electricity purchased from external power system. Furthermore, by calculating the excess generation for distributed generators and electricity purchased from the external power system in different scenarios, the independence and economy of the operation of the micro grid under the three charging scenarios are further analyzed. In order to illustrate that the implementation of dynamic time-of-use price for EV charging will improve the  
Figure 7: The load curves of the micro-grid in three charging situations of EVs. economics of EV users, the unit charging cost of EV users under three charging situations is simulated. In addition, for the sake of simplicity, the main variable costs such as the penalty fees for abandonment of wind, photovoltaic, and electricity purchasing charges in three scenarios are compared. It is assumed that the penalty fees for abandonment of wind and photovoltaic are 0.88 yuan/kWh [31]. The above simulation results and the respective decline rates after the implementation of peak-valley price and dynamic price compared with uncoordinated charging are shown in Tables 3 and 4 respectively. It can be seen from Tables 3 and 4 that the excess generation for distributed generators and electricity purchased from the external power system are the highest among the three charging scenarios when EVs are charged uncoordinatedly, which indicates that the micro-grid has a large imbalance between power supply and demand. Moreover, the unit charging cost of EV users and the main variable costs of the micro-grid are also the highest, which reflects that the low utilization rate of renewable energy at night and the charging behaviors of EV users during the peak-load periods result in a continuous increase of the charging load. In summary, from the decline of the four indicators, the operational independence under the dynamic time-of-use price is the highest, which does not only improve the utilization of renewable energy, but could also reduce the electricity purchased from the external power system and enhance the economy of the micro-grid.