## 3 Design of IDPGMFO
### Configuration of Simulation Platform  
The specific detailed configuration of the simulation platform is shown below: the Matlab/Simulink revision for computation and figures drawn is \"Matlab GUI 2016b\"; the major computer configuration is \"Core i7-7700K @ 4.2 GHZ\" and \"Windows 10\"; the display software revision is \"Internet Explorer 11\"; and the data storage software is \"office2019 excel\". Simulation and Verification of EV OCP Optimization for Chinese Economic and Technological Development Zones  
Aiming at the practical EV OCP optimization, both charging user preferences and grid quality should be taken into account. To verify the effectiveness of the algorithm proposed in this work, the simulation experiment is implemented, which takes the preferences of charging users and the power grid quality into account. The proposed IMFO in this paper is used for optimization verification, while the traditional MFO, the IPSO and the IHBA are used for optimization comparison and evaluation. The specific optimization results are shown in Figures 5-11. Figure 5: Iterative convergence curves of each algorithm considering charging user preferences and power grid quality. Figure 8: Schematic diagram of the operation plan curves of charging station 3 considering both charging user preferences and grid quality. Figure 6: Schematic diagram of the operation plan curves of charging station 1 considering both charging user preferences and grid quality. Figure 7: Schematic diagram of the operation plan curves of charging station 2 considering both charging user preferences and grid quality. Figure 11: Node voltage amplitude curves considering both charging user preferences and grid quality. Figure 10: Line loss power curves considering both charging user preferences and grid quality. Figure 9: The overall grid load variation curves considering both charging user preferences and grid quality. Figure 5 is used for evaluating the optimization algorithm ability throughout the whole process. The evolutional generations and fitness values are pure numerical values without units. Figures 6-8 are used to show the final ordered charging planning of charging stations 1-3 obtained by proposed IDPGMFO and comparison optimization algorithms. The unit of power is kW, the unit of time is h, of course, the time total number is 24. Figures 9-11 are used to show the grid side comprehensive performance for the final ordered charging planning obtained by the proposed IDPGMFO and comparison optimization algorithms. The unit of load power and line loss power is kW, while the node number and voltage amplitude are pure numerical values without units. As can be seen from Figure 5, compared with comparison optimization algorithms, the IDPGMFO has a faster global convergence speed and better global convergence accuracy under the condition of taking into account the preferences of charging users and the quality of the power grid. As can be seen from Figures 6-8, compared with comparison optimization algorithms, the improved PSO and the improved honey-badger algorithm used for comparison, the operation plan curves of charging stations 1-3 obtained by the IMFO are more straight, and it is beneficial to reduce line loss power. It can be seen from Figures 9 and 10 that when considering the preferences of charging users and the quality of the power grid, compared with comparison optimization algorithms, the IMFO can better realize \"peak and valley filling\" to effectively ensure the load stability of the power grid and reduce the network loss more significantly. As can be seen from Figure 11, when considering the preferences of charging users and the quality of the power grid, compared with comparison optimization algorithms, the node voltage amplitude of 33 nodes for the planning scheme obtained by the proposed IDPGMFO in this paper belongs to the range of 0.96-1.05, and its fluctuation is small. The specific performance evaluation results for the EV OCP obtained by proposed IDPGMFO and comparison optimization algorithms are listed in Table 2 below.