## 3 Design of IDPGMFO
### Data Sources for an EV OCP Optimization Example  
In this work, the EV OCP optimization example about the Dalian bonded area scenic spot is taken as the research object. The Dalian bonded area scenic spot is one of the Chinese economic and technological development zones. The EV OCP optimization simulation environment is built with real data sources for the Dalian bonded area scenic spot. IEEE-33 network is a standard IEEE network, and IEEE-33 network topology with security and steadiness is popularly used in electric vehicle traffic network construction [11]. In this paper, IEEE-33 network topology is selected. There are 33 nodes in the smart grid of this district, and the type, applicable voltage range and voltage phase of each node have been identified, and the resistance between each node is known. The specific load data of the IEEE-33 smart grid system are shown in Table 1, and the specific the IEEE-33 smart grid system diagram is shown in Figure 4.  
Figure 3: Schematic diagram of IDPGMFO calculating process.  
In Table 1, the head node and end node, active resistance and active resistance, active power and active power of the end node for a specific branch have been listed.  
In Figure 4, the numbers are Branch No. listed in In Table 1.  
In the smart grid of the community, the charging station control center is set up at the 15 th, 18 th and 32 th nodes, which supply electric energy to the smart charging piles in the area under their jurisdiction for charging electric vehicles.  
In actuality, to implement simulation verification of EV OCP optimization for Chinese economic and technological development zones, the data sources for EVs charging must be forecast in advance. However, precise forecast results are very difficult to forecast, and next to impossible to achieve. So, in this paper, the real history results of EVs charging for the Dalian bonded area scenic spot collected from EVs monitoring system made in Liaoning Northeast Asia Travel Group Co., Ltd., Dalian, China (a company that partially manages the electric vehicle traffic network for the Dalian bonded area scenic spot) have been chosen for simulation verification; the specific date is 26 February 2022. On 26 February 2022, there were 1400 Dalian bonded area registration EVs and 241 unregistered EVs (EVs that came from other areas or were newly purchased and unregistered in the Dalian bonded area) were charged in this scenic spot. The charging types are divided into \"only once/day\",  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Branch No.** & **Head Node** & **End Node** & **Active R (\(\Omega\))** & **Reactive R (\(\Omega\))** & **Active P (\&W)** & **Reactive P (kVar)** \\ \hline
1 & 1 & 2 & 0.0922 & 0.0470 & 100 & 60 \\
2 & 2 & 3 & 0.4930 & 0.2511 & 90 & 4  
\"twice/day\" and \"three times/day\"; the corresponding number of vehicles is 866, 437 and 198, respectively; the total number is 1501; and the other 140 EVs were charged more than three times. The real data come from the EVC data sensing and management system for the Dalian bonded area scenic spot, and we selected only the 1501 EVs with a charging frequency less than or equal to \"three times/day\" for research in this paper. Their battery capacity was determined before and after charging. There are four types of smart charging piles in the district, which are the slow charging mode suitable for households and the \(L-1\), \(L-2\) and \(L-3\) modes suitable for parking lots and shopping malls. Their charging powers are 3.5 kW, 7 kW, 12 kW and 24 kW, respectively, and the charging power factor is 0.9. All of them can charge any type of vehicle in the district car group and charge truth-telling.