Research Article

On the Optimization Strategy of EV Charging Station Localization and Charging Piles Density

Algorithm 2. Improved Particle Swarm Optimization (IPSO) algorithm

Input: EV position data set, .
Output: the location and number of charging stations and the number of charging piles in the charging station under the optimal cost .
1: According to the location and quantity of EVs in the planned area, estimate the range of the number of charging stations in the planned area
2: Set the initial value of the number of charging stations
3:  while
4:     Set the maximum number of iterations of the algorithm MaxIter, particle population size PopSize, random values , , learning factors , , inertia weight
5:    forPopSize do
6:        Randomly select group data from as the charging station initial position data set , . Initial particle velocity , and
7:        Use the Voronoi diagram to divide the service scope of the charging station ,
8:        Assign EVs to the nearest charging station ,
9:        Use queuing theory [M/M/S] to calculate the number of charging piles in the charging station ,
10:         Calculate the total cost when deploying charging stations in combination with constraint conditions
11:     The optimal statistical particle individual is ,
12:     end for
13:  The particle population cost data set is ,
14:  The optimal data set of individual particles is ,
15:  Set the particle global optimal value , , the corresponding particle is the global optimal particle
16:  repeat
17:     fordo
18:         Update particle velocity ,
19:         Update particle position ,
20:         Calculate the total cost when deploying charging stations in combination with constraint conditions
21:         Get the optimal position of each particle
22:       ifthen
23:          
24:       else
25:          Keep the current particle position unchanged
26:       end if
27:     end for
28:   The particle population cost data set is ,
29:   Set the global optimal value , , determine the global optimal particle
30:    ifthen
31:      =
32:    else
33:      Keep the current particle position unchanged
34:    end if
35:  until the number of cycles reaches MaxIter
36: end while
37: Current output: output the optimal location for deploying charging stations
38: Use the optimal location to calculate the total cost of deploying charging stations and the number of charging piles in the charging station.
39: Calculate the total cost of deploying different numbers of charging stations and get the total cost data set ,
Algorithm 2. Improved Particle Swarm Optimization (IPSO) algorithm