%0 Dataset
%T Game data set of new energy vehicle power sharing scenarios based on multi-objective complex multi-agent game model based on swarm intelligence evolutionary learning
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/de4f5432-c12b-4715-86b8-a180e2ec7cbc
%W NCDC
%A chen chun hua
%K New Energy Vehicle Battery Swapping;Game Model
%X The content of the game data set of the new energy vehicle sharing power exchange scenario based on the multi-objective complex multi-agent game model based on swarm intelligence evolution learning is three types of static complete information synchronous game scenarios: small-scale (30 vehicles, 5 power exchange stations), medium-scale (150 vehicles, 25 power exchange stations) and large-scale (600 vehicles, 100 power exchange stations).Each class contains 20 independent random instances, for a total of 60 JSON format instance files. Each example records the two-dimensional coordinates of the vehicle and the exchange station (area side length is 20), and the number of batteries at each station (5~10 small/medium scale, 10~15 large scale), initial SoC per battery (0.5~1.0 uniform sampling), initial SoC of vehicle (0.2~0.4 uniform sampling), minimum safe arrival SoC of vehicle (1/3~2/3 of the initial SoC), vehicle power replacement demand threshold (0.5~0.7 uniform sampling) and other parameters, and define individual costs and total social costs based on the dynamic electricity price model.