Building　a　new　power　system　with　renewable　energy　as　the　main　body　is　the　only　way　to　solve　the　problem　of　global　climate　change　and　achieve　the　dual　carbon　goal.　However,　the　increasing　penetration　rate　of　renewable　energy　and　large-scale　electric　vehicles　have　brought　great　challenges　to　the　safe　and　reliable　operation　of　traditional　power　system,　resulting　in　the　inability　to　effectively　meet　the　enormous　urban　electricity　demand　in　real　time.　In　response,　this　paper　proposes　to　adopt　mobilized　and　distributed　batteries　and　establishes　a　two-stage　logistic　and　scheduling　optimization　model,　thereby　realizing　the　power　transportation　between　renewable　energy　power　plants　and　cities.　The　first　stage　model　aims　to　optimize　the　battery　transportation　and　logistics　scheme　with　minimizing　the　total　battery　procurement　and　transportation　cost　as　the　objective　function,　considering　various　constraints　including　railway　transport　capacity　limitation,　battery　supply　and　demand　balance,　and　other　technologies.　The　second　stage　model　aims　to　maximize　the　peak　shaving　effect　of　urban　power　system　and　optimize　the　railway　departure　time　with　mobile　batteries,　considering　the　train　operation,　battery　supply　limitation,　and　battery　transportation　balance　constraints.　Finally,　a　quantitative　economic　evaluation　of　six　cities　(Heilongjiang,　Gansu,　Fujian,　Shanghai,　Jilin,　and　Liaoning)　in　China　is　presented,　and　the　results　indicate　that　the　average　levelized　cost　of　electricity　is　as　low　as　0.052　$/kWh,　illustrating　the　great　technical　and　economic　performance　of　battery　logistics　and　scheduling.　In　addition,　the　impact　of　various　sensitive　factors　on　the　economic　performance　of　the　urban　energy　system　is　implemented.　©　2022