In　order　to　further　enhance　the　utilization　rate　of　renewable　energy　and　achieve　the　goal　of　carbon　emission　reduction,　this　paper　establishes　a　stable　and　clean　energy　supply　mode　of　charging　system　and　constructs　a　three-stage　optimization　and　benefit　distribution　model.　Firstly,　the　charging　system　structure　is　built　with　employing　photovoltaic　generator　and　carbon　capture　thermal　power　generator.　Secondly,　the　charging　load　uncertainty　is　modeled　by　using　Markov　Chain　where　the　differences　of　speeds　of　vehicles　are　considered.　Thirdly,　a　deterministic　charging　optimization　model　is　constructed　in　the　first　stage,　with　the　objectives　of　economy,　environment,　energy　utilization　and　load　fluctuation;　and　then,　in　the　second　stage,　the　uncertainty　of　photovoltaic　power　generation　is　considered　to　formulate　two　types　of　information　gap　decision　theory-based　models.　Finally,　a　double　factor-involved　benefit　allocation　model　for　the　proposed　charging　system　is　con-structed　in　the　third　stage,　based　on　the　Shapley　method.　The　case　study　shows　that:　(1)　the　forecast　error　of　charging　load　is　smaller　by　considering　quantity　transfer　and　speed　differences;　(2)　carbon　capture　and　storage　system　reduces　CO2　emission　by　85.08　%　and　system＇s　cost　by　2.60　%;　(3)　Tripartite　cooperation　maximizes　the　system＇s　benefits,　and　IGDT　provides　multiple　strategies　for　dealing　with　PV　uncertainty;　(5)　benefit　allocation　considering　economy　and　environment　is　more　rational　and　highlights　the　contribution　of　carbon　capture　system.