In　the　context　of　double　carbon,　it　is　an　inevitable　requirement　for　the　low-carbon　power　industry　to　take　economic　efficiency　and　low　carbon　into　consideration.　This　article　introduces　the　carbon　emission　constraint　into　the　economic　dispatching　of　the　power　system.　Then,　combined　with　the　blockchain　theories,　the　methods　of　particle　swarm　optimization　and　multi-objective　particle　swarm　optimization　(MOPSO)　are　employed　to　simulate　the　economic　and　environmental　scheduling　of　a　power　generation　system　based　on　six　thermal　power　units.　Research　shows　that　the　constraint　processing　approach　is　practical　and　effective,　and　it　can　firmly　adhere　to　equality　requirements,　which　is　superior　to　other　algorithms＇　constraint　processing　methods;　the　algorithm　is　stable,　and　the　global　optimal　solution　can　be　determined　under　different　initial　solutions.　In　the　process　of　multi-objective　optimization,　the　solutions　of　POF　obtained　by　using　the　slope　method　are　evenly　distributed.