The  uncertainty  of  wind  and  photovoltaic  power  generation  results  in  carbon  emissions  of  low-carbon scheduling  methods  not  meeting  expectations.  Therefore,  a  multi-time-scale  low-carbon  scheduling  method  for  regional integrated energy systems under chance constrained planning is proposed. Firstly, it uses the power of wind and solar power generation  at  different  time  periods  as  random  variables,  and  introduces  confidence  level  quantification  constraints,  an improved  particle  swarm  algorithm  is  used  to  determine  the  optimal  decision  variables.  Secondly,  it  introduces  carbon capture power plants to capture, store, and reuse CO₂ , constructs a carbon cycle system, and designs a tiered carbon trading mechanism  and  user  demand  response  mechanism.  Finally,  it  designs  a  multi-time-scale  real-time  rolling  control  plan,constructs  real-time scheduling  objective  functions  and  constraints,  and  achieves  low-carbon  scheduling  of  regional integrated  energy  systems  at  multiple  time  scales.  The  experimental  results  show  that  the  designed  scheduling method reduces carbon emissions by 4 570.1 kg compared to the no strategy scenario, and the actual carbon emissions are slightly lower than the free quota by 5%. It can effectively utilize low-carbon resources while meeting the requirements of system carbon emission constraints.