Abstract: Enhancing the proportion of renewable energy sources in energy supply becomes a significant initiative to realize a low-carbon economy. A model based on deep reinforcement learning（DRL） for optimal allocation of low-carbon economy in microgrid is proposed to mitigate carbon emission and decrease electricity cost. Firstly, carbon emission flow theory is introduced on which a carbon measurement model and a stepped carbon price model are constructed. Secondly, the low-carbon economy optimization problem is converted into a Markov decision. Finally, the multi-objective optimization issue can be addressed utilizing DRL. The experimental results demonstrate that the proposed approach is effective in boosting system economy and mitigating carbon emissions by regulating the capacity of generating units and shifting the load.