In order to solve the problem of large amount of calculation in multi-objective optimization of microgrid, a distributed neural dynamic optimization algorithm considering demand response was proposed. Firstly, the multi-objective optimization model was established considering the average efficiency function, micro grid emissions, demand response induced dissatisfaction and total profit function. Then, the multi-objective optimization problem was transformed into a single objective optimization problem by using the single objective product formula, and it was proved that the optimal solution was the Pareto best of the original multi-objective problem. Furthermore, the logarithmic obstacle penalty factor was used to deal with inequality constraints, and the invariance principle of LaSalle and Lyapunov function were used to prove that the proposed algorithm can converge to the optimal solution. Finally, the simulation results show that the proposed method can greatly reduce the calculation cost under the condition of ensuring the optimization accuracy and convergence.