Abstract：The intermittency and uncertainty of large-scale distributed new energy bring great challenges to the

stable operation of power system. Intelligent soft open point（SOP）and energy storage are effective ways to absorb distributed new energy in spatial and temporal dimension，and play an important role in improving the capacity of distributed new energy in distribution network. Therefore，considering the flexible operation characteristics of SOP and energy storage，a double-layer multi-objective programming model of SOP，energy storage and DGs for the capacity improvement of new energy was proposed. The upper level takes the total life cycle income of the distribution network，the carrying capacity of new energy，the system power supply capacity，and the power quality as the optimization objectives for the location and capacity determination of the units. However，the lower level takes the minimum daily total loss of the distribution network as the goal for the system optimization operation. The improved multi-objective particle swarm optimization algorithm was combined with the mixed integer secondorder cone programming algorithm to solve the proposed model. Finally，the effectiveness of the joint programming method was verified in the improved IEEE 43-node AC-DC flexible interconnected distribution network，and the optimal scheme under different scenarios was analyzed.

      Key words：distributed generation（DG）；soft open point（SOP）；AC/DC distribution network；double-layer

programming；multi-objective optimization