The escalating installation of distributed generation (DG) within active distribution networks (ADNs) diminishes the reliance on fossil fuels

yet it intensifies the disparity between demand and generation across various regions. Moreover

due to the intermittent and stochastic characteristics

DG also introduces uncertain forecasting errors

which further increase difficulties for power dispatch. To overcome these challenges

an emerging flexible interconnection device

soft open point (SOP)

is introduced. A distributionally robust chance-constrained optimization (DRCCO) model is also proposed to effectively exploit the benefits of SOPs in ADNs under uncertainties. Compared with conventional robust

stochastic and chance-constrained models

the DRCCO model can better balance reliability and economic profits without the exact distribution of uncertainties. More-over

unlike most published works that employ two individual chance constraints to approximate the upper and lower bound constraints (e.g

bus voltage and branch current limitations)

joint two-sided chance constraints are introduced and exactly reformulated into conic forms to avoid redundant conservativeness. Based on numerical experiments

we validate that SOPs' employment can significantly enhance the energy efficiency of ADNs by alleviating DG curtailment and load shedding problems. Simulation results also confirm that the proposed joint two-sided DRCCO method can achieve good balance between economic efficiency and reliability while reducing the conservativeness of conventional DRCCO methods.