The increasing installations of distributed generation (DG) in active distribution networks(ADNs) reduce the consumption of fossil fuels but also exacerbate the demand/ generation im-balance among different regions. Moreover, due to the intermittent and stochastic characteristics,DG also introduces uncertain forecasting errors, which further increases the 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 exactly exploit the benefits of SOPs in ADNs under uncertainties. Compared with conventional robust, stochastic and chance-constrained models, DRCCO model can better balance reliability and economic profits without the exact distribution of uncertainties. Moreover,unlike most published works that employ two individual chance constraints to approximate the upper and lower bound constraints (e.g. voltage and current limitations), joint two-sided chance constraints are introduced and exactly reformulated into conic forms to avoid the redundant conservativeness. Based on a numerical experiment, we validate that SOPs’ employment can enhance the energy-efficiency of ADNs by significantly reducing the DG curtailment and load shedding. Simulation results also confirm that the proposed joint two-sided DRCCO method can achieve good balance between economic efficiency and reliability as well as decrease the conservativeness of conventional DRCCO methods.