## 1 Introduction  
With the continuous shortage of fossil energy and the increasing demand for environmental protection, the proportion of clean energy in the energy system is increasing. Especially in recent years, with the rapid development of wind power generation and photovoltaic power generation technology, wind turbine power generation and photovoltaic power generation have been widely used. In order to make reasonable use of various resources and improve the controllability of the power system, active distribution networks have emerged. On the one hand, _DG_ devices improve the utilization of clean energy and increases the flexibility of the network. On the other hand, the uncertainty of _DG_ also has a certain impact on the stability and safe operation of the network. Therefore, it is necessary to plan _DG_ reasonably to make ADN operate more safely and reliably, and make full use of renewable energy for power generation. ADN emphasizes that various controllable sources in modern distribution networks, especially renewable energy generation, should be passively absorbed to actively managed and utilized [1]. Therefore, it is necessary to consider the operation characteristics of ADN while planning distribution network. An optimal allocation model of renewable energy considering the special supply capacity of ADN under the active management mode is proposed [2]. A double-layer programming model of ADN is established to promote the efficient utilization of intermittent _DG_[3]. The literature [4, 5] establishes the multi-time-scale optimization model and multi-objective _DG_ location and capacity planningmodel considering the investment level and operation simulation level, respectively. In the ADN planning stage, a joint planning operation optimization model considering the economic dispatching strategy of \(DG\) and the energy storage system (ESS) is developed in [6]. Although some operation characteristics of ADN are considered in the \(DG\) planning stage, few scholars consider network reconfiguration in the \(DG\) planning stage, although network reconfiguration is among the important operation means of distribution network. At the same time, the high proportion of renewable energy integration into the power grid is another major feature of ADN. The large-scale penetration of renewable energy increases the uncertainty of distribution network, posing challenges to distribution network planning. Therefore, references [7; 8] establish the corresponding multi-objective programming model for the uncertainty of intermittent \(DG\) output and load behavior. Considering the uncertainty of \(DG\) output and load growth, an ADN planning model is established with \(DG\) and grid as planning objects [9; 10]. A probability model considering the uncertainty of \(DG\) is proposed in [11], and used the theory of multi-state system to transform the stochastic problem into the deterministic problem. \(DG\) planning model is developed based on multi-scenario analysis solution [12; 13; 14]. Considering the intermittency of \(DG\) and the correlation between wind speed, light intensity and load, the chance constrained programming method is proposed [15]. Taking into account the random fluctuation of wind turbine output power, a probability analysis model of wind power generation is established [16]. The uncertainty of \(DG\) is considered in the planning stage in the above documents, but the robust optimization model is rarely used. According to [17; 18], robust optimization model has significant adaptability to the uncertainty of \(DG\) and load, and should be widely used. However, the above literature only deducts the uncertainty of \(DG\) and does not consider improving the consumption of renewable energy. In the context of a high proportion of renewable energy connected to the power grid, it is crucial to consider the consumption of renewable energy during the planning phase. In the planning stage, some scholars gradually consider the characteristics of active management of active distribution networks.