## 1 Introduction  
With the rapid growth of renewable energy and energy storage systems integrated in the distribution network, the development of a DC distribution network has drawn more and more attention [1]. Compared to the AC distribution network, the DC distribution network has the advantages of reducing active power losses, and improving the power quality and utilization rate of electric energy [2,3]. As a result, the hybrid AC/DC distribution network will become a new tendency of intelligent distribution network development in the future [4,5]. By combining the advantages of two kinds of distribution networks, the hybrid distribution network can achieve flexible power supply for different types of electric load and renewable energy accommodation [6,7]. To handle the variations of renewable energy and load demand, a multi-timescale coordinated stochastic voltage/var control approach was developed and a mixed-integer quadratic programming model was built for the IEEE 33-bus radial AC distribution [8]. The authors of [9] proposed a day-ahead reactive power dispatch method of AC distribution networks by considering power forecast errors of renewable energy, and a dynamic preliminary-coarse-fine adjustment strategy was designed to achieve the optimal scheduling of distributed generators (DGs) and capacitor banks (CBs). At present, research of the hybrid AC/DC distribution network is in the elementary stage and needs to expand and deepen. Voltage source converters (VSCs) have been utilized to convert AC lines into DC lines to improve DG accommodations [10]. To realize the coordinated voltage regulation in a hybrid AC/DC distribution system, a priority-based real-time control strategy was proposed according to the voltage control effect of active-reactive power adjustment in [11]. Multiple battery energy storage systems (ESSs) have been considered in distribution networks for real-time voltage regulation in [12]. Furthermore, [13] proposed an optimal control management of ESSs to mitigate the fluctuation and intermittence of renewable energy. Taking into consideration prediction errors, the optimal operation of ESSs in a distribution system was developed and solved in a two-level framework to alleviate the net load uncertainties [14; 15]. For the planning problems of ESSs, [16] introduced a new index to quantify wind power fluctuations, and the impact of different ESSs configurations on the solutions were analyzed. A scenario-based chance-constrained planning approach was developed to handle the joint planning of multiple technologies of ESSs, and an easy-to-implement variant of Benders decomposition algorithm was proposed to solve the chance-constrained optimization problem [17]. In order to improve the reliability of electricity supplies with wind power integration, a population meta-heuristics algorithm was adopted to determine the minimum capacity of kinetic energy storage in [18]. To consider the randomness and uncertainty of wind power output, this paper proposes a two-stage stochastic scheduling model to realize active-reactive power coordinated economic dispatch for the hybrid AC/DC distribution network with the integration of capacitor banks and an energy storage system. The first stage is to determine the power setpoints of generator units, switching number of CBs, and charging/discharging state of ESSs, and the second stage is to adjust the transferred active/reactive power of VSCs and charging/discharging power of ESSs based on the realized wind power scenarios. To sum up, the schematic framework of this study is shown in Figure 1, for which the corresponding research contents are described in the following sections. Figure 1: The schematic framework of this study. The contributions of this paper can be summarized as follows:  
(1) The capacitor bank, energy storage system, and voltage source converter are coordinated as the active adjustment measures simultaneously in the hybrid AC/DC distribution system.