## 1 Introduction  
Challenges of the continued growth of energy requirements, as well as energy shortage and environmental problems and the existing energy production and consumption patterns, cannot meet the growing needs of metropolitan regions for future development. Power energy systems need a transformation to overcome the above concerns. The development of concepts such as energy internet [1] and integrated energy systems [2] provide new ideas for energy efficiency and utilizing multiple energy carriers as well as renewable energy. Multi-energy microgrids (MEMGs), as small-scale integrated energy systems including electricity, gas, cooling, heating and other forms of energy for intelligent buildings, residential communities, industrial parks and other regions, comprise the developing trends of integrated energy systems [3]. Extensive research works are carried out on the small-scale integrated energy systems, including modeling, optimizing system structures and operation strategies. For instance, certain authors proposed a comprehensive model to decide the component capacities in an integrated energy system for a Swedish building, considering the system planning and system operation simultaneously [4]. In [5], the multi-carrier energy system, including hydro-wind-solar-hydrogen-methane-carbon dioxide-thermal energies, are integrated and modeled in a zero-energy building. The authors of [6] proposed the optimization configuration of a regional integrated energy system based on typical residential area modules and typical commercial modules built on actual regional plots. In [7], a double-layer planning model for an integrated energy system at the community level is proposedthat considers varying coupling factors to determine the optimal planning and operation schemes for the system. Another study [8] proposed a capacity planning and optimization model for an integrated energy system in an industrial park, aiming to minimize the cost per unit power generation. A multi-criteria decision-making method for a selection problem involving integrated energy system composition schemes in a practical industrial park is presented in [9]. With the increasing penetration of variable renewable energies (VRE) in MEMGs, considering the VRE-associated uncertainties in the system would make the results more realistic. On the one hand, various methods have been applied to model the uncertainties and obtain the optimal values in different research works. The stochastic method is one of the most common methods [10]. Solar and wind are the most widely used VRE in power energy systems worldwide [11]. In [12; 13; 14], a stochastic programming modeling framework is studied for solving the solar PV and wind power integrated smart energy hub scheduling problem. A Monte Carlo sampling method is used to generate the solar PV and wind power scenarios. The scenario reduction method is introduced to reduce the number of scenarios and simulation burden. The shortcoming of the above method is that it is computationally expensive, and the probability density functions of uncertain parameters are necessary. Robust optimization is another common method to handle the uncertainties. For instance, the authors of [15] proposed an interval optimization-based operational strategy for integrated energy systems to overcome uncertainties associated with VRE and loads. In [16], the authors proposed an interval-based integrated energy system planning with wind power integration, and the authors developed a probability-interval method to describe the uncertain wind power. In [17], a two-stage hybrid stochastic-information gap decision theory (IGDT) based on the network-constrained unit commitment framework is proposed for integrated power- and heat-based energy systems. In the framework, the uncertainties of load demands and wind power generation are studied using the Monte Carlo simulation method and IGDT, respectively.