## 1 Introduction
In [18], the authors proposed an IGDT-based robust problem model for multi-carrier energy system management; it uses an IGDT model for handling the uncertainties associated with VRE. Although the interval- and IGDT-based robust models are useful for uncertainties, optimization results are conservative [10]. A data-driven p-efficient point method was used to compute renewable generation amounts, taking into account the renewable uncertainties in the distribution system, and achieved satisfactory results [19]. To properly handle the uncertainties associated with VRE in MEMGs, the p-efficient point method based on historical VRE data is involved in this paper. On the other hand, the energy storage systems (ESS) are known as a solution for the integrated energy systems with high VRE penetration. The authors of [20] described the role of electrical energy storage in an energy system dominated by distributed generation as well as possible modes of deployment of energy storage solutions in an industrial setting. In integrated energy systems, ESS may be used to enhance the potential energy and cost savings provided by combined heat and power (CHP) generation, if properly sized and operated [21]. In [22], authors proposed the optimal configuration of ESS in integrated energy system, taking into account reducing wind curtailment, price arbitrage, peak demand shaving and coordinated operation with CHP. In [23], the optimal schedule of battery-integrated energy systems is investigated with consideration of forecast error, and the optimal battery charging/discharging state is analytically obtained to maintain the real-time balance between supply and demand and simultaneously improve the system's economy. A combination of applications of ESS and thermal energy storage seems more promising as it offers higher potential to achieve energy efficiency improvement and cost savings in integrated energy systems. For instance, the electrical-thermal hybrid energy storage is used for mitigating the problem of intermittency that plagues electrical and thermal renewable forms of energy in [24]. The use of the energy stored in the hybrid energy storage to supply part of the energy required by the heating load leads to a reduction of the amount of power supplied by the mains, thus reducing the microgrid operating costs. In [25], an optimal configuration method for community-integratedenergy systems considering electrical and heat storage devices is proposed, which can meet the load requirements of electricity, cooling and heating in the system and ensure economic efficiency simultaneously. In [26], the effects of cold storage on the performance and efficiency of the energy hub operation cost are investigated; it is demonstrated that the ice storage performance increases the flexibility of the energy hub to apply more energy resources, which leads to the cost reduction alongside using other programs and storages. In [27], a risk-averse method for the optimal deployment of heterogeneous energy storage (HES), consisting of electrical and thermal energy storage, in a residential MEMG is proposed; results indicate that the deployment of electrical and thermal energy storage can effectively increase the system equivalent daily profit and make it more immune to the uncertainties. It is obvious from the specialized literature that integration of the heterogeneous energy storage with MEMGs has undeniable impacts on enhancement of the systems' operation. In this paper, HES consisting of electrical, cooling and heating energy storage is exploited to provide a potentially cost-effective solution to enhance the flexibility of the MEMG system. Demand response (DR) is an important measure to guide the customers to consume electricity rationally to achieve economic and efficient operation. Traditionally, DR programs only focused on the electricity pattern of the customers and aimed to shift electrical loads from peak periods to off-peak periods [28].