## 1 Introduction
[PERSON] [15] proposed a capacity configuration model for small-island electricity systems with WPP, PV, and ESDs. Similarly, [PERSON] et al. [16] proposed a hybrid generation system with WPP, PV, and flywheel energy storage systems. [PERSON] et al. [17] discussed the influence of the synergic operation of WPP, HS, and PV on net power output curve smoothing. [PERSON] et al. [18] put forward a new energy coordinated model for a virtual power plant and discussed the impact of plug-in hybrid vehicles with a high proportion of wind power penetration. [PERSON] et al. [19] constructed an optimization configuration model for a WPP-PV hybrid energy system and analyzed its economy and reliability. These studies have demonstrated the significance of complementary power sources. [PERSON] et al. [20] chose WPP, solar collectors (SC), combinedheat, and ESDs to get the optimal operation cost. The above research discussed the optimal capacity planning configuration and coordinated control of hybrid energy systems with different power sources; however, the complementarity of different power sources from the scheduling perspective needs to be discussed further. According to the above analysis, some research has already investigated the randomness and intermittent nature of uncontrollable power sources with the three proposed available ways. Firstly, a series of advanced intelligent methods were put forward to improve the forecast accuracy and achieve a better practical effect. However, an excessively large amount of data is needed to achieve high accuracy which consumes too much effort. In order to overcome the above problem, the uncertainty could be simulated by a random sampling technique based on the probability distributions of different uncertainty factors. Secondly, some of the literature has discussed the optimization effect of ESDs on multi-energy complementary system (MECS) operation, and different optimization models have been constructed. However, almost all studies have assumed that the ESDs will fully respond to MECS scheduling to achieve the maximum use of clean energy without considering the influences of different operation modes. In fact, ESD could operate in two modes, namely, the longest life cycle (LLC) and the optimum economic efficiency (OEE). The optimal scheduling strategy of MECS operation will show great differences under different operation modes. That means that a discussion about ESDs' operation modes is necessary. Finally, most of the research studied the optimal capacity planning configuration and coordinated control of hybrid energy systems and analyzed the complementarity characteristics of different power sources. However, the studied hybrid systems have been limited to only two or three power sources. In fact, WPP, photovoltaic power plants (PV), hydropower stations (HS), thermal power plants (TPP), and energy storage devices (ESDs) show a great complementarity. Therefore, it is important to construct a new hybrid system with the above power sources and discuss the optimal operation strategy. All the above analyses motivated us to develop a multi-objective scheduling optimization model for MECS operation. The main works of the paper are summarized as follows:  
* An uncertainty analysis and simulation method are proposed to generate a typical distribution scenario for the uncertainty factors of MECS operation based on the Wasserstein method, and the K-distance and the K-medoids algorithms. The method includes three steps, namely, the discretization of the continuous probability distribution functions, the generation of the initial simulation scenarios, and the selection of the most representative scenarios. * A multi-objective scheduling model and solution algorithm are proposed by considering different ESD operation modes under three objective functions, namely, the maximum operation revenue, the minimum abandoned energy cost, and the minimum output fluctuations. Then, the multi-objective model is weighted into the single objective mode by the rough set theory based on the payoff table.