## 7 Conclusions  
WPPs, PVs, HSs, TPPs, and ESDs were integrated into a MECS. This paper proposed a multi-objective model for MECS operation considering different operation constraint conditions under three objective functions: the maximum operation revenue (F\({}_{1}\)), the minimum abandoned energy cost (F\({}_{2}\)), and the minimum output fluctuation (F\({}_{3}\)). Then, the rough set theory was applied to handle the information of the payoff table of the objective functions to calculate the weight coefficients. Finally, the improved IEEE 14-bus system was used as the simulation system. The following conclusions were gained:  
(1) The proposed uncertainty analysis and simulation method generated the most appropriate scenarios for wind power, photovoltaic power, and other uncertainty factors. The Wasserstein method achieved a better discretization by dividing the CPDF into several unequal subintervals. The scenario tree method comprehensively simulated the uncertainty factors by considering different occurrence states, whereas the improved K-medoids method selected the most representative scenarios more efficiently by calculating the relative K-distances of different scenarios and ensuring the updated clustering center.  
(2) The MECS fully utilized the complementarity of the different power sources, and the proposed multi-objective model obtained the optimal scheme for MECS scheduling. TPPs, HSs, and PVs were the major power sources used to satisfy the load demand on a typical summer day, whereas TPPs and WPPs were the major power sources used for load demand on a typical winter day. Compared with the results of the single optimization objective, the scheduling results better balanced the revenue and risk when multiple optimization objectives were taken into consideration.  
(3) The operation results of MECS scheduling improved as the ESD capacity increased, and they were restricted when the capacity reached the required value. The change trend of the complementarity indexes was nearly identical to that of the objective functions. The ESD optimized the MECS scheduling by utilizing the characteristics of power discharge-charge. The ESD operation mode directly influenced the optimality of the results. In the OEE mode, the discharge-charge power was better utilized than in the LLC mode; moreover, the LLC mode ensured the ESD's operation life cycle.  
Figure 16: The complementarity indexes of MECS operation under different ESD capacities.  
The optimal ESD operation strategy should be individually determined to achieve the optimal scheme for MECS operation.  
(4) The operation results of MECS scheduling improved as the ESD capacity increased, and they were restricted when the capacity reached the required value. The change trend of the complementarity indexes was nearly identical to the objective functions. When the capacity ratios of the ESD and the WPP and the PV was in [0.62, 0.77] in the OEE mode and in [1, 1.08] in the LCC mode, the optimal results of MECS scheduling were obtained on a typical summer day. When the capacity ratios were in [0.92, 1] in the OEE mode and in [1.23, 1.31] in the LCC mode, the optimal results were obtained on a typical winter day. The optimal ESD operation strategy should be individually determined.  
[PERSON] and proposed the researching framework. [PERSON] and [PERSON] conducted the empirical analysis and wrote the manuscript. [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] provided several useful recommendations on the manuscript revision  
This research was funded by Supported by the Beijing Social Science Fund (18 GLC058, 16 JDYJB044) and the National Science Foundation of China (Grant No. 71874053, 71273090) and the Beijing Social Science Fund (18 GLC058) and the Science Foundation of China University of Petroleum, Beijing (No. ZX20170256)  
The authors declare no conflict of interest.