## 6 Conclusions  
In this paper, the following work is carried out for the multi-area RIES optimal scheduling problem with an SESS, considering RES uncertainty. Firstly, a multi-area RIES system model considering SESS access is established. At the same time, the working state of SESS access of the RIES is considered from three aspects and the corresponding constraints are proposed. Secondly, PV cells and a WT are regarded as time-varying parameters, and a dynamic optimization problem model considering time-varying parameters is established. For such problems, this paper also proposes a ROOT-TES-PCPG algorithm combined with a scene analysis method to solve them. Finally, the proposed method is verified by establishing a practical example model. Based on the proposed different models, the following conclusions can be obtained through the results. 1. For the dynamic robust optimization problem considering time-varying parameters, the improved ROOT algorithm based on the two-stage evaluation proposed in this paper has a better judgment effect on the predicted solution in the future, so that the robustness of the solution obtained by the overall algorithm is better. In the mMPB test environment, compared with the results of the existing ROOT algorithm, the solution AF index and ST index obtained by ROOT-TSE-PCPG are increased by 94.41% and 179.78, respectively. Therefore, the algorithm proposed in this paper provides a new method for calculating the optimal robust solution of dynamic optimization problems in practical engineering and has certain practical application value. 2. When there are uncertainties such as a WT and PV cells in the RIES system, the ROOT-TSE-PCPG based on the scenario analysis method proposed in this paper can be used to analyze the uncertainty of RESs through the robust control method. At the same time, the method proposed in this paper can effectively reduce the operating cost of the RIES. The application of the proposed method in the optimal scheduling problem can reduce the operating cost of the whole system by 5.32% on average. Similarly,  
Figure 14: Cold load optimization scheduling results of RIES. Figure 13: Heat load optimization scheduling results of RIES. when there are multiple sub-energy regions in the system, the rational allocation of SESSs can make the energy consumption of the whole system more stable and the energy interaction more scientific, so as to achieve the purpose of reducing the operating cost of the system. The rational allocation of SESSs can reduce the operating cost of the whole system by an average of 6.81%, while considering the above two factors in the optimal scheduling problem can reduce the operating cost of the system by 11.65%. At the same time, the SESS also acts as an energy transmission line, which can transmit electricity from RES-rich areas to RES-deficient areas. At present, although several SESS demonstration parks have been put into operation in China, they are still in the development stage. As China continues to move toward the goal of 'carbon peak carbon neutrality', the method proposed in this paper will provide a reference for the operation of SESSs in the future. At the same time, with the increasing uncertainty factors on the source-load side of the RIES, the operation cost and economy requirements of RIES optimal scheduling will be higher in the future, and the operation optimization objectives will be more diversified. Therefore, how to model and solve the dynamic robust optimization problem with multiple optimization objectives and uncertain time-varying parameters is an issue that needs to be studied in the future. Conceptualization, B.Z. and E.L.; methodology, B.Z. and E.L.; validation, E.L.; investigation, B.Z. ; data curation, B.Z. and E.L.; writing--original draft preparation, B.Z. ; writing--review and editing, B.Z. and E.L.; supervision, E.L.; funding acquisition, B.Z. and E.L. All authors have read and agreed to the published version of the manuscript.