## 5 Case Study
### Analysis of Optimal Scheduling Results of RIES Considering SESS  
We take mode 4 as an example to analyze the optimal scheduling result for each region in the RIES. The optimal scheduling results of power load in each region of the RIES are shown in Figure 12. On the whole, RESs in all regions can participate in the actual power load supply; so, the optimal scheduling strategy can complete the consumption of RESs well. At the same time, the area with abundant RESs sells a large amount of electric energy to the EPG to reduce the operation cost of the whole system. Similarly, abundant electric energy can also be stored in the SESS to ensure the rational utilization of renewable energy in the RIES. Specifically, it can be seen from Figure 12 that the RA and CA only contain a PV cell, which belongs to the RES-deficient area. Therefore, when the RA has no PV output during 03:00-04:00 and 18:00-24:00, it is necessary to purchase electricity from the EPG to meet its own demand for power load. When the output power of the PV cell is large at 09:00-11:00, most of the users of the RA have moved to other areas to consolidate their lives. At this time, their own power load is small, so they can be charged to the SESS to improve their own electricity sales revenue and complete the consumption of RESs. For the CA, since the power load and heat load are at the peak stage during the period of 10:00-17:00, and during this period, the CA's own photovoltaic power generation cannot meet the load's demand for electricity, the CA mainly purchases electricity from the EPG during this period. In the rest of the time period, due to the comprehensive consideration of the coupling supply of cold and heat energy, some of the electricity is supplied through a GT. From Figure 12b, it can be seen that the IA has abundant RESs and its own power load is low; so, the IA can sell rich power resources to the EPG to earn profits. Similarly, while the OA region is rich in RESs, its own power load is lower than that of the IA, so it can sell a large amount of power to the EPG. Figure 11: The optimized operation results of the SESS under different modes. The optimal scheduling results of the RIES heat load are shown in Figure 13. On the whole, the thermal energy generated by the GB is the main source used to meet the thermal load in the region, accounting for 86.58% of the total cooling load supply, and the remaining thermal energy supply is completed by the HE and EB. The following is a detailed analysis of the thermal energy supply model for each region from Figure 14. Figure 13a shows the electric energy purchased from the EPG in the RA and CA areas. The RA and CA areas are mainly used to supply power to the EB, and the EB converts electric energy into heat energy to heat the area. In particular, because the electric load and heat load in the CA area are at their peak during 10:00-17:00 and the external electricity price is at the valley stage, the CA is mainly provided for by the EB during this period. It can be seen from Figure 13b that the IA and OA use the GB as the only device that provides more than 80% of thermal energy in a day. In particular, the IA only uses the EB and HE to provide a small amount of heat energy during the morning and evening due to electricity prices. The reason for the above results is that gasoline prices remain unchanged for a day. At the same time, in the process of the GB directly providing heat to the load, the energy from the conversion steps involved is less and the energy loss is lower. Figure 14 shows the optimal scheduling results of the multi-region RIES cooling load. On the whole, the cold energy generated by the EC is the main source used to meet the cooling load in the region, accounting for 84.38% of the total cooling load supply, and the remaining cold energy supply is completed by the AC.