## 6 Case Data and Simulation Results
### Optimal Scheduling Result Analysis
#### 6.2.2 The Summer Cooling Scenario Simulation Analysis  
Case 1: VES is not considered  
VES is not adopted in the system, which means that the AC injects cool air into the building to maintain the indoor temperature at 24 Celsius, and the water heater adopts a ready-to-use model, not equipped with a tank. Figure 5 depicts the optimal scheduling results in the summer. Figure 4: Photovoltaic (PV) generation and load demand. Figure 3: Solar radiation and outdoor temperature. Figure 2: Real-time electricity price. In Figure 5, the power \(\geq\)0 represents the output power of PV, battery and the main grid. The power \(<\)0 represents the power consumed by loads, the charging power of the battery and the power sold to the main grid. Figure 5 shows that during non-working hours, due to the low electricity price, the system purchases electricity from the main grid to meet the electrical load demand in the building and charges the battery. During working hours, PV generator provides power for the system, the cost of purchasing electricity is reduced. Most of the working time, the battery is in the discharge state, but at 16:00, because the price of electricity is relatively lower than the adjacent time, the battery is charged. The cost of running the system in a day when VES is not considered is $165.06.  
Case 2: Only EWHVES is considered  
As shown in Figure 6, which plots the optimal scheduling result of BIPV microgrid when only EWHVES is considered in summer.  
As can be seen from Figure 6, at 3:00, due to the low electricity price, the EWH works and inject hot water into the tank for use during the working hours. At 11:00, due to the high electricity price, the power exchanged between the system and the main grid changes to 0, which reduces the system's electricity cost. Figure 7 shows the EWHVES and battery charging/discharging power and their state of charge.  
As shown in Figure 7, power \(\leq\)0 represents charging, and power \(>\)0 represents discharging. During non-working hours, the electricity price is low, both the battery and the WHVES are charged, meanwhile, both reach the maximum state of charge. During the working period, the battery discharges. Due to its limited capacity, the EWHVES is in a discharged state at a high electricity price time, and  
Figure 5: The optimal scheduling results when virtual energy storage (VES) is not considered.  
Figure 6: The optimal scheduling results when only electric water heater-based VES (EWHVES) is considered.  
in a charged state at low electricity price time. As mentioned above, both of them charge when the electricity price is low, and discharge when the electricity price is high, which play the role of peak load shaving. The BIPV microgrid costs $152.46 operating a day when only the EWHVES is adopted, which reduces 7.63% than that in case of without VES. In order to prove that the EWHVES can replace the battery to a certain extent, reduce part of the capacity of the battery to simulation, the result shows that when reducing 78 kWh capacity of the battery, the system has the same cost as the scene where the VES is not considered. Case 3: Only ACVES is considered  
The AC is turned on only during working hours. The indoor temperature is adjusted from the original fixed 24 Celsius to the upper and lower limit of 22-26 Celsius. The penalty factor of user comfort is 0.1. The optimal scheduling results of BIPV microgrid adopts ACVES is shown in Figure 8.  
As the figure above shows, at 11:00 and 17:00 with higher electricity price, the AC only consumes little electric energy to keep the room temperature in the comfort zone, which plays the role of peak load shaving and reduces the operating cost of the system.