## 7 Discussion  
With the increasing penetration of BIPV in urban buildings, it is increasingly important to optimize the operation of a BIPV microgrid. This paper proposes an optimal scheduling strategy for BIPV microgrid considering multiple VES. The simulation results validate the effectiveness of the proposed strategy and provide ideas for future research.  
Most of the existing literature studies focus on the participation of a single controllable load in the optimal scheduling of a microgrid, improving the operation economy of a microgrid or providing frequency response service, etc. In practice, controllable loads such as AC, EWH, and refrigerators often participate in demand response together. Therefore, in this paper, two VES models, i.e., ACVES and EWHVES, are developed and integrated into the optimal scheduling of a BIPV microgrid. At the same time, the charging/discharging characteristics between ACVES and EWHVES, EWHVES and battery were analyzed and compared. Thus, the integrated research of ACVES and EWHVES fills the gap and enriches the existing literature. Simulation results in different studies demonstrate that both ACVES and EWHVES are effective in reducing the operating cost of the system. When ACVES participated alone in the optimal scheduling of the system during the summer scenario, the operating costs were reduced by 5.67%, and indoor temperature comfort was maintained. A similar research approach to analyze the ACVES utility is also applied in [19], which shows similar results of this paper. When EWHVES participated alone in the optimal scheduling of the system in the summer scenario, the operating cost was reduced by 7.63%, which is in consistent with the findings shown  
Figure 13: The optimal scheduling results in winter: (**a**) VES is not considered; (**b**) VES is considered.  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Seasons** & **Without VES/S** & **With VES/S** & **Cost Reduction with VES** \\ \hline Spring & 226.01 & 218.02 & 3.54\% \\ Summer & 165.06 & 144.69 & 12.34\% \\ Autumn & 228.71 & 214.84 & 6.06\% \\ Winter & 257.27 & 246.51 & 4.18\% \\ \hline \hline \end{tabular}
\end{table}
Table 5: Daily operating costs of the system under 4 seasons.  
in [15]. In this paper, there are two main new insights: (1) both ACVES and EWHVES can effectively reduce the operating cost of the system, and when they participate together, the cost reduction is not a linear superposition of their effects when they participate alone; (2) both ACVES and EWHVES play a similar role of battery energy storage system, but they show different energy storage principles due to different VES characteristics.  
The simulations in this paper are based on day-ahead forecast data, and due to the forecast errors, the day-ahead planned operation strategy differs from the actual situation of the microgrid's intra-day operation. The solution to this issue is either improving the forecast accuracy or performing intraday optimal scheduling.  
In future work, we will study more VES characteristics of controllable loads and aggregate them together to provide VES utility. Besides, based on their different VES characteristics (e.g., storage quality, VES charging/discharging power, response speed, etc.) and our optimization goals (e.g., reduction of operating costs, providing frequency response, etc.), we will set their charging/discharging priorities to maximize the VES utility. In addition, we consider integrating VES into intraday optimal scheduling using methods such as model predictive control to cope with forecast uncertainty in real-time. In addition, how to aggregate massively different controllable loads and design their control algorithms to provide VES utility can also be a research point. At last, we will also research how to develop incentives for more controlled loads in homes and commercial buildings to provide VES utility, while ensuring user comfort and privacy.