**5. Case Study**

To evaluate the effectiveness of the operation scheme and optimization algorithm proposed in this study, the load data of a large hotel, a supermarket, and a primary school in 16 typical buildings provided by the US Department of Energy Building Technologies program are selected as cases for analysis [47,48]. Figure 3 shows the load curves of the three buildings. Figure 4 shows the temperature and solar irradiance curves. Table 2 lists the relevant parameters of the equipment in the system. Table 3 shows the installation cost and life of the equipment. Table 4 shows the price of electricity and natural gas. Table 5 shows the pollutant gas emission factors and treatment costs.

**Figure 3.** The load demand of the buildings.

**Figure 4.** Temperature and solar irradiance curves.

**Table 2.** The value of the equipment parameters.


**Table 3.** The investment cost and the life of the equipment.


**Table 4.** The price of electricity and natural gas.



**Table 5.** Pollutant gas emission and treatment parameters.

Note: The definitions of *γmt g*, *γgbg* , *γgrid g* , and *βg* are consistent with Equation (18).

In this study, the population size of the algorithm is 30, and the number of iterations is 500. The experiments were performed on MATLAB R2016b software. The computer is configured with Intel® CoreTM i5-6200U, 2.4 GHz, 12 GB RAM, and is made in China.
