## 4 Case Studies
### The Optimization Results of Coordinated Dispatching for an Integrated Energy System
It can be seen from Figure 9 that there is abandoned WT and PV power at 5 a.m. and 8 p.m. During this period, the CHP unit has reached its minimum technical output, providing the largest consumption margin of renewable energy. Meanwhile, the heating power is 31.77 MW and 32.17 MW at 5 a.m. and 8 p.m., respectively. The heating load is 30.15 MW and 30.55 MW at 5 a.m. and 8 p.m., respectively. The heating power has exceeded the heating load in the allowable range of the heat elasticity at 5 a.m. and 8 p.m. to consume more renewable energy. The cooling power during this period is larger than the adjacent periods, and the indoor temperature of the cooling building has reached \(-20^{\circ}\)C, which is the lowest temperature in allowance. The tie line has also reached the limitation of the transmission power. The abandonment rate of WT and PV power has been minimized through the coordination optimization of cooling power, heating power, electric power, and tie line power. The Impacts of the Penetration Rate of EVs and the Charging Coefficient on the Consumption of Renewable Energy  
The impacts of the penetration rate of EVs on the consumption of renewable energy are compared and analyzed, and the results for different penetration rates of EVs are shown in Table 5. Since there is no abandoned WT and PV power in both the office area and the commercial area, only abandoned WT and PV power in the residential area and the industrial area are listed. It can be seen from Table 5 that the abandoned WT and PV power in the residential area and the industrial area are also decreasing with the increase of the penetration rate of EVs, while the reduction of the residential area is more  
Figure 9: The optimization of cooling power, heating power, electric power, and tie line power in the industrial area. obvious. The reason is that the number of EVs distributed in the residential area is greater than the industrial area during the periods of abandoned WT and PV power, so the penetration rate of EVs have a greater impact on the consumption of renewable energy in the residential area than in the industrial area. In summary, transferring the charging loads of EVs in the industrial area to the periods with abandoned WT and PV power by reducing the charging price in these periods should be considered. The impacts of the charging coefficient \(\alpha_{r,k}^{\min}\) on the consumption of renewable energy are compared and analyzed, and the results for different charging coefficients are shown in Table 6. Since there is no abandoned WT and PV power in both the office area and the commercial area, only abandoned WT and PV power in the residential area and the industrial area is listed in Table 6. It can be seen from Table 6 that with the decrease of \(\alpha_{r,k}^{\min}\), the abandoned WT and PV power in the residential area and the industrial area is also decreasing, because \(\alpha_{r,k}^{\min}\) relates to the minimum charging power in time period \(k\) of area \(r\). When \(\alpha_{r,k}^{\min}\) decreases, the lower limit of charging power could be more relaxed, which means that EVs can be charged in other time periods and other areas. Thus, the charging power of EVs could match the output curves of renewable energy better, and the abandoned power of renewable energy could be reduced.