## 3 Coordinated Dispatching Model of IESs Considering Differences of Multiple Functional Areas  
Previous work on IES system dispatching mainly focused on single-area IES. There are few studies on multiarea IES dispatching and less consideration on different load characteristics of different areas. Thus, inevitably, there were some problems, such as low energy efficiency and poor economic benefits. To solve the above problems, the different load characteristics of different functional areas are considered and the following points are proposed in this paper: (1) the cooling loads, heating loads, and charging loads of EVs have energy storage characteristics; (2) the cooling loads and heating loads \begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Loads** & **Residential Area** & **Office Area** & **Commercial Area** & **Industrial Area** \\ \hline Heating Loads & High at night and low in the day, and constrained by the PMV index & High during working hours, low at night, and constrained by PMV index & High during business hours, low at night, and constrained by PMV index & High during the day, relatively low at night, not subject to PMV index \\ \hline Cooling Loads & Affected by the equivalent thermal resistance \(D\) & N/A & N/A & Affected by the equivalent thermal resistance \(D\) \\ \hline Electric Loads & Double peaks in the morning and evening & High during working hours & Double peaks at noon and night & High loads rate throughout the day, highest during the daytime \\ \hline Charging Loads of EVs & Concentrated on charging at night & Concentrated on charging during working hours & Concentrated on shopping and leisure time, and with large charging power & Concentrated on charging during working hours \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparisons of load characteristics of multiple functional areas. are suitable for transmission within the functional areas; (3) the electric loads and charging loads of electric vehicles are suitable for transmission across functional areas. Thus, a coordinated dispatching model of IESs is established considering the above characteristics. Through the complementarity of various forms of energy systems and different loads in multiple functional areas, the absorption rate of renewable energy can be effectively improved and the economic efficiency of the operation of IESs can be improved. Uncertainty is a key factor to be considered in power management and there is strong uncertainty in renewable energy output. Scenario analysis and robust optimization are commonly used to deal with uncertainty in power management problems. In scenario analysis, uncertainties are described through scenario sets [28]. Uncertain parameter intervals are used in robust optimization to describe the uncertainty. Robust optimization requires less information about the probability distribution of random variables [29; 30; 31]. Considering that scenario analysis can clearly describe the probability characteristics of uncertain variables and its optimization model can be easily calculated, scenario analysis is used to deal with production uncertainty in this paper. It is assumed that there are \(S\) scenes, and the probability of scene \(s\) is \(p_{s}\). The lowest operating cost is generally taken as the objective of coordinated dispatching model. In order to promote the consumption of renewable energy, the cost of abandoned WT and PV power is added to the total operating cost of the IESs.