## 2 Microgrid Structure and Dispatching Strategy
### Scheduling Strategy Research  
In this paper, in order to minimize the overall cost by dispatching each generation unit, the following requirements should be met in the scheduling strategy to ensure power supply reliability:  
1. Maximize the utilization of wind and photovoltaic power generation, and maximize their output through reasonable scheduling;
2. Minimize the redundant power generated by wind and photovoltaic units to avoid energy waste;
3. The difference between wind-photovoltaic generation and the power consumption of the load depends on the energy interaction with batteries, EVs, and the main grid, and whether this can meet power balance constraints.The comprehensive cost can be further reduced to achieve economic optimization by selling electricity to the main grid and EVs.  
Figure 1: The model of wind–solar-storage electric vehicle microgrid system.  
In order to achieve the above requirements, the dispatching strategy aiming at the system economy is designed as follow: The output of wind power and photovoltaic generations are coordinated, and participate in the dispatching according to the state of the battery and EV on charge. Finally the power balance is realized through the interaction process with the main grid.  
a. Wind and photovoltaic generation  
The empirical output value of wind and photovoltaic generation is taken as the actual output power, and the scheduling is carried out after increasing the cost of wind and solar abandoning in order to reduce energy waste. The output power of wind and photovoltaic generation after dispatching is compared with the empirical value. If the output power is lower than the empirical value, the output power after dispatching can be used; otherwise, the empirical value has to be maintained.  
b. Battery generation  
Since photovoltaic and wind generation is affected by daily environmental changes, the charging and discharging process of batteries can meet the demand. According to power load trends within 24 h, power supply states are divided into peak, normal, and valley periods. Charging and discharging strategies are adopted based on the current period and the battery state of charge (SOC). The specific process is shown in Figure 2.  
According to Figure 2, charging and discharging can be carried out only if the battery SOC is within a certain range. When the charging and discharging standard is reached by the battery, the interactive state is judged according to its SOC value and the time period. Thereby, the charging and discharging power is calculated. The specific calculation method is provided as follow:  
\[P_{\textit{bess}}(t)=SOC_{x}(t)C_{x} \tag{1}\]  
where the charging and discharging power of battery at time \(T\) is described as \(P_{\textit{bess}}(t)\). The SOC of the battery at time \(T\) is shown as \(SOC_{x}(t)\), which is the scheduling target of the battery. The rated capacity of the battery collected from empirical data is defined as \(C_{x}\).  
c. Electric vehicle  
The output of an EV can be judged according to its SOC. If the SOC can maintain the normal operation of the vehicle, the power is outputted to the system; otherwise, the system's power is consumed. The flow is expressed in Figure 3.  
Figure 2: The scheduling strategy of battery generation.  
Similar to battery scheduling, the output state of EVs can be judged according to their SOC. The output of the SOC after scheduling, according to the idea shown in Figure 3, can be used for further calculations, and the specific expression is represented as follows:  
\[P_{ev}(t)=SOC_{e}(t)C_{e} \tag{2}\]  
where interactive power between EVs and the microgrid at time \(T\) is given as \(P_{ev}(t)\). The SOC of the EV at time \(T\) is shown as \(SOC_{e}(t)\), and the fixed capacity of EV is expressed as \(C_{e}\).