## 5 Conclusions  
This paper proposes a mathematical optimization model of AGC power allocation with EV charging stations. Besides, an AGC power allocation with EV based on the cost consensus algorithm is also developed, in which the main findings/contributions can be summarized as follows:  
1. A feasible method for decentralized control is presented for AGC power allocation with EVs. After the virtual consensus variables and actual consensus variables are introduced, the cost consensus algorithm can be flexibly applied on the AGC power allocation of EV. Meanwhile, because such an algorithm possesses the superiorities of distributed calculation and simple updating rules, self-regulation of EV charging and discharging can be efficiently and effectively achieved. 2. The adjustment cost is regarded as the consentaneous state variable in the cost consensus algorithm, which means the charging stations with less adjustment cost receive more power disturbances. Particularly, such a strategy can effectively reduce the power grid frequency regulation cost and improve the control performance standard of a regional power grid. Figure 7: Stochastic load disturbance in July; (**a**) active power regulation; (**b**) absolute value of frequency deviation. **Author Contributions:** Preparation of the manuscript was performed by [PERSON], X.M., R.G., Z.Y., S.L., C.Y., and B.Y. **Funding:** This research received no external funding. **Conflicts of Interest:** The authors declare no conflict of interest. **Nomenclature**  
**Variables**  
\(\Delta P_{\mathrm{EV}}\Sigma\)  
\(C_{\mathit{iso}}\)  
\(\Delta P_{i}\)  
\(\Delta P_{\mathit{iso}}\)  
\(\Delta P_{\mathit{iso}}\  
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