# Research on Optimal Voltage Control of Distribution Network with the Participation of EVs and PVs
## 1 Introduction
The proposed scheduling strategy achieves the loss minimization and alleviation of bus voltage deviation simultaneously on the premise of satisfying the operational constraints of the substation transformer and sustaining competitive charging costs for EV owners. Ref. [6] describes a Volt-Var-Optimization-based EV charging scheduling scheme for the continuous bus voltage improvement of a distribution network with a high penetration of EVs and renewable energy sources (RESs). With the deepening of the research on the reactive power support capacity of the EV charger, the four-quadrant operation capability of EV chargers provides a new idea for the voltage regulation of the distribution network [7,8]. Most of the existing studies on the participation of EVs in distribution voltage regulation focus on developing the EV charging scheduling schemes without fully investigating the coordination potential of different types of voltage support resources (e.g., [9,10]) and the impact of EV transport types on the voltage support capability of EV fleets (e.g., [11,12]). In terms of research on PV participation in distribution voltage regulation, refs. [13,14] dynamically adjust the voltage at the grid connection point based on PV inverters' reactive power compensation capability. However, the reactive power compensation capability becomes restricted when the PV power generations are close to the power ratings of PV inverters. In [15,16], aiming at the power quality problem caused by the high-level penetration of PVs in the distribution network, semi-definite relaxation techniques and alternating direction method of multipliers are applied to optimize the reactive power outputs of the intelligent PV inverters to address the grid voltage deviation problem. Ref. [17] proposes a local voltage regulation technique that utilizes short-term PV power forecasts to circumvent potential bus voltage violations. In [18], an optimal coordination scheme between the active power curtailment and reactive power compensation is proposed for smart PV inverters to address the overvoltage issues. Among all the above studies, the voltage droop control is still the dominant voltage support approach for smart PV inverters, while the optimal operational settings of a droop controller can be achieved using a variety of optimization methods like machine learning [19], multi-time scale collaborative optimization [20], robust optimization [21] and stochastic optimization [22]. With respect to research on the coordination of EVs and PVs for distribution voltage regulation, an optimal reactive power support method of EVs and PVs is introduced to enhance the hosting capacity of distribution networks with EVs and PVs integrated [23]. Ref. [24] presents a decentralized voltage control algorithm that considers the active and reactive power control capability of both PVs and EVs. For rooftop PVs in industrial parks and EVs in residential areas, refs. [25,26] consider the V2G technology of EVs and propose a synergistic dispatch approach of EVs and PVs with the objective of minimizing the daily \begin{table}
\begin{tabular}{c c c c c} \hline
**Device Name** & **Output Type** & **Mechanism** & **Response Speed** & **Number in a Feeder** \\ \hline OLTC transformer & Discrete voltage & Mechanical & Slow & Limited \\ SCB & Discrete Var & Mechanical & Slow & Limited \\ Voltage regulator & Discrete voltage & Mechanical & Slow & Limited \\ Smart EV charger & Continuous Watt and Var & Electronic & Fast & Numerous increasing \\ Smart PV inverter & Continuous Watt and Var & Electronic & Fast & Numerous increasing \\ \hline \end{tabular}
\end{table} 
Table 1: Characterization of the voltage support resources of distribution networks integrated with EVs and PVs. operating costs in PV-rich industrial parks. The direct integration of a PV system with an EV charging station (EVCS) as the solar PV-based EVCS is a possible way to accommodate more clean energy and alleviate peak charging load [27]. Ref.