# Research on Optimal Voltage Control of Distribution Network with the Participation of EVs and PVs
## 4 Discussion  
Based on the case studies discussed in Section 3, the proposed two-stage voltage regulation scheme can improve the grid voltage distribution pattern with the aid of the coordination between conventional voltage regulation resources and distributed voltage resources, including PVs and EVs. For the day-ahead control, the daily optimal operation settings of OLTC transformers and CBs are predefined based on the day-ahead forecasting of preliminary load consumptions, EV charging demands, and solar PV generations. Due to the limited number of taps or capacitor units, the voltage regulation objective of the day-ahead control is to mitigate the potential voltage violations with minimum operating costs. Based on the case studies performed in Section 3, it turns out that the proposed day-ahead control can successfully keep all the bus voltages within the safe operation margin. However, the limited setting points of OLTCs and CBs bring in discrete voltage regulation, which cannot fully address the issues of voltage deviations and fluctuations. To further alleviate the voltage deviations and voltage fluctuations, intraday control is introduced where the voltage support capability of distributed PVs and EVs is considered. For the distributed PV systems, the voltage droop control is applied, for which the PV systems will automatically adjust their reactive power according to the predefined linear correlation between the maximum reactive power available and the terminal voltage. It should be noted that the reactive power compensation capability of a PV system is directly affected by its active power output (as discussed in Section 2.2.2). Due to the power constraint of PV inverters, higher active power generation indicates less reactive power compensation  
Figure 21: The optimal EV charging schemes achieved from the intraday control (EV charging and discharging are represented by green color and red color respectively). Figure 20: The bus voltage improvement achieved from the intraday control. capability for a PV system. For EVs connected to charging stations, their voltage support capability is achieved by the optimal scheduling of the EV charging/discharging powers under the premise of meeting the charging requirements of EV users. However, due to spatiotemporal uncertainties of EV charging behaviors and the diversified EV charging patterns of different types, the EV grid support capability will vary with the EV availability and the EV fleet composition. In addition, the EV users' willingness to participate in the grid voltage support can be affected by factors like the price subsidy, battery state of health, traffic conditions, etc. Accordingly, predicting the EV availability for the grid voltage support is complex, and the uncertainty of EV availability further affects the distribution voltage support performance of the connected EV charging station. To deal with the stochastic nature of EV charging behavior and EV drivers' willingness to participate in V2G service, a ROCS-based control scheme is proposed for which the control window length is self-adjusted based on the monitored states of EVs and EV chargers. The case study results demonstrate that the ROCS-based intraday control can further alleviate the grid voltage deviation and fluctuation to some extent when compared to the voltage distribution patterns achieved by the day-ahead control. Due to the constraints of satisfying EVs' desired departure SoC and PVs' maximum power generation, the distribution voltage regulation capability of the ROCS-based intraday control is limited. To enhance the voltage support capability of intraday control, onsite battery energy storage systems can be incorporated into solar PV farms and EV charging stations to achieve a mild decoupling among EVs, PVs, and the distribution network. As indicated in this work, the voltage support capability of a specific EV charging station is mainly decided by the time-varying EV availability and EV fleet composition.