# V2G Strategies to Flatten the Daily Load Curve in Seoul, South Korea
## 1 Introduction
In [6], an algorithm was presented to calculate the daily load curve of electric vehicles charged by buses based on the daily charging patterns of electric vehicles according to electric vehicle supply scenarios, and to evaluate the effect of the bus load using power fluctuation analysis; however, there are downsides to this that were not taken into account. In addition, ref. [7] presented the V2G optimization technology problem for grid peak reduction, and the V2G scheduling optimization problem, that is, the problem of minimizing peaks and finding grid constraints with smart V2G technology; this seems difficult and interesting, but the problem of flattening the daily load curve was not reviewed. In [8], research focused on studying the optimal locations of electric vehicle charging stations. Also, in New York City, USA, research was conducted on how to distribute grid load and reduce costs by applying an intelligent EV charging method in order to charge the EV load during valley fill time [9]. The valley fill method is a technology that equalizes the overall load by inducing an increase in the charging load during a low-charging load-time period. Research is ongoing in Ireland to optimize EV charging cycles using demand-side management (DSM) in order to reduce both consumer costs and peak load demand on the grid [10]. In another study [11], an EV scheduling algorithm was developed to meet charging requirements of EV owners through an impact analysis of DRM (demand response management). Another study conducted in Winnipeg, Canada [12], used vehicle usage data to predict and analyze EV charging through probabilistic methods. In [13], a study was presented on minimizing peak reduction and voltage regulation problems through smart load management in residential area distribution systems. There was also a study of EV TOU (time of use) rates required to minimize the impact of EV charging on the grid. However, there are not enough studies on how to flatten the daily load curve of the metropolitan power grid using the V2G strategy of electric vehicles based on TOU and SMP rates. Several studies have explored TOU tariff system models to minimize EV charging costs in regulated markets [13] and reduce the impact of EV charging on the grid [14; 15]. In ref. [16], a solution is presented for how to optimize energy management by additionally utilizing ESS to reduce electric energy bills according to the TOU pricing scheme of housing systems with PV and EV charging. Also, in ref. [17], the authors propose a charge-discharge scheduling strategy utilizing G2V/V2G and a battery energy storage system (BESS) to further improve the operation of electric vehicle charging stations. In [18], the pattern of the daily load curve according to the EV charging pattern in Seoul was analyzed, but the discharge of the EV was not considered at the same time. Another study attempted to improve efficiency by applying an energy management strategy (EMS) to fuel cell electric vehicles (FCEVs) and hybrid electric buses (FCHEBs) for low-carbon driving [19; 20; 21]. From this perspective, most studies focus on proposing sequential charging, reducing power loss, reducing charging rates for electric vehicle owners, TOU strategies for the highest savings, and implementing EV charging stations using energy storage devices (ESSs). However, there are not enough studies based on TOU and SMP plans to flatten the daily load curve of the metro power grid by using the electric vehicle V2G strategy. Since there are few studies that have analyzed the effect of flattening the grid, it is essential to evaluate V2G strategies on how much the impact of the grid can be reduced by efficient charging and discharging of electric vehicles in the wide-area grid of a large metropolitan city. In general, EV owners want to charge and discharge their electric vehicles at work or at home, mainly because they are commuting vehicles, so it is essential to model V2G effects by place and time of charging and discharging, at home or at work.