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Recently, the generalization of P2P (peer-to-peer) technology with enhanced security due to blockchain technology and the expansion of renewable energy-based distributed energy resources have led to blockchain technology being applied in power transactions, thus giving the potential to become a new platform for DC microgrid operation. Meanwhile, the voltage of a DC microgrid represents the balance of energy supply and demand and also serves as a stability index. The balance is represented as a steady state; the stability is represented during and after events. This paper examines the stability of the DC microgrid built on a university campus in Korea and, in particular, the blockchain technology-based power transactions performed in the DC microgrid. The test is based on the pre-planned transaction schedule applied in the DC microgrid. The transaction schedule has used day-ahead and real-time bidding data. Although many technologies are included in the project, this paper focuses on the voltage stability of the DC microgrid. In addition, the DC protection is applied and evaluated. To consider general DC protection, the DC breaker was simplified with several IGBTs, diodes, capacitors, and arrestors and was designed to interrupt the fault current within five milliseconds. The stability was evaluated using a PSCAD/EMTDCTM.

In order to meet the increasing demand for electricity to maintain electric vehicles (EVs) worldwide, this paper aims to improve our understanding of the impact of the load on the power grid generated by the charging and discharging of electric vehicles. The rapid development of the electric vehicle (EV) industry offers new economic and environmental benefits, such as mitigating global warming by reducing carbon dioxide. On the other hand, however, we will face the reality that the emergence of such large-scale EVs will undoubtedly put additional strain on the power grid. In this context, solving the problem of excessive power usage associated with charging large electric vehicles and reducing the impact on the grid is paramount. Accordingly, in order to meet the increasing demand for electricity to maintain electric vehicles (EVs) worldwide, this paper aims to improve our understanding of the impact of the load on the power grid generated by the charging and discharging of electric vehicles. A V2G strategy is presented with the goal of flattening the daily load curve by considering the charge and the discharge positions of EVs. First, in this paper, based on the estimated share of electric vehicles, we set the assumption that EVs travel to work in the morning and leave work in the afternoon. Second, we develop an efficient V2G strategy to equalize the daily load curve due to charging and discharging of electric vehicles in Seoul by applying a system marginal price (SMP) and time-of-use (TOU) rate system. The EV charging/discharging load and existing load using V2G modeling are added up, all daily load curves are calculated and analyzed based on the 2030 and 2040 EV share scenarios for Seoul, and the grid load is leveled. The analysis suggests measures to minimize the impact of EV loads on the power grid according to the V2G strategy based on charging and discharging plans. Overall, this paper aims to smooth the grid’s daily load curve and avoid grid overload by applying appropriate SMP and TOU plans; we also present an efficient V2G strategy, established through charge and discharge modeling and EV charge and discharge management techniques, in order to minimize grid expansion.

This paper presents a methodology to calculate daily charging load curves in Seoul, South Korea, by taking into account plug-in electric vehicles (PEVs) charging stations, allowing Seoul’s government to determine the PEVs charging effect on the load. In particular, the study calculates the charging power of uncontrolled PEVs charging in terms of the daily operating characteristics of a vehicle traveling between home and workplace, with respect to PEVs charging stations in the city, according to the PEVs’ market share. For the controlled PEVs charging strategy based on morning and afternoon work-to-home and vice versa traffic characteristics and time-of-use (TOU) prices in Seoul, the study calculates daily load patterns of uncontrolled and controlled charging scenarios. After adding the calculated values to the existing load, the study assesses and compares their effects on the power grid. The results are as follows. If by 2030 the share of electric vehicles is 10%, compared to the existing load, the total load increases by about 13% between 9:00 and 11:00 in the morning for the uncontrolled mode and by about 10% for the controlled mode. The total load increases by about 16% between 20:00 and 22:00 for the uncontrolled mode and 17% for the controlled mode. However, if by 2040 the share of electric vehicles is 30%, compared to the existing load, the total load increases by about 35% between 9:00 and 11:00 in the morning for the uncontrolled mode and by about 32% for the controlled mode. Between 20:00 and 22:00, the uncontrolled mode’s total charging load increases by about 35% and the controlled mode’s total load by about 32%. The analysis also demonstrated that it was possible to achieve a significant load-leveling effect in all charging periods for the controlled mode, with the daily load pattern’s average leveling rate increasing by 8% and 13% in 2030 and 2040, respectively, based on the TOU price system compared with the uncontrolled mode. Based on these results, it is possible to determine the PEVs’ hourly charging load effect on the power grid in Seoul and establish a PEVs charging load management plan to prevent the power grid reinforcement and expansion and to satisfy its overload constraint by using an appropriate TOU price plan.