-Due to increased concerns for rising oil prices and environmental problems, various solutions have been proposed for solving energy problems through tightening environmental regulations such as those regarding CO 2 reduction. Among them, Electrical Vehicles (EVs) are evaluated to be the most realistic and effective approach. Accordingly, research and development on EVs and charging infrastructures are mainly proceeding in developed countries. Since EVs operate using electric energy form a battery, they must be connected to the power system to charge the battery. If many EVs are connected during a short time, power quality problems can occur such as voltage sag, voltage unbalance and harmonics which are generated from power electronics devices. Therefore, when EVs are charged, it is necessary to analyze the effect of power quality on the distribution system, because EVs will gradually replace gasoline vehicles, and the number of EVs will be increased. In this paper, a battery for EVs and a PWM converter are modeled using an ElectroMagnetic Transient Program (EMTP). The voltage sag and unbalance are evaluated when EVs are connected to the distribution system of the Korea Electric Power Corporation (KEPCO). The simulation results are compared with IEEE standards.

-This paper analyzes the effect of voltage sag on distribution systems due to the connection of Electric Vehicles (EVs). In order to study the impact of the voltage sag on the power system, two scenarios have been selected in this paper. The distribution system and EVs are modeled using the Electro Magnetic Transients Program (EMTP). The numbers of EVs are predicted based on the number of vehicles in distribution system of Seoul. In addition, the number of EVs is set up using realtime traffic in Seoul to simulate Scenario I and II. The simulation results show that voltage sag can occur if the distribution system has more than 30% of the total number of vehicles.

Many studies have been performed to reduce electric consumption in railway systems. Due to its low conduction loss and high regenerative braking efficiency characteristics, the ESS powered railway system is chosen as a promising candidate for future railway systems. This paper introduces the ESS powered railway system and analyzes current power charge calculation methods that have been set up by KEPCO (Korea Electric Power Corporation). Based on the analysis, this paper proposes two different power charge reduction methods for the railway system. One is to smooth the peaks of traction energy consumption by supplying additional energy to the grid. The other is to save electric charge by reducing electric energy consumed by the railway during the energy peak time, 2 p.m.~5 p.m., which has highest 'Won/kWh' rates. To verify the effectiveness of the proposed method, the power charge of Seoul Metro Line 2 is recalculated using the method.

Smart transportation technologies are being rapidly developed for enhancing the smart grid establishment. Such technologies are mostly focused on electric vehicles. However, the electric railroad has advantages in various aspects such as facility construction and utilization over an electric vehicle. Therefore, in this paper, we introduce the train-to-grid system using the electric railroads for the smart grid, and propose a reduction method for the electricity prices. The proposed method obtains actual data from the currently operating railroad systems. Furthermore, the number of trains for charging and discharging batteries is decided by using the time-of-use price and the number of railroad operations. The electricity prices are then determined by the energy consumption calculated using the number of trains used for charging and discharging and the capacity of the energy storage system in the trains. The proposed method is simulated using real data, and its superiority is verified by comparing its electric prices with the conventional electricity prices.

-An Electric Vehicle (EV) is operated with the electric energy of a battery in place of conventional fossil fuels. Thus, a suitable charging infrastructure must be provided to expand the use of electric vehicles. Because the battery of an EV must be charged to operate the EV, expanding the number of EVs will have a significant influence on the power supply and demand. Therefore, to maintain the balance of power supply and demand, it is important to be able to predict the numbers of charging EVs and monitor the events that occur in the distribution system. In this paper, we predict the hourly charging rate of electric vehicles using transformation matrix, which can describe all behaviors such as resting, charging, and driving of the EVs. Simulation with transformation matrix in a specific region provides statistical results using the Monte-Carlo Method.

No abstract

No abstract