• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1743-1753
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• 2017

Since there are multiple random variables in the probabilistic load flow (PLF) calculation of distribution system containing distributed generation (DG) and electric vehicle charging load (EVCL), a Monte Carlo method based on composite sampling method is put forward according to the existing simple random sampling Monte Carlo simulation method (SRS-MCSM) to perform probabilistic assessment analysis of voltage quality of distribution system containing DG and EVCL. This method considers not only the randomness of wind speed and light intensity as well as the uncertainty of basic load and EVCL, but also other stochastic disturbances, such as the failure rate of the transmission line. According to the different characteristics of random factors, different sampling methods are applied. Simulation results on IEEE9 bus system and IEEE34 bus system demonstrates the validity, accuracy, rapidity and practicability of the proposed method. In contrast to the SRS-MCSM, the proposed method is of higher computational efficiency and better simulation accuracy. The variation of nodal voltages for distribution system before and after connecting DG and EVCL is compared and analyzed, especially the voltage fluctuation of the grid-connected point of DG and EVCL.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1916-1924
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• 2017

Fossil oil, as the main energy of transportation, is destined to be exhausted. The electrification of transportation is a sustainable solution to the energy crisis, since electric power could be acquired from the inexhaustible sun, wind and water. Among all the problems that hinder the development of Electric Vehicle (EV) industry, charging issue might be the most prominent one. In this paper, the service process of a charging station with Battery Energy Storage System (BESS) is analyzed by means of $Cram{\acute{e}}r$ - Lundberg model which has been intensively utilized in ruin theory. The service quality is proposed in two dimensions: the service efficiency and the service reliability. The arrival rate and State of Charge (SOC) upon arrival are derived from 2009 National Household Travel Survey (NHTS). The simulations are performed to show how the service quality is determined by the system parameters such as the number of servers, the service rate, the initial capacity, the charge rate and the maximum waiting time. At last, the economic analysis of the system is conducted and the best combination of the system parameters are given.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.937-944
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• 2022

Electric vehicles (EVs) have been growing to reduce energy consumption and greenhouse gas (GHG) emissions in the transportation sector. The increasing number of EVs requires adequate recharging infrastructure, and at the same time, adopts low- or zero-emission electricity production because the GHG emissions are highly dependent on primary sources of electricity production. Although previous research has studied solar photovoltaic (PV) -integrated EV charging stations, it is challenging to optimize spatial areas between where the charging stations are required and where the renewable energy sources (i.e., solar photovoltaic (PV)) are accessible. Therefore, the primary objective of this research is to support decisions of siting EV charging stations using a spatial data clustering method integrated with Geographic Information System (GIS). This research explores spatial relationships of PV power outputs (i.e., supply) and traffic flow (i.e., demand) and tests a community in the state of Indiana, USA for optimal sitting of EV charging stations. Under the assumption that EV charging stations should be placed where the potential electricity production and traffic flow are high to match supply and demand, this research identified three areas for installing EV charging stations powered by rooftop PV in the study area. The proposed strategies will drive the transition of existing energy infrastructure into decentralized power systems. This research will ultimately contribute to enhancing economic efficiency and environmental sustainability by enabling significant reductions in electricity distribution loss and GHG emissions driven by transportation energy.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1234-1242
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• 2013

To verify the effectiveness of the proposed system, the charges in power demand are analyzed for an AC and DC distribution system for the existing V2G concept and electric vehicle charging stations connected to a Battery Energy Storage System. In addition, since many power-converter-based chargers are operated simultaneously in an EV charging station, the change in the system harmonics when several EV chargers are connected at a single point is analyzed through simulations.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.51-59
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• 2019

In this paper, we analyzed the relationship between charging operation system and electricity charges connected with charging infrastructure among data of many demonstration projects focused on electric vehicles recently. At this point in time, due to the rapid increase in demand for the electric charging infrastructure that will take place in the future, we can prepare for an upcoming era in the sense of forecasting the demand value. At the same time, demonstrating and modeling optimized system modeling centering on sites is a prerequisite. The modeling based on the existing small - scale simulation and the design of the operating system are based on the data linkage analysis. In this paper, we implemented a new optimized system modeling and introduced it as a standard format to analyze time - dependent time - divisional data for each vehicle and user in each point and node. In order to verify the efficiency of the optimization based on the data linkage analysis for the actual implemented electric car charging infrastructure and operation system.

• Journal of Information Technology Services
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• v.21 no.6
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• pp.117-125
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• 2022

In respond to climate change caused by global environmental problems, countries around the world are actively promoting the advancement of new electricity industries. The new energy business is being applied to energy storage systems (ESS), electric vehicle charging business, and power demand response using cutting edge technologies. In 2022, the Korean government is also establishing a policy stance to foster new energy industries and making efforts to improve its responsiveness to power demand response with the innovative technologies. In Korea, attempts to commercialize energy power are also being made in the private and public sectors to control energy power in houses, buildings, and industries. For example, private companies, local governments, and central government are making all-out efforts to develop new energy industry models through joint investment. There are forms such as establishing energy-independent facilities by region, establishing an electric vehicle charging system, controlling urban lighting systems with Information technologies, and managing demand between power suppliers and power consumers. This study examined the business model applied with energy storage system, electric vehicle charging business, smart lighting, and power demand response based on information communication technology to examine the site where smart energy system was introduced. According to this study, company missions and government tasks are suggested to apply new energy business technologies as economical energy solutions that meet the purpose of use by region, industry, and company.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.677-687
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• 2020

This paper deals with the electrical shock that can occur in a car wireless charging system. The recently released the Wireless Power Consortium (WPC) standard specifies that the receiver must be protected from the radio power generated by the transmitter and presents two scenarios in which the receiver may be subjected to electrical shock due to the wireless power generated by the transmitter. The WPC also provides a hardware approach for blocking the wireless power generated by the transmitter to protect the receiver in each situation. In addition, it presents the hardware constraints that must be applied to the transmitter and the parameters that must be constrained by the software. In this paper, we analyze the results of the electric shock in the vehicle using the WPC certified transmitter and receiver in the scenarios presented by WPC. As a result, we found that all the scenarios had electrical shocks on the receiver, which could have a significant impact on the receiver circuitry. Therefore, we propose wireless power transfer limit (WPTL) algorithm to protect receiver circuitry in various vehicle charging environments.

• Journal of electromagnetic engineering and science
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• v.11 no.3
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• pp.174-182
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• 2011

The On-line Electric Vehicle (OLEV) is an electric transport system in which the vehicle's power is transferred wirelessly from power lines underneath the surface of the road. Advantages of the OLEV include reducing battery size and cost to about 20 percent of that of conventional battery-powered electric vehicles, thereby minimizing the vehicle's weight and price, as well as the cost of charging the system. In this paper, we introduce a wireless power transfer mechanism to maximize the electrical performance of the power transfer system. Power transfer capacity, power transfer efficiency, and magnitude of leakage in the electromagnetic field (EMF) are analyzed, and the optimization methodology of the design parameters is discussed.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.2
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• pp.215-220
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• 2021

• International Journal of Automotive Technology
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• v.2 no.4
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• pp.157-164
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• 2001

The vehicle electric power system, which consists of two major components: a generator and a battery, which have to provide numerous electrical and electronic systems with enough electrical energy. A detailed understanding of the characteristics of the electric power system, electrical load demands, and the driving environment such as road, season, and vehicle weight is required when the capacities of the generator and the battery are to be determined for a vehicle. An easy-to-use and inexpensive simulation program may be needed to avoid the over/under design problem of the electric power system. A vehicle electric power simulator is developed in this study. The simulator can be utilized to determine the optimal capacities of generators and batteries. To improve the expandability and easy usage of the simulation program, the program is organized in modular structures, and is run on a PC. Empirical electrical models of various generators and batteries, and the structure of the simulation program are presented. For executing the vehicle electric power simulator, data of engine speed profile and electric loads of a vehicle are required, and these data are obtained from real driving conditions. In order to improve the accuracy of the simulator, numerous driving data of a vehicle are logged and analyzed.