• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1276-1282
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• 2013

This paper proposes a stochastic modeling of plug-in electric vehicles (PEVs) distribution in power systems, and analyzes the corresponding clustering characteristic. It is essential for power utilities to estimate the PEV charging demand as the penetration level of PEV is expected to increase rapidly in the near future. Although the distribution of PEVs in power systems is the primary factor for estimating the PEV charging demand, the data currently available are statistics related to fuel-driven vehicles and to existing electric demands in power systems. In this paper, we calculate the number of households using electricity at individual ending buses of a power system based on the electric demands. Then, we estimate the number of PEVs per household using the probability density function of PEVs derived from the given statistics about fuel-driven vehicles. Finally, we present the clustering characteristic of the PEV distribution via case studies employing the test systems.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.742-751
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• 2018

Electric vehicles (EV) are emerging as the future transportation vehicle reflecting their potential safe environmental advantages. Vehicle to Grid (V2G) system describes the hybrid system in which the EV can communicate with the utility grid and the energy flows with insignificant effect between the utility grid and the EV. The paper presents an optimal power control and energy management strategy for Plug-In Electric Vehicle (PEV) charging stations using Wind-PV-FC-Battery renewable energy sources. The energy management optimization is structured and solved using Multi-Objective Particle Swarm Optimization (MOPSO) to determine and distribute at each time step the charging power among all accessible vehicles. The Model-Based Predictive (MPC) control strategy is used to plan PEV charging energy to increase the utilization of the wind, the FC and solar energy, decrease power taken from the power grid, and fulfil the charging power requirement of all vehicles. Desired features for EV battery chargers such as the near unity power factor with negligible harmonics for the ac source, well-regulated charging current for the battery, maximum output power, high efficiency, and high reliability are fully confirmed by the proposed solution.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.111-119
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• 2015

Smart Grid is a next-generation intelligent grid to optimize energy efficiency by integrating information and communication technologies to the existing power grid as a two-way exchange of information. HPGP communication standard for smart grid implementation has been developed for the emerging smart energy, home automation, electric vehicle communications applications. HPGP communication standard has the advantage of reducing cost and power consumption. Also, it can be interoperated with the previous HPAV communication standard. For the introduction of a new communication standard, the analysis of the reliability and interoperability verification is required. In this paper, we present sniffer test method as reliability test method about power line communication between PEV(Plug-in Electric Vehicle) and EVSE(Electric Vehicle Supply Equipment). Power line communication between PEV and EVSE is one of the most important Smart Gird applications. Also, we analyzed sniffer test results about power line communication based on HPGP between PEV and EVSE by using QCA7000 device, AVitar and Tool kit.