• Journal of Power Electronics
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• v.18 no.5
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• pp.1479-1488
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• 2018

Power packet (PP) distribution system distributes power to different loads that share the same distribution cable in a packetized form. When compared with conventional power systems, a PP distribution system (PPDS) can reduce standby power, eliminate Point-of-Load (PoL) power conversion, and intelligently control the load demand from the source side. Due to the absence of PoL conversion, when multiple power sources at different voltage levels and conditioning requirements jointly send power to various loads at different voltage ratings, the generated voltage has an irregular shape. A large filter at each of the load sides is required to reduce such a large voltage ripple. In this paper, a single-inductor, multiple-input-single-output converter structure based multiple-energy-source mixer is proposed. It combines PP generation, maximum power point tracking (MPPT) of renewable energy sources (RESs) and filtering at the source side. To demonstrate the possible renewable energy integration, a PV panel is used as a power source together with other constant voltage sources. The PV power is approximately tracked using the constant voltage method and it is used for each of the PP generations. The proposed PP distribution system is experimentally verified and it is shown that a conventional PI controller is sufficient for stable system operation.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3359-3364
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• 2007

The smart energy system is the integrated power system in which the power components including central station generation, distributed generation, renewable power generation, energy storage, and communications and controls are complexly connected with each other. In smart energy system, it is very important how to configure the diverse power generations and how to determine the operation mode of the chosen components with economic feasibility. In this study, we introduce the optimal planning method based on both economic feasibility and load profiles and its applications for the smart energy system in apartment. This method was considered very useful to determine the configuration and to decide the optimal operation mode of the smart energy system.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2323-2328
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• 2011

There have been many changes in Subway train types since SeoulMetro opened the Line No.1 in 1974. Propulsion control device has changed many times following the generations of control method from resistance control method which uses large resistor for the traction motor control to chopping control which uses power semiconductors and finally to inverter control. Railroad vehicle propulsion control device refers to devices such as converter/inverter which supply power for subway operation, power conversion equipment like small switching-mode power supply and traction motor. In this paper, we will analyze every part of railroad vehicle propulsion control device of SeoulMetro so we can find problems in the subway operation. And we will present propulsion control device model which makes minimized failures, efficient maintenance possible when replacing railroad vehicle later. By doing this, we hope to ensure stability and improve energy efficiency to the top.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.714-716
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• 2004

Owing to the environmental problems as well as increasing energy prices and power plant construction costs, many researches have been made for the safe operation of distributed generations. In order to be more popularly used in parallel with the distribution network, the distributed generation and its correlation with the power system should be exactly monitored at any time. This paper presents a monitoring system which displays the important states of the distributed generation in operation and stores various measurements of the system. The proposed system constructs a data-base for developing algorithms against any faults of the interconnected system, and monitors efficiently at any place with the communication network function.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.403-405
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• 2000

This paper presents a N-player game theory application for analyzing power transactions in a deregulated energy marketplace such as PoolCo, where, participants, especially, generating entities, maximize their net profits through optimal bidding strategies (i.e., bidding prices and bidding generations). In this paper, the electricity market for power transactions is modeled as a non-cooperative. N-player game with complete information, where the solution is determined in a continuous strategy domain having recourse to the Nash equilibrium idea.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.425-427
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• 2002

In a deregulated power market, a load model considered the characteristics of electric consumers is required and the congestion management of transmission lines should be resolved in a point of economic benefits. It is essential that the optimal power flow algorithm is applied to manage transmission line congestion. Therefore, in this paper, we implement the optimal power flow with object function of social welfare maximization based linear programming and analysis the nodal prices for generations and loads through a numerical study.

• Proceedings of the KAIS Fall Conference
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• 2005.05a
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• pp.231-233
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• 2005

국가차원의 신$\cdot$재생에너지 활성화 방안에 따라 지자체 등의 분산형전원 시설계획이 점차 증가하고 있으나, 아직 우리나라에는 분산형전원의 계통연계에 대한 체계적인 기술지침이 초기 단계에 있거나 제정 중에 있어서, 계통연계와 관련하여 발전사업자와 전력회사간의 이 해가 상충되는 등 문제점이 발생되고 있다. 현재 분산형전원 단지의 도입계획은 비교적 많은 반면에 이에 대한 해석방법과 기술적인 평가방안이 구체적으로 제시되어 있지 않아, 설치자(시도 및 지자체)와 각 배전지사에서 많은 혼돈과 어려움을 려고 있는 실정이다. 따라서 본 논문에서는 태양광, 풍력 등의 분산형전원이 배전계통에 도입되는 경우, 기술적인 평가 알고리즘을 제시하고자 한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.11
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• pp.1547-1553
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• 2017

Due to the high penetration ratio of dispersed generations, overvoltage problem of the feeder has become more an important issue in distribution system operation. This paper proposes a new method for the smart inverter to control reactive power to mitigate voltage rise by the reverse power flow from the DGs. The proposed method controls reactive power based on current measurement while conventional methods use voltage measurement which include unacceptably large errors. Various case studies using MATLAB simulation have been performed to verify effectiveness of proposed method.

• Journal of Electrical Engineering and Technology
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• v.7 no.1
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• pp.9-16
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• 2012

The present study presents the Phasor Discrete Particle Swarm Optimization (PDPSO) algorithm, an effective optimization technique, the multi-dimensional vectors of which consist of magnitudes and phase angles. PDPSO is employed in the configuration of micro-grids. Micro-grids are concepts of distribution system that directly unifies customers and distributed generations (DGs). Micro-grids could supply electric power to customers and conduct power transaction via a power market by operating economic dispatch of diverse cost functions through several DGs. If a large number of micro-grids exist in one distribution system, the algorithm needs to adjust the configuration of numerous micro-grids in order to supply electric power with minimum generation cost for all customers under the distribution system.

• KIEE International Transactions on Power Engineering
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• v.5A no.1
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• pp.9-15
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• 2005

In the operation of distribution systems, DGs (Distributed Generations) are installed as an alternative to extension and the establishment of substations, transmission and distribution lines according to the increasing power demand. In the operation planning of DGs, determining optimal capacity and allocation achieves economical profitability and improves the reliability of power distribution systems. This paper proposes a determining method for the optimal number, size and allocation of DGs in order to minimize the operation costs of distribution systems. Capacity and allocation of DGs for economical operation planning duration are determined to minimize total cost composed with power buying cost, operation cost of DGs, loss cost and outage cost using the GA (Genetic Algorithm).