• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1043-1050
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• 2014

Obsolescent control systems for power systems are evolving into intelligent systems and connecting with smart devices to give intelligence to the power systems. As networks of the control system are growing, vulnerability is also increasing. The communication network of distribution areas in the power system connects closely to vulnerable environments. Many cyber-attacks have been founded in the power system, and they could be more critical as the power system becomes more intelligent. From these environment, new communication network architecture and mitigation method against cyber-attacks are needed. Availability and Fault Tree analysis used to show that the proposed system enhances performance of current control systems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.365-369
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• 2015

In this paper, geographic information system(GIS) for an intelligent power distribution network was implemented with location informations acquired from automatic meter reading system, where the location informations of power line communication(PLC) modems installed at customer side were collected at data concentration units(DCUs) of headend equipment via PLC and then were transmitted to front end processor server. By displaying the connection status of the power distribution network on GIS map, operation of advanced metering infrastructure(AMI) or management of power grid system could be performed intuitionally and in real time, because the configuration state of the power grid could be easily monitored. The feasibility of the proposed system was confirmed with the especially constructed laboratory-level test bed and the verification test of the system will be carried out for a real power distribution network.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1807-1813
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• 2018

In this paper, the fault line selection and location problems of single line-to-ground (SLG) fault in distribution network are addressed. Firstly, the adaptive filtering property for empirical mode decomposition is formulated. Then in view of the different characteristics showed by the intrinsic mode functions(IMF) under different fault inception angles obtained by empirical mode decomposition, the sign of peak value about the low-frequency IMF and the capacitance transient energy is chosen as the fault line selection criteria according to the different proportion occupied by the low-frequency components. Finally, the fault location is determined based upon the comparison result with adjacent fault passage indicators' (FPI) waveform on the strength of the interaction between the distribution terminal unit(DTU) and the FPI. Moreover, the logic nodes regarding to fault line selection and location are newly expanded according to IEC61850, which also provides reference to acquaint the DTU or FPI's function and monitoring. The simulation results validate the effectiveness of the proposed fault line selection and location methods.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.6
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• pp.115-121
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• 2011

Intelligent distribution equipment is inevitable to realize self-healing which is one of smart grid functions in distribution network. Therefore, most of distribution equipment have been developed with self diagnostic sensors. However, it is not effective to construct on-line monitoring system for underground distribution cable because of high cost and low sensitivity. Recently, optical fiber composite cable is being considered for communication and power delivery in order to cope with increasing communication in distribution network. This paper presents the design and performance assessment results of underground cable on-line monitoring system using DTS(Distributed Temperature Sensing) and optical fiber composite underground cable.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.580-590
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• 2018

Active distribution system (ADS) considering distributed generation (DG) and electric vehicle (EV) is an effective way to cut carbon emission and improve system benefits. ADS is an evolving, complex and uncertain system, thus comprehensive model and effective optimization algorithms are needed. Battery swapping station (BSS) for EV service is an essential type of flexible load (FL). This paper establishes ADS planning model considering BSS firstly for the minimization of total cost including feeder investment, operation and maintenance, net loss and carbon tax. Meanwhile, immune binary firefly algorithm (IBFA) is proposed to optimize ADS planning. Firefly algorithm (FA) is a novel intelligent algorithm with simple structure and good convergence. By involving biological immune system into FA, IBFA adjusts antibody population scale to increase diversity and global search capability. To validate proposed algorithm, IBFA is compared with particle swarm optimization (PSO) algorithm on IEEE 39-bus system. The results prove that IBFA performs better than PSO in global search and convergence in ADS planning.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.19-29
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• 2019

Recently, with the rise of environmental issues and the change of government policy (Renewable Energy 3020 Implementation Plan), a large amount of renewable energy such as solar and wind power is connected to the power system, and most of the renewable energy is concentrated in the power distribution network. This causes many problems with the voltage management and the protection coordination of the grid due to the its intermittent power generation. In order to effectively operate the distribution network, it is necessary to deploy more intelligent terminal devices in the field to measure the status of the distribution network and develop various operation functions such as visualization and big data analysis to support the power distribution system operators. In addition, the failover technology must be supported for the non-stop operation of the power distribution system. This paper proposes the system architecture of new power distribution management system to cope with high penetration of renewable energy. To verify the proposed system architecture, the functional unit test and performance measurement were performed.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.93-99
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• 2021

The government has proposed a mission to enhance intelligent power networks, decrease coal-fired generation, expand distributed energy resources, and promote energy prosumer into the distribution network in Korea. Installation cost of facility expansion to guaranteed interconnection with small distributed energy resources increases dramatically on KEPCO's distribution sector. And it is hard to withdraw in time. In addition, there are explicit research is required to meet the reliability on grid corresponding to the increase of distributed power. Infrastructure support for accommodating energy prosumer is also needed. Therefore, KEPCO is pushing transition to DSO by expanding distribution management scope and changing its roles. In addition, KEPCO is proactively preparing for integrated operation between distribution network and existing distributed power which is accommodated passively. KEPCO is also trying to accept multiple network users, e.g. building platforms, to manage a data and promote new markets. In the long term, transition to DSO will achieve saving investment costs for accommodating distributed sources and maintaining stable electrical quality. And it will be possible to create new business model using the platform to secure revenue.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.672-681
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• 2012

A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.106-111
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• 2010

Electronic watt hour meters(WHM) for high pressure running in domestic were installed to the digital type meter and ones for low pressure are expected to complete within several years. Domestic power metering technology is being beyond a simple framework with an electronic type and is rapidly evolving to intelligent smart metering systems in conjunction with promotion of a national smart grid project. Major policy outlook of the world's major power company regarding Intelligent metering is the application of the fare structure diversification and is the improvement of level of service to customers. In addition, electric power companies should focus on the cost reduction and the improvement of management efficiency through an efficient operation of distribution facility. In this paper, we are about to make an observation of the additional services technology development trend of the overseas smart meter and to have a view of value-added services(VAS) system of smart meter suitable for the domestic environment based on the technology development of VAS utilizing electronic watt hour meter performed by recent research projects.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.115-123
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• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.