• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.81-88
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• 2018

Performance evaluation of a plant to efficiently manage and maintain the performance of the plant is a very important procedure. However, since the conventional performance evaluation method is an Excel-based manual method, the preparation procedure is complicated and the versatility is poor. In this paper, we analyze the problems of the existing performance evaluation system, effectively model the equipment, calculate the missing physical properties, and improve the versatility, efficiency and accuracy of the performance evaluation through the equipment modeler which performs automatic index calculation based on this.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.63-66
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• 2018

Lattice towers and tubular steel poles have been commonly used for electrical power transmission in Korea as well as the other countries. They are durable, structurally stable, simple and can easily be constructed in limited spaces. However, residents are opposed to construct transmission lattice towers in their areas because they are not visually attractive, and electrical field occur at the transmission lines. Underground transmissions have been used instead of the traditional towers to resolve these problems, however they are not cost effective to construct and run. Therefore, we have developed compact towers that are more attractive, well blend into the surrounding environment and much more economical than underground transmissions. This paper shows the design of a compact towers with insulation arm, in order to reduce the height of tower and the separation between phases. The compact tower can be installed in a narrow right-of-way. Insulation arms are easily applied to lattice and steel tubular towers instead of steel arms. Compact towers with insulation arm are also considered as a solution to have public acceptance or to create a familiar atmosphere among towers and people. Compact tower compared with a conventional tower, insulation arms reduces the width and height of the tower by 20% and 15% respectively.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.89-99
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• 2018

Downtime and malfunction of industrial rotor machines represents a crucial cost burden and productivity loss. Fault diagnosis of this equipment has recently been carried out to detect their fault(s) and cause(s) by using fault classification methods. However, these methods are of limited use in detecting rotor faults because of their hypersensitivity to unexpected and different equipment conditions individually. These limitations tend to affect the accuracy of fault classification since fault-related features calculated from vibration signal are moved to other regions or changed. To improve the limited diagnosis accuracy of existing methods, we propose a new approach for fault diagnosis of rotor machines based on the model generated by supervised learning. Our work is based on feature residual values from vibration signals as fault indices. Our diagnostic model is a robust and flexible process that, once learned from historical data only one time, allows it to apply to different target systems without optimization of algorithms. The performance of the proposed method was evaluated by comparing its results with conventional methods for fault diagnosis of rotor machines. The experimental results show that the proposed method can be used to achieve better fault diagnosis, even when applied to systems with different normal-state signals, scales, and structures, without tuning or the use of a complementary algorithm. The effectiveness of the method was assessed by simulation using various rotor machine models.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.1
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• pp.11-15
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• 2019

Recently, the circuit-breaker rated voltage is getting higher as the transmission voltage increases. To increase the circuit-breaker rated voltage, a multi-break circuit-breaker which has two or more breakers in series is adopted. For multi-break circuit-breaker, a grading capacitor is used to mitigate the Transient Recovery Voltage(TRV) and control the voltage distribution across the individual interrupter units. However, all over the world, there are many failures such as mechanical damage, explosion due to insulation breakdown. Therefore, it is necessary to study the causes of failure and the new performance verification method. In this paper, we investigate the causes of dielectric breakdown of the grading capacitors in the KEPCO power system and propose the performance verification method.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.97-107
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• 2014

The development of ICT has led positive aspects such as popularization of Internet. It, on the other hand, is causing a negative aspect, Cyber Terror. Although the causes for recent and continuous increase of cyber security incidents are various such as lack of technical and institutional security measure, the main cause which threatens the cyber security is the users' lack of awareness and attitude. The purpose of this study is the positive analysis of how the personal and job characteristics influence the cyber security training participation rate and the response ability to cyber terror response training with a sample case of K-corporation employees. In this paper, the relationship among career, gender, department, whether he/she is a cyber security specialist, whether he/she is a regular employee), "ratio of cyber security training courses during recent three years", "ratio that he/she has opened the malicious email in cyber terror response training during recent three years", "response index of virus active-x installation (higher index means poorer response)" is closely examined. Moreover, based on the examination result, the practical and political implications regarding K-corporation's cyber security courses and cyber terror response training are studied.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.137-143
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• 2021

As an electrochemical water electrolysis for green hydrogen production, both polymer electrolyte membrane (PEM) and alkaline electrolyte are being developed extensively in various countries. The PEM electrolyzer with high current density (above 2 A/cm²) has the advantage of being able to design a simple structure. Also, it is known that it has high response to electrical output fluctuations. However, the cost problem of major components is the most important issue that a PEM electrolyzer must overcome. Instantly, there are platinum group metal (PGM)-based electrocatalysts, fluorine-based polyfluoro sulfuric acid (PFSA) membrane, Ti felt (porous transport layer, PTL) and so on. Another challenging issue is productivity. A securing outstanding productivity brings price benefits of the electrolytic cells. From this point of view, we conducted basic studies on manufacturing electrode and membrane electrode assembly (MEA) for PEM electrolyzer production.

• 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.

• 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.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.171-177
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• 2021

In terms of distribution planning, accurate electric load prediction is one of the most important factors. The future load prediction has manually been performed by calculating the maximum electric load considering loads transfer/switching and multiplying it with the load increase rate. In here, the risk of human error is inherent and thus an automated maximum electric load forecasting system is required. Although there are many existing methods and techniques to predict future electric loads, such as regression analysis, many of them have limitations in reflecting the nonlinear characteristics of the electric load and the complexity due to Photovoltaics (PVs), Electric Vehicles (EVs), and etc. This study, therefore, proposes a method of predicting future electric loads on distribution lines by using Machine Learning (ML) method that can reflect the characteristics of these nonlinearities. In addition, predictive models were developed based on actual data collected at KEPCO's existing distribution lines and the adequacy of developed models was verified as well. Also, as the distribution planning has a direct bearing on the investment, and amount of investment has a direct bearing on the maximum electric load, various baseline such as maximum, lowest, median value that can assesses the adequacy and accuracy of proposed ML based electric load prediction methods were suggested.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.153-159
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• 2021

A two-step process for increasing the leaching efficiency of yttrium and neodymium from coal fly ash were investigated at solid loadings of 5.0 g ash ~1,000 g ash/l of 1.0 N~10.0 N H₂SO₄, temperature ranging from 30℃ to 90℃, ultrasonic leaching time of 1~10 hours, and ultrasonic power of 25~200 W. The yttrium and neodymium from coal fly ash were effectively leached into ion phases by step change of the first conventional dissolution at room temperature and then the second heating process with the aid of ultrasonic wave, and maximum leaching efficiency of yttrium and neodymium obtained were 66 % and 63 %, respectively. The activation energies for the leaching reaction of yttrium and neodymium at second heating process dependent on leaching time and temperature were derived to be 41.540 kJmol^-1 and 507.92 kJmol^-1, respectively. The optimum conditions for the maximum leaching of yttrium and neodymium were found to be the solid loading of 250 g ash/l of H₂SO₄, solvent concentration of 2.0 N H₂SO₄, and second step process of temperatures of 30℃ for 3 hours and then 90℃ for 4 hours with ultrasonic intensity of 100 W.