• KEPCO Journal on Electric Power and Energy
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• v.8 no.1
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• pp.9-14
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• 2022

Social infrastructure facilities such as production, transportation, gas and electricity facilities may experience poor performance depending on time, load, temperature, etc. and may require maintenance, repair and management as they are used. In particular, in the case of transformers, the process of managing them for the purpose of preventing them from failing is necessary because a failure can cause enormous social damage. The management of transformers should consider both technical and economic aspects and strategic aspects at the same time. Thus, it applies the Asset Management concept, which is widely used in the financial industry as an advanced method of transformer management techniques worldwide. In this paper, the operation and power outage data were secured for the asset management of the transformer for distribution, and the asset status was analyzed. Analysis of asset status using actual operation and power outage data is essential for assessing the statistical life and failure rate of the facility. Through this paper, the status of transformer assets for arbitrary A group distribution was analyzed, and the end of life and replacement life were calculated.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.300-307
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• 2008

Power management (PM) depends on the power state transition and system workload. The system model is composed of corresponding stochastic models of the power state and system queue. In this paper, stochastic models which can handle various PM techniques are developed. SRN (Stochastic Reward Nets), an extended Petri-Net, has facilities that represent system queue and various modelling functions. The SRN is employed for developing PM models. An adaptive timeout PM model is also introduced and the power consumption and performance of this model are compared with other existing PM techniques models such as greedy and N-Policy techniques.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.5
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• pp.257-265
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• 2004

The complex documentation involved in power system analysis software require a well-defined and friendly database system. We have developed an object-oriented database management system for power system analysis, and have described load flow analysis and transient stability analysis using object-oriented database(OODB). Database management systems are widely used and achieve high reliability of data management in the engineering fields. However relational database system have shortcomings in application to power system analysis. ill relational database, the data model is too simple for modeling complex data and database languages are very different from programming languages. Object-oriented techniques are sufficiently powerful to support data-modeling requirements of GUI applications. The GUI is implemented using C++ on a MS windows platform. The OODB supports data modeling requirements of GUI applications and the performance is well acceptable for Gill applications.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2211-2220
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• 2015

This paper analyzes multiple active management (AM) techniques of active distribution network (ADN), and proposes an optimal coordination model of intermittent distributed generation (IDG) accommodation considering the timing characteristic of load and IDG. The objective of the model is to maximize the daily amount of IDG accommodation under the uncertainties of IDG and load. Various active management techniques such as IDG curtailment, on-load tap changer (OLTC) tap adjusting, voltage regulator (VR) tap adjusting, shunt capacitors compensation and so on are fully considered. Genetic algorithm and Primal-Dual Interior Point Method (PDIPM) is used for the model solving. Point estimate method is used to simulate the uncertainties. Different scenarios are selected for the IDG accommodation capability investigation under different active management schemes. Finally a modified IEEE 123 case is used to testify the proposed accommodation model, the results show that the active management can largely increase the IDG accommodation and penetration.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.133-142
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• 2023

The large process plant is currently implementing predictive maintenance technology to transition from the traditional Time-Based Maintenance (TBM) approach to the Condition-Based Maintenance (CBM) approach in order to improve equipment maintenance and productivity. The traditional techniques for predictive maintenance involved managing upper/lower thresholds (Set-Point) of equipment signals or identifying anomalies through control charts. Recently, with the development of techniques for big analysis, machine learning-based AAKR (Auto-Associative Kernel Regression) and deep learning-based VAE (Variation Auto-Encoder) techniques are being actively applied for predictive maintenance. However, this predictive maintenance techniques is only effective during steady-state operation of plant equipment, and it is difficult to apply them during start-up and shutdown periods when rises or falls. In addition, unlike processes such as nuclear and thermal power plants, which operate for hundreds of days after a single start-up, because the pumped power plant involves repeated start-ups and shutdowns 4-5 times a day, it is needed the prediction and alarm algorithm suitable for its characteristics. In this study, we aim to propose an approach to apply the optimal predictive alarm algorithm that is suitable for the characteristics of Pumped Storage Power Plant(PSPP) facilities to the system by analyzing the predictive maintenance techniques used in existing nuclear and coal power plants.

• The Journal of the Korea Contents Association
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• v.8 no.9
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• pp.42-54
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• 2008

In recent years, embedded systems have been expanding their application domains from traditional embedded systems such as military weapons, robots, satellites and digital convergence systems such as celluar phones, PMP(Portable Multimedia Player), PDAs(Personal Digital Assistants) to Next Generation Personal Computers(NGPCs) such as eating PCs, wearable computers. The NGPCs are network-based, human-centric digital information devices diverged from the traditional PCs used mainly for document writing, internet searching and database management. Wearable computers with battery capacity and memory size limitations have to use real-time operating systems with small footprints and low power management techniques to provide user's QoS in spite of hardware constraints. In this paper, we have designed and implemented a low-power RTOS (called eRTOS) for wearable computers. The implemented eRTOS has 18KB footprints and the dynamic power management and the device power management schemes are adapted in it. Experimental results with wearable computer applications show that the low power techniques could save energy up to 47 %.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1434-1439
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• 2011

The purpose of this study is based on the optimize the system life cycle cost apply to the advanced systems engineering techniques consideration thought to the system life cycle for the power system which is the one of the major component of the light rail transit system. Generally, the systems engineering techniques apply to the LRT's power systems are not optimize the whole life cycle cost of the power systems because systems engineering management activities are concentrate in performing the key-technology oriented at the construction stage of the dedicated power systems for light rail transit. Through this study, All the stakeholders can be utilize a this advanced systems engineering techniques which is fully considered the life cycle cost through the considering in whole system life cycle (such as concept, design, operation, maintenance and dispose stage as well as construction stage) and adopted by KSX ISO/IEC 15288 system life cycle processes.

• Journal of the Korea Safety Management & Science
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• v.24 no.2
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• pp.67-76
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• 2022

Power generation construction projects involving large amounts of capital can affect the survival of a company along with huge economic losses in the event of a business failure. In general, private companies are organizations with challenging risk taking tendencies while public companies have a risk averse tendency to avoid risk, so these differences in organizational tendencies make it difficult to respond to risk. In particular, public companies are more likely to fail than private companies because they choose the contradiction of risk picking to enter overseas markets with high uncertainty despite their tendency to risk averse due to the nature of the organization. Therefore, these organizations need risk management techniques that reflect a risk-averse strategy. Accordingly, this paper analyzes the risk management research papers of the existing overseas development EPC business in order to find the risk management techniques related to the organizational tendencies of public companies and proposes "establishing a performance audit system for risk management of the organizational tendencies of public companies" as a way to extract the risk factors through the examples of overseas development projects of public companies and to manage the organizational tendencies of public companies that affect them.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.69-78
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• 2007

In recent years, embedded mobile systems have been expanding their application domains from embedded portable devices which only execute a specialized application such as MP3 player or digital camcoder to digital convergence devices which execute more complicated applications converged various functionalities such as video and audio play, digital dictionary, DMB, games, phone, etc. As it requires the increasing hardware performance such as more faster CPU and more larger RAM, display, disk size, it has brought about a corresponding increase in power consumption. However, coupled with relatively small gains in battery capacity over recent years, the importance of software architecture including intelligent power management has become paramount. In this paper, we have ported UbiFOSTM with energy saving techniques on the ARM9-based MBA2440 platform. For energy savings, we adapted the dynamic power management and the device power management schemes based on monitoring workload. Experimental results with some well-known applications show that proposed low power technique could save energy up to 24 %.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.1965-1970
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• 2016

This paper studies generator rescheduling technique for congestion management in power system with wind farms. The proposed technique is formulated to minimize the rescheduling cost of conventional and wind generators to alleviate congestion subject to operational line overloading. The generator rescheduling method has been used with incorporation of wind farms in the power system. The locations of wind farms are selected based upon power transfer distribution factor (PTDF). Because all generators in the system do not need to participate in congestion management, the rescheduling has been done by generator selection based on the proposed generator sensitivity factor (GSF). The selected generators have been rescheduled using linear programming(LP) optimization techniques to alleviate transmission congestion. The effectiveness of the proposed methodology has been analyzed on IEEE 14-bus systems.