• KIEE International Transactions on Power Engineering
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• v.5A no.2
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• pp.109-115
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• 2005

Recently, the needs and concerns regarding power loss have been increasing according to energy conservation at the level of the national policies and the business strategies of power utilities. In particular, the issue of power loss is the main factor for determining rates for electrical consumption in the deregulation of the electrical industry. However, because of the lack of management for power loss load factors (LLF) it is difficult to make a calculation for power loss and to make a decision concerning the electric rates. Furthermore, loss factor (k-factor) in Korea, which is of primary significance in the calculation of distribution power loss, has been used as a fixed value of 0.32 since the fiscal year 1973. Therefore, this study presents the statistical calculation methods of the loss factors classified by load types and seasons by using the practical data of 65 primary feeders that have been selected by appropriate procedures. Based on the above, the algorithms and methods, as well as the optimal method of the distribution loss management classified by facilities such as primary feeders, distribution transformers and secondary feeders is presented. The simulation results demonstrate the effectiveness and usefulness of the proposed methods.

• Korean Management Science Review
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• v.28 no.3
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• pp.73-82
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• 2011

Basel II advanced measurement approaches for operational risk need to estimate the frequency and severity distribution of operational losses. Due to lack of internal loss data, the estimation is impossible in many cases and so external loss data might be used by scaling on asset or gross income. To get around lack of loss data, scenario analysis combined with loss distribution approach can be useful in calculating the capital charge of operational risk. However, scenario based loss distribution approach requires much time and effort. Instead we may apply the analytic hierarchy process to measure operational risk of financial institutions. The analytic hierarchy process combined with loss distribution approach is to estimate the capital charge of operational risk in other areas based on the operational VaR in an area with sufficient loss data. AHP provides a tool for timely measurement of operational risk in this rapidly changing global environment.

• Journal of Korean Society for Quality Management
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• v.31 no.1
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• pp.109-122
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• 2003

This paper presents a robust process capability index(PCI) based on the expected loss derived from the empirical distribution function(EDF). We propose the EDF expected loss in order to develop a PCI that does not depends on the underlying process distribution. The EDF expected loss depends only on the sample data, so the PCI based on it is robust and it does nor require complex calculations. The inverted normal loss function(INLF) is employed in order to overcome the drawback of the quadratic loss which may Increase unboundedly outside the specification limits. A comprehensive simulation study was performed under various process distributions, in order to compare the accuracy and the precision of the proposed PCI with those of the PCI based on the expected loss derived from the normal distribution. The proposed PCI turned out to be more accurate than the normal PCI in most cases, especially when the process distribution has high kurtosis or skewness. It is expected that the proposed PCI can be utilized In real processes where the true distribution family may not be known.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.26-31
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• 2011

In this paper, we focused on the loop distribution system to solve the international issues of energy depletion and global warming. The conventional method of reconfiguration of distribution system was moving open points of switches from an actual switch position to another, while an appropriate switch must be opened to preserve the radial structure and this procedure is continued til there is no further loss reduction. However, the loop distribution system is the best optimization method to minimize loss than the other methods which is preserving radial structure. So we analyzed 3 types of loop distribution system upgraded from radial distribution system by changing normally open switch to normally closed switch. The simple 3 types of model system for simulation were composed, and each types of loop system were simulated in accordance with varying parameters. As a result of simulations, the loss reduction was different for each types of loop distribution system and each loop types have constraints for composing loop distribution system. The algorithms propose the method how to construct loop distribution system regarding constraints. Type I that needs least requirements get least loss reduction and Type III that needs most requirements get maximum loss reduction. On the other hand, Type I was most feasible distribution system to be realized.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.45-51
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• 2014

Distribution system is a critical link between customer and utility. The control of power loss is the main factor which decides the performance of the distribution system. There are two methods such as (i) distribution system reconfiguration and (ii) inclusion of capacitor banks, used for controlling the real power loss. Considering the improvement in voltage profile with the power loss reduction, later method produces better performance than former method. This paper presents an advanced evolutionary algorithm for capacitor inclusion for loss reduction. The conventional sensitivity analysis is used to find the optimal location for the capacitors. In order to achieve a better approximation for the current candidate solution, Opposition based Differential Evolution (ODE) is introduced. The effectiveness of the proposed technique is validated through 10, 33, 34 and85-bus radial distribution systems.

• Journal of Information Technology Services
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• v.4 no.1
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• pp.129-139
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• 2005

This paper proposes a framework of Operational Risk-based Business Continuity System(ORBCS), and develops protection system for operational risk through operational risk assessment and loss distribution approach based on risk management guideline announced in the basel II. In order to find out financial operational risk, business processes of domestic bank are assorted by seven event factors and eight business activities so that we can construct the system. After we find out KRI(Key Risk Indicator) index, tasks and risks, we calculated risk possibility and expected cost by analyzing quantitative data, questionnaire and qualitative approach for AHP model from the past events. Furthermore, we can assume unexpected cost loss by using loss distribution approach presented in the basel II. Each bank can also assume expected loss distributions of operational risk by seven event factors and eight business activities. In this research, we choose loss distribution approach so that we can calculate operational risk. In order to explain number of case happened, we choose poisson distribution, log-normal distribution for loss cost, and estimate model for Monte-Carlo simulation. Through this process which is measured by operational risk. of ABC bank, we find out that loss distribution approach explains closer unexpected cost directly compared than internal measurement approach, and makes less unexpected cost loss.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.33-55
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• 2007

The economic world is full of patterns, many of which exert a profound influence over society and business. One of the most contentious is the distribution of wealth. Way back in 1897, an Italian engineer-turned-economist named Vilfredo Pareto discovered a pattern in the distribution of wealth that appears to be every bit as universal as the laws of thermodynamics or chemistry. The present paper proposes some Bayes estimators of shape parameter of Pareto income distribution in censored sampling. Asymmetric LINEX loss function has been considered to study the effects of overestimation and underestimation. For the prior distribution of the parameter involved a number of priors including one and two-parameter exponential, truncated Erlang and doubly truncated gamma have been contemplated to express the belief of the experimenter s/he has regarding the parameter. The estimators thus obtained have been compared theoretically and empirically with the corresponding estimators under squared error loss function, some of which were reported by Bhattacharya et al. (1999).

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.6
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• pp.340-349
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• 2004

Recently, the needs and concerns for the power loss are increasing according to the energy conservation at the level of the national policies and power utilities's business strategies. Especially, the issue of the power loss is the main factor for the determining the electric pricing rates in the circumstances of the deregulation of electrical industry. However, because of the lacking of management for power loss load factors (LLF), it is difficult to make a calculation for the power loss and to make a decision for the electric rates. And loss factor(k-factor), which is a most important factor for calculation of the distribution power loss, has been used as a fixed value of 0.32 since the fiscal year 1973. Therefore, This study presents the statistical calculation methods of the loss factors classified by load types and seasons by using the practical data of 65 primary feeders which are selected by proper procedures. Based on the above the algorithms and methods, the optimal method of the distribution loss management classified by facilities such as primary feeders, distribution transformers and secondary feeders is presented. The simulation results show the effectiveness and usefulness of the proposed methods.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.101-114
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• 2012

In car insurance, the loss ratio is the ratio of total losses paid out in claims divided by the total earned premiums. In order to minimize the loss to the insurance company, estimating extreme quantiles of loss ratio distribution is necessary because the loss ratio has essential prot and loss information. Like other types of insurance related datasets, the distribution of the loss ratio has heavy-tailed distribution. The Peaks over Threshold(POT) and the Hill estimator are commonly used to estimate extreme quantiles for heavy-tailed distribution. This article compares and analyzes the performances of various kinds of parameter estimating methods by using a simulation and the real loss ratio of car insurance data. In addition, we estimate extreme quantiles using the Hill estimator. As a result, the simulation and the loss ratio data applications demonstrate that the POT method estimates quantiles more accurately than the Hill estimation method in most cases. Moreover, MLE, Zhang, NLS-2 methods show the best performances among the methods of the GPD parameters estimation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.3
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• pp.231-240
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• 2005

Recently, the needs and concerns for the power loss are increasing according to the energy conservation at the level of the national policies and power utilities's business strategies. Especially, the issue of the power loss is the main factor for the determining the electric pricing rates in the circumstances of the deregulation of electrical industry. However, because of the lacking of management for power loss load factors (LLF) it is difficult to make a calculation for the power loss and to make a decision for the electric rates. And loss factor (k-factor) in korea, which is a most important factor for calculation of the distribution power loss, has been used as a fixed value of 0.32 since the fiscal year 1973, There(ore, this study presents the statistical calculation methods of the loss factors classified by load types and seasons by using the practical data of 65 primary feeders which are selected by proper procedures. Based on the above the algorithms and methods, the optimal method of the distribution loss management classified by facilities such as primary feeders, distribution transformers and secondary feeders is presented. The simulation results show the effectiveness and usefulness of the proposed methods.