• 한국경영과학회지
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• 제16권2호
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• pp.164-176
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• 1991

This paper considers the model of a k-out-of-n :G system with non-identical components which are subject to both forced and planned outages. For the forced outages, it assumes that there are the independent and common-cause outage events causing component failures. Then, the objective is to derive the upper and lower bounds on the mean operating time between system failures in the ample-server model. In addtion, the mean system failure times are also considered.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 A
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• pp.195-198
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• 2004

In recent, the Importance and necessity of some studies on reliability evaluation of grid comes from the recent black-out accidents occurred in the world. The quantity evaluation of transmission system reliability is very important under competitive electricity environment. Accurate probabilistic reliability evaluation depends on assessment of forced outage rate of elements, generators, transmission lines. This paper describes basic theory of relationship between outage rates and reliability evaluation for assessing FOR(forced outage rate) of elements of power system. In case study, FORs assessed and supplied from Canada Electricity Association is introduced and FORs assessed from using actual historical data from 1997 to 2002 for transmission lines of KEPCO system.

• 에너지공학
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• 제11권1호
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• pp.47-58
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• 2002

본 논문은 민자발전소의 회피 발전비용을 계산하는 새로운 방법을 제안하였다. 제안된 방법은 기존의 부하감소법과 달리 민자발전소의 고장정지율과 경제적 투입순서를 정확히 고려할 수가 있다. 그러므로 더욱 정확한 회피 발전비용을 계산할 수가 있다. 또한 확률적 시뮬레이션을 수행하여 계산하므로 민자발전소의 비용에 대한 영향도 정확히 고려할 수가 있다. 부가적으로 한 개 이상의 민자발전소가 참여하였을 때에 회피 발전비용을 할당하는 방법도 제안하였다. 다양한 사례연구를 통해 제안한 방법의 결과를 분석하였다.

• 대한전기학회논문지:전력기술부문A
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• 제54권8호
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• pp.418-428
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• 2005

In this paper, a new probabilistic generation modeling method which can address the characteristics of changed electricity industry is proposed. The major contribution of this paper can be captured in the development of a probabilistic generation modeling considering generator maintenance outage and in the classification of market demand into multiple demand clusters for the applications to electricity markets. Conventional forced outage rates of generators are conceptually combined with maintenance outage of generators and, consequently, effective outage rates of generators are newly defined in order to properly address the probabilistic characteristic of generation in electricity markets. Then, original market demands are classified into several distinct demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the original demand. We have found that generators have different effective outage rates values at each classified demand cluster, depending on the market situation. From this, therefore, it can be seen that electricity markets can also be classified into several groups which show similar patterns and that the fundamental characteristics of power systems can be more efficiently analyzed in electricity markets perspectives, for this classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
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• pp.804-806
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• 2005

In this paper, a new probabilistic generation modeling method which can address the characteristics of changed electricity industry is proposed. The major contribution of this paper can be captured in the development of a probabilistic generation modeling considering generator maintenance outage and in the classification of market demand into multiple demand clusters for the applications to electricity markets. Conventional forced outage rates of generators are conceptually combined with maintenance outage of generators and, consequently, effective outage rates of generators are new iy defined in order to properly address the probabilistic characteristic of generation in electricity markets. Then, original market demands are classified into several distinct demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the original demand. We have found that generators have different effective outage rates values at each classified demand cluster, depending on the market situation. From this, therefore, it can be seen that electricity markets can also be classified into several groups which show similar patterns and that the fundamental characteristics of power systems can be more efficiently analyzed in electricity markets perspectives, for this classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
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• pp.235-237
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• 2005

This paper presents a method of incorporating weather effects in KEPCO systems reliability evaluation. The effects of adverse weather on composite power system FOR(Forced Outage Rate) increase considerably as the proportion of outages in adverse weather increases. It is therefore important to establish suitable and practical procedures for collecting adverse weather data which can be utilized in realistic KEPCO systems reliability assessment. The modeling procedure proposed in this paper also provides a realistic FOR in KEPCO systems using real historical data.

• KIEE International Transactions on Power Engineering
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• 제4A권2호
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• pp.91-99
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• 2004

This paper illustrates a tie line constrained equivalent assisting generator (TEA G) model considering forced outage rates of transmission systems for reliability evaluation of interconnected power systems. Interconnections between power systems can provide improved levels of reliability. It is expected that the TEAG model developed in this paper will prove useful in the solution to problems related to the effect of transmission system uncertainties in the reliability evaluation of interconnected power systems. The characteristics and concept of this TEAG considering transmission systems are described in detail by sample studies on a simple test system.

• International Journal of Reliability and Applications
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• 제4권1호
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• pp.13-26
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• 2003

This paper presents a comparative study of a few commonly used maintenance scheduling methods for small utilities that consists solely of thermal generating plants. Two deterministic methods and a stochastic method are examined. The deterministic methods employ the leveling of reserve capacity criterion, of which one uses a heuristic rule to level the deterministic equivalent load obtained by using the product of the unit capacity and its corresponding forced outage rate. The stochastic method simulates the leveling of risk criterion by using the peak load carry capacity of available units. The results indicate that for the size and type of the maintenance scheduling problem described In this study, the stochastic method does not produce a schedule which is significantly better than the deterministic methods.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2001년도 추계학술발표회요약집
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• pp.183.1-183
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• 2001

• 대한전기학회논문지:전력기술부문A
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• 제55권4호
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• pp.172-178
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• 2006

In this paper, an advanced demand clustering algorithm which can explore the planned maintenance outage of generators in changed electricity industry is proposed. The major contribution of this paper can be captured in the development of the long-term estimates for the generation availability considering planned maintenance outage. Two conflicting viewpoints, one of which is reliability-focused and the other is economy-focused, are incorporated in the development of estimates of maintenance outage based on the advanced demand clustering algorithm. Based on the advanced clustering algorithm, in each demand cluster, conventional effective outage of generators which conceptually capture maintenance and forced outage of generators, are newly defined in order to properly address the characteristic of the planned maintenance outage in changed electricity markets. First, initial market demand is classified into multiple demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the initial demand. Then, based on the advanced demand clustering algorithm, the planned maintenance outages and corresponding effective outages of generators are reevaluated. Finally, the conventional demand clusters are newly classified in order to reflect the improved effective outages of generation markets. We have found that the revision of the demand clusters can change the number of the initial demand clusters, which cannot be captured in the conventional demand clustering process. Therefore, it can be seen that electricity market situations, which can also be classified into several groups which show similar patterns, can be more accurately clustered. From this the fundamental characteristics of power systems can be more efficiently analyzed, for this advanced classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.