• Proceedings of the KIEE Conference
• /
• 1999.07c
• /
• pp.1270-1272
• /
• 1999

The generator cost function is one of the basic data for the generation scheduling. Generally the cost functions are obtained form design calculations or from heat rate tests. The real operating condition may be different from the condition of design or the tests. Some of the conditions may not be tested during the periodical maintenance. In order to improve the calculation of the generator cost function, this paper presents a new calculation method of the generator cost functions using the utilization factors of generators and the mixed fuel burning ratio of the generators.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.54 no.8
• /
• pp.418-428
• /
• 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.

• Proceedings of the KIEE Conference
• /
• 2004.11b
• /
• pp.104-106
• /
• 2004

In competitive electricity markets, the System Operator (SO) coordinates the overall maintenance schedules whenever the collective maintenance schedule reported to SO by Gencos in the pool does not satisfy the specified operating criteria, such as system reliability or supply adequacy. In this paper, we divide maintenance schedule problem into master-problem and sub-problem. Master-problem is schedule coordination and sub-problem is DC-optimal power flow. If sub-problem is infeasible, we use the algorithm of modifying operating criteria of master-problem.

• Proceedings of the KIEE Conference
• /
• 2015.07a
• /
• pp.471-472
• /
• 2015

This paper proposes a generator maintenance scheduling (GMS) problem with due consideration of various objective functions. The objectives include leveling the reserve rate, maximizing reliability and minimizing production cost. The practicality and effectiveness of the proposed approach are demonstrated in the simulation for a real-size power system model in South Korea.

• Proceedings of the KIEE Conference
• /
• 1991.11a
• /
• pp.47-50
• /
• 1991

This paper discusses a knowledge-based system being developed by KAIST and KEPCO to assist planning the annual maintenance schedule of power units. To meet users' requirements, we have designed the system with several features: man-machine interaction, catalog system, user-friendliness, the hybrid-system of math-model and knowledge-base. In this paper, we introduce the outline of our system.

• Proceedings of the KSR Conference
• /
• 1999.11a
• /
• pp.46-53
• /
• 1999

As of July 1999, i,185 lomocotives(excluding metropolitan area electric locomotives) are in Korean National Railroad(KNR). With this limited number of resources assigning locomotives to each trains of timetable is very important in the entire railway management point of view because schedule can be regarded as goods in transportation industry. On a simple rail network, it is rather easier to assign proper locomotives to trains with the experience of operating experts and get optimal assignment solution. However, as the network is getting bigger and complicated, the number of trains and corresponding locomotives will be dramatically increased to rover all the demands required to service all of the trains in timetable. There will be also numerous operational constraints to be considered. Assigning proper locomotives to trains and building optimal cyclic rotations of locomotive routings will result in increasing efficiency of schedule and giving a guarantee of more profit. The purpose of this study is two fold: (1) we consider a planning-level locomotive scheduling problem with the objective of minimizing the wasting cost under various practical constraints and (2) development of implementation prototype program of its assigning result. Not like other countries, i.e. Canada, Sweden, Korean railroad operates on n daily schedule basis. The objective is to find optimal assignment of locomotives of different types to each trains, which minimize the wasting cost. This problem is defined on a planning stage and therefore, does not consider operational constraints such as maintenance and emergency cases. Due to the large scale of the problem size and complexity, we approach with heuristic methods and column generation to find optimal solution. The locomotive scheduling prototype consists of several modules including database, optimization engine and diagram generator. The optimization engine solves MIP model and provides an optimal locomotive schedule using specified optimization algorithms. A cyclic locomotive route diagram can be generated using this optimal schedule through the diagram generator.

• Proceedings of the KIEE Conference
• /
• 2005.07a
• /
• pp.804-806
• /
• 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.

• Proceedings of the KSME Conference
• /
• 2007.05b
• /
• pp.3236-3240
• /
• 2007

This paper describes the results of steam turbine performance tests. The objectives of performance test is to exactly evaluate the degradation(decrease in performance) of the coal-fired steam turbine generator in order to provide plant information to help performance engineers identify problems, improve performance, and make economic decisions about scheduling maintenance and optimizing operation. To achieve these goals, the periodic thermal performance tests have been carried out since the initial operation period, 1997. We made the calculation program and guidelines for the tests and developed the performance index of the turbine cycle on the basis of the ASME PTC. By comparing the performance changes throughout the whole operation period, we confirmed the performance reliabilities of the turbine and its conditions.

• Proceedings of the KIEE Conference
• /
• 2015.07a
• /
• pp.459-460
• /
• 2015

현재의 예방정비계획 운영 방법은 KPX에서 발전 사업자들로부터 희망하는 자신들의 발전기 예방정비계획 일정을 받아서 공급예비력 기준을 만족하면 승인을 해주는 방법으로 진행되고 있다. 이는 경제적인 부분을 예방정비계획 수립에 반영하지 못하고 계통의 신뢰도 측면만을 판단하는 것으로 생각할 수 있다. 따라서 발전비용을 최소화하는 예방정비계획 최적화 모델을 적용하여 예방정비계획 수립 시 경제성을 반영하려 한다. 이를 통해 연발전비용을 낮추면서 연평균 SMP 또한 낮춤으로서 한전과 발전사업자 모두에게 이익을 가져다 줄 수 있는 것이다. 따라서 본 연구에서는 비용 최소화를 목적함수로 하는 tool을 적용한 예방정비계획 최적 값과 기존의 예방정비계획을 공급예비율, 계통한계가격(System Marginal Price, SMP), 발전비용 세 가지로 나눠 비교하고 신뢰도와 경제성을 고려한 최적 예방정비계획을 수립하였다.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.364-365
• /
• 2011

This study develops a new system for generation system simulation and operational planning (namely, KPWR-X) including GMS(Generator Maintenance Scheduling), UC(Unit Commitment), and LF(Load Forecasting) for new power system environment in recent. The KPWR-X provides operator and planner to help the generation system more safely and economically. GUI developed in this study makes operator feel in convenient to control whole power system. In future, it is expected that generation company, ISO, and fuel procurement, etc. may use an instructional tool developer's suggestion for application. It will be also applicable to establish the operational strategies for generation control, fuel procurement and power system risk management.