• Journal of Energy Engineering
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• v.7 no.1
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• pp.89-95
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• 1998

Maintenance scheduling of generators plays an important role in evaluating supply reliability of power systems. Since generators must be maintained and inspected, the generation planner must schedule planned outages during the year. Several factors entering into this scheduling analysis include: seasonal load-demand profile, amount of maintenance, size of the units, elapsed time from last maintenance, and availability of maintenance crew. This paper proposes a new maintenance scheduling algorithm for the alternatives of long-term generation expansion planning by using LOLP levelization method which is known as an effective method for the generator's maintenance scheduling. To get the best supply reliability of power systems, we change the maintenance period to levelize the reliability over all period. The proposed algorithm is applied to a real size power system and the better reliability results are obtained.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1066-1071
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• 2007

This case study refers to turbine-generator with retrofitted turbine rotor. Vibration problem occurring after the retrofit was mainly due to high vibration from exciter side. However, repeated test run and operation during scheduled maintenance caused high vibration from generator bearing, and post-overhaul test run before turbine vibration correction caused oil whip on the bearing. This case study shows how to analyze vibration condition of high turbine generator vibration detected during the post-overhaul test run and vibration condition of offline and online data to reflect it on establishing maintenance schedule and overhaul correction procedure. Vibration data could be acquired during steady load operation or even with varying speed and load. Each data is important for machinery condition evaluation. This case study shows that the vibration data during extreme condition is the key factor in analysis, which helps to find the machinery problem.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.2
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• pp.238-246
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• 2008

This case study refers to turbine-generator with retrofitted turbine rotor. Vibration problem occurring after the retrofit was mainly due to high vibration from exciter side. However, repeated test run and operation during scheduled maintenance caused high vibration from generator bearing, and post-overhaul test run before turbine vibration correction caused oil whip on the bearing. This case study shows how to analyze vibration condition of high turbine generator vibration detected during the post-overhaul test run and vibration condition of offline and online data to reflect it on establishing maintenance schedule and overhaul correction procedure. Vibration data could be acquired during steady load operation or even with varying speed and load. Each data is important for machinery condition evaluation. This case study shows that the vibration data during extreme condition is the key factor in analysis, which helps to find the machinery problem.

• Proceedings of the KSR Conference
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• 1999.11a
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• pp.46-53
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• 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
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• 1991.11a
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• pp.47-50
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• 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.