• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.1
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• pp.9-17
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• 1992

Proper resource allocation is also a very important topic in power system problems, especially in operation and planning. One such is optimal maintenance problem in operation and planning. Least cost and highest reliability should be the subjects to be pursued. A probabilistic operation simulation model developed recently by authors is applied to the proboem of optimal maintenance scheduling. Three different methods are compared, marginal maintenance cost, levelized risk and maintenance space. The method by the marginal maintenance costs shows the least cost, the highest reliability and the highest maintenance outage rates. This latter characteristics may considerably influence the results of genetation planning, because the usual maintenance outages obtained from the other methods have shown to be lower.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.338-346
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• 2016

In order for the optimal solution of generators’ annual maintenance scheduling to be applicable to the actual power system it is crucial to incorporate the constraints related to the equivalent operation hours (EOHs) in the optimization model. However, most of the existing researches on the optimal maintenance scheduling are based on the assumption that the maintenances are to be performed periodically regardless of the operation hours. It is mainly because the computation time to calculate EOHs increases exponentially as the number of generators becomes larger. In this paper an efficient algorithm based on demand grouping method is proposed to calculate the approximate EOHs in an acceptable computation time. The method to calculate the approximate EOHs is incorporated into the optimization model for the maintenance scheduling with consideration on the EOHs of generators. The proposed method is successfully applied to the actual Korean power system and shows significant improvement when compared to the result of the maintenance scheduling algorithm without consideration on EOHs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1382-1389
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• 2007

This paper presents a new approach for solving the problem of maintenance scheduling of generating units using a binary particle swarm optimization (BPSO). In this paper, we find the optimal solution of the maintenance scheduling of generating units within a specific time horizon using a binary particle swarm optimization algorithm, which is the discrete version of a conventional particle swarm optimization. It is shown that the BPSO method proposed in this paper is effective in obtaining feasible solutions in the maintenance scheduling of generating unit. IEEE reliability test systems(1996) including 32-generators are selected as a sample system for the application of the proposed algorithm. From the result, we can conclude that the BPSO can find the optimal solution of the maintenance scheduling of the generating unit with the desirable degree of accuracy and computation time, compared to other heuristic search algorithm such as genetic algorithms. It is also envisaged that BPSO can be easily implemented for similar optimizations and scheduling problems in power system problems to obtain better solutions and improve convergence performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.131-138
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• 1995

A new technique using integer programming based on fuzzy multi-criteria function is proposed for generator maintenance scheduling. Minimization maintenance delay cost and maximization reserve power are considered for fuzzy multi-criteria function. To obtain an optimal solution for generator maintenance scheduling under fuzzy environment, fuzzy multi-criteria integer programming is used. In the maintenance scheduling, a characteristic feature of the presented approach is that the crisp constraints with uncertainty can be taken into account by using fuzzy set theory and so more flexible solution can be obtained. The effectiveness of the proposed approach is demonstrated by the simulation results.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.234-240
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• 1999

This paper presents a new approach for large-scale generator maintenance scheduling optimizations. The generator preventive maintenance scheduling problems are typical discrete dynamic n-dimensional vector optimization ones with several inequality constraints. The considered objective function to be minimized a subset of{{{{ { R}^{n } }}}} space is the variance (i.g., second-order momentum) of operating reserve margin to levelize risk or reliability during a year. By its nature of the objective function, the optimal solution can only be obtained by enumerating all combinatorial states of each variable, a task which leads to computational explosion in real-world maintenance scheduling problems. This paper proposes a new priority search mechanism based on each generator's discrete sensitivity value which was analytically developed in this study. Unlike the conventional capacity-based priority search, it can prevent the local optimal trap to some extents since it changes dynamically the search tree in each iteration. The proposed method have been applied to two test systems (i.g., one is a sample system with 10 generators and the other is a real-world lage scale power system with 280 generators), and the results anre compared with those of the conventional capacith-based search method and combinatorial optimization method to show the efficiency and effectiveness of the algorithm.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.559-561
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• 1995

The cogeneration system has a strong merit in providing thermal and electrical energy simultaneously. Nowadays, cogeneration system is widely used in the point of efficient use of the energy resources And the installation of the system is expected to be greatly increased in each year. So, we need to develop an optimal operation planning for those systems. In this paper, we are used to result what studed at the my power system of room because it is in order to solve maintenance scheduling problem. Also we added a constraints to the proposed maintenance model for optimal maintenance rate. In the case study, we construct an multi-machine generated example system which operated in topping cycle, and calculate the yearly optimal production cost, marginal maintenance cost, and maintenance scheduling of the example system respectively.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.855-858
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• 1988

Two methods for probabilistic maintenance scheduling are developed and compared ; one with operation and supplied-shortage cost and other with risk level of LOLP. Based on the real economic power dispatch, quadratic optimal maintenance conditions are obtained and simple amtrix equations are suggested for solutions. Both methods are compared in a sample system of 26,000 [MW] peak and 32,000 [MW] generation capacity.

• IE interfaces
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• v.13 no.4
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• pp.680-687
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• 2000

The objectives of this research are to establish the operation scheduling and the preventive maintenance system in order to optimize the operation of mailing center. For the optimal operation scheduling of mailing process, the existing workflow of mailing process and that of required time are investigated prior to simulation modeling. The simulation experiments are conducted to increase the nextday delivery rate. The best alternative whose nextday delivery rate up to 100% is selected based the AHP(Analytic Hierarchy Process) method. The optimal work scheduling of all mailing centers are also presented. In addition, the CMMS(Computerized Maintenance Management System) for preventive maintenance is introduced for efficient operation of highly automated facilities of mailing center.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1359-1370
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• 2008

In the track geometry such as rails, sleepers, ballasts and fastener, track deterioration occurs by repetitive train weight and the high-speed railway takes a trend faster than normal. Track deterioration of over threshold value harms ride comfort and furthermore affect in trains safety seriously. An organic and systematic track maintenance system is very important because a trend of the track deterioration effects on track life-cycle and running safety. Also costs of the railway track permanent way and its maintenance are extremely large, forming a significant part of the total infrastructure expenditure. Therefor reasonable and efficient track maintenance has to be planed on a budget. It is required to carry out not only corrective maintenance but preventive maintenance for the track maintenance. In order to perform maintenance jobs in the boundary of the machines and resources given regarding the type and amount jobs, it is necessary to determine feasible or optimal scheduling considering the priority. In this study, the system organization and required functions for the development of track maintenance system supported track deterioration prediction and optimal scheduling are proposed.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.77-85
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• 1997

A new technique using integer programming based on fuzzy multi-criteria function is proposed for generator maintenance scheduling. Minimization of maintenance delay cost and maximization of supply reserve power are considered for fuzzy multi-criteria function To obtain an optimal solution for gen- ,:rator maintenance scheduling under fuzzy environment, fuzzy multi-criteria integer programming is )used. In the maintenance scheduling, a characteristic feature of the presented approach is that the crisp conaitraints with uncertainty can be taken into account by using fuzzy set theory and so more flexible solution Ian he obtained. The effectiveness of the proposed approach is demonstrated by the simulation results.