• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.4
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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.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.431-438
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• 2011

To ensure that equipment outages do not directly impact the reliability of the ISO-controlled grid, market participants request permission and receive approval for planned outages from the independent system operator (ISO) in competitive electricity markets. In the face of major generation outages, the ISO will make a critical decision as regards the scheduling of the essential maintenance for myriads of generating units over a fixed planning horizon in accordance with security and adequacy assessments. Mainly, we are concerned with a fundamental framework for ISO's maintenance coordination in order to determine precedence of conflicting outages. Simulated annealing, a powerful, general-purpose optimization methodology suitable for real combinatorial search problems, is used. Generally, the ISO will put forward its best effort to adjust individual generator maintenance schedules according to the time preferences of each power generator (GENCO) by taking advantage of several factors such as installed capacity and relative weightings assigned to the GENCOs. Thus, computer testing on a four-GENCO model is conducted to demonstrate the effectiveness of the proposed method and the applicability of the solution scheme to large-scale maintenance scheduling coordination problems.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.701-703
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• 1996

Maintenance scheduling plays an important role in evaluating the supply reliability of power systems. Since generating units 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 to bo done on all generating units, size of the units, elapsed time from last maintenance, and availability of maintenance crews. This paper proposes a new algorithm to decide the multi-year maintenance scheduling with considering the total cost. We adjust the maintenance scheduling to levelize the reliability over all period. The proposed algorithm is applied to a real size power system and the developed reliability results are obtained.

• 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 KIEE Conference
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• 2001.05a
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• pp.316-318
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• 2001

Occasionally, equipment in a distribution system fails due to damage from weather, vandalism, or other causes. In addition, it is recommended practice to have some way in which maintenance or replacement of every element in a system can be performed without causing lengthy interruption of electrical service to the customers it feeds. Thus, alternate sources, paths, and configurations of service must be planned so that both failures and maintenance do not affect customer service beyond a reasonable amount. In some cases, planning for alternate routes of service during equipment outages or emergencies -- will be the major aspect influencing selection of a feeder's capacity, type of route, or layout. We want to know the relationship between molt-dividing multi-connection and distribution reliability for contingency support considerations.