• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.408-409
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• 2006

In this paper, we surveyed researches on the generation maintenance scheduling in competitive electricity markets. Maintenance scheduling can be one of the strategies submitted by market participants in electricity market. Many researches on the maintenance scheduling were preceded with or without transmission system. They have their own specific algorithm for ISO to operate, and control the maintenance schedules. This paper is focused on the survey on the generator and transmission system maintenance scheduling in competitive electricity markets.

• KIEE International Transactions on Power Engineering
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• 제5A권4호
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• pp.331-338
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• 2005

In this paper, an improved maintenance scheduling approach suitable for the competitive environment is proposed by taking account of profits and costs of generation companies and the formulated combinatorial optimization problem is solved by using Reactive Tabu search (RTS). In competitive power markets, electricity prices are determined by the balance between demand and supply through electric power exchanges or by bilateral contracts. Therefore, in decision makings, it is essential for system operation planners and market participants to take the volatility of electricity price into consideration. In the proposed maintenance scheduling approach, firstly, electricity prices over the targeted period are forecasted based on Artificial Neural Network (ANN) and also a newly proposed aggregated bidding curve. Secondary, the maintenance scheduling is formulated as a combinatorial optimization problem with a novel objective function by which the most profitable maintenance schedule would be attained. As an objective function, Opportunity Loss by Maintenance (OLM) is adopted to maximize the profit of generation companies (GENCOS). Thirdly, the combinatorial optimization maintenance scheduling problem is solved by using Reactive Tabu Search in the light of the objective functions and forecasted electricity prices. Finally, the proposed maintenance scheduling is applied to a practical test power system to verify the advantages and practicability of the proposed method.

• 대한전기학회논문지:전력기술부문A
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• 제48권5호
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• pp.545-552
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• 1999

The Maintenance scheduling is one of the mid-term scheduling problems systems. There have been many methods for this problem, but there is no effective way to treat all the generators simultaneously. In this paper, we apply a genetic algorithm(GA) to the maintenance scheduling problem. We proposed new crossover operators(BOX type crossover) to improve searching ability of GA. Satisfactory results are obtained by GA with the proposed corssover operators.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1995년도 추계학술대회 학술발표 논문집
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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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.

• 대한산업공학회지
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• 제34권3호
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• pp.318-327
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• 2008

This paper considers a single-machine scheduling problem with availability constraints. In many realistic situations, machines may not be always available due to various reasons such as maintenance, breakdown and repair. However, most literature on scheduling assume that the machines are available at all times. This paper deals with a single-machine scheduling problem with periodic maintenance. If the maintenance decision is made jointly with the job scheduling, the system will be more effective. The objective is to minimize the total completion time of jobs. This problem is proved to be NP-hard in the strong sense. The proposed breaking heuristic(BH) algorithm rule is established by some theorems and conditions. Our computational results show that the BH algorithm is much more efficient than existing heuristic.

• 전기학회논문지
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• 제56권8호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.829-831
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• 1996

This paper is concerning on a study on the object-oriented programming and its application to maintenance scheduling. The concept of object-oriented programming enables us to modify and reuse software with much ease. By introducing object-oriented programming to maintenance scheduling, we can develop a hierarchical and reusable software in maintenance scheduling. The maintenance scheduling problem becoming more and more large and complex can be dealt with the concept of object-oriented technique and we hope this concept will give a reasonable solution. And evolutionary computation will be developed as a optimization technique.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.826-828
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• 1996

Genetic Algorithm(GA) is a searching or optimizing algorithm based on natural evolution principle. GA has demonstrated considerable success in providing good solutions to many nonlinear, multi-dimensional optimization problems. The preventative maintenance scheduling is a kind of dynamic optimization problem with constraints. This paper applies GA to the preventative maintenance scheduling problem. In the case study, we can get the preventative maintenance scheduling of 3-generators during 8 weeks using GA. It is shown that GA can be available to the preventative maintenance scheduling problem.

• 에너지공학
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• 제7권1호
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• pp.89-95
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• 1998

발전기의 보수계획은 전력계통의 공급신뢰도를 평가하는데 중요한 영향을 미치는 변수이다. 발전기는 반드시 검사와 보수를 해야 하기 때문에, 운전계획을 세울 때 한해의 발전기 정지계획을 고려하여 정해야 한다. 이러한 보수계획을 수립할 대에는 계절적 부하수요특징, 보수용량, 발전기 용량, 지난번 보수로부터의 경과시간 등의 여러 가지 요인들을 고려해야 한다. 본 논문에서는 발전기 보수계획 프로그램중 실용적인 방법으로 알려져 있는 LOLP(Loss of Load Probability) 평활화법을 이용하여 각 연도별 공급신뢰도를 최대로 하여 고려대상 기간 전체의 공급신뢰도를 향상시키는 보수계획 수립 알고리즘을 제안한다. 즉, 전력계통의 더 좋은 신뢰도를 얻기 위하여 전체 기간에 대한 신뢰도가 평활화되도록 보수시기를 변경하였다. 제안한 알고리즘을 실계통에 적용하여 그 유용성을 검증하였다.