• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1507-1513
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• 2010

The $CO_2$ emission can be decreased due to freedom of generator maintenance scheduling(GMS). This paper proposes assessment of $CO_2$ emission considering generator maintenance scheduling(GMS) and evaluates effect of the GMS on $CO_2$ emission. And also, this paper assesses the $CO_2$ emission and the probabilistic production cost simulation of nuclear and thermal power generators considering operation of hydro and pumped generator. The minimum reliability criterion level satisfied production cost minimization function model is used in this paper. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system in Korea in 2010.

• Journal of Sensor Science and Technology
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• v.25 no.2
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• pp.91-102
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• 2016

The objective of this paper is to propose a heuristic algorithm to optimize the railway track maintenance scheduling, a NP-hard problem, by reflecting conditions of the actual field more quickly and easily. We develop the mechanism based on Binary Artificial Bee Colony (BABC) and Binary Harmony Search (BHS), and verify their performance through simulation experiments. Our proposed BABC and BHS mechanisms were applied to problems composed of 30, 60, 100, and 200 operations for railway track maintenance scheduling to carry out experiments and analysis. On comparing it with the results solved by CPLEX, it is found that the mechanism could present an optimal solution within limited time by user.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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• pp.1892-1902
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• 2007

This paper presents a new generating unit maintenance scheduling algorithm considering regional reserve margin and transfer capability. Existing researches focused on reliability of the overall power systems have some problems that adequate reliability criteria cannot be guaranteed in supply shortage regions. Therefore specific constraints which can treat regional reserve ratio have to be added to conventional approaches. The objective function considered in this paper is the variance (second-order momentum) of operating reserve margin to levelize reliability during a planning horizon. This paper focuses on significances of considering regional reliability criteria and an advanced hybrid optimization method based on PSO algorithm. The proposed method has been applied to IEEE reliability test system(1996) with 32-generators and a real-world large scale power system with 291 generators. The results are compared with those of the classical central maintenance scheduling approaches and conventional PSO algorithm to verify the effectiveness of the algorithm proposed in this paper.

• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.8-15
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• 2010

A new technique using a search method which is based on fuzzy multi-criteria function is proposed for GMS(generator maintenance scheduling) in order to consider multi-objective function. Not only minimization of probabilistic production cost but also maximization of system reliability level are considered for fuzzy multi-criteria function. To obtain an optimal solution for generator maintenance scheduling under fuzzy environment, fuzzy multi-criteria relaxation method(fuzzy search method) is used. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system model in Korea in 2010.

• International Journal of Reliability and Applications
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• v.4 no.1
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• pp.13-26
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• 2003

This paper presents a comparative study of a few commonly used maintenance scheduling methods for small utilities that consists solely of thermal generating plants. Two deterministic methods and a stochastic method are examined. The deterministic methods employ the leveling of reserve capacity criterion, of which one uses a heuristic rule to level the deterministic equivalent load obtained by using the product of the unit capacity and its corresponding forced outage rate. The stochastic method simulates the leveling of risk criterion by using the peak load carry capacity of available units. The results indicate that for the size and type of the maintenance scheduling problem described In this study, the stochastic method does not produce a schedule which is significantly better than the deterministic methods.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.9
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• pp.542-549
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• 2003

In this paper, a novel approach to generator maintenance scheduling strategy in competitive electricity markets based on non-cooperative dynamic game theory is presented. The main contribution of this study can be considered to develop a game-theoretic framework for analyzing strategic behaviors of generating companies (Gencos) from the standpoints of the generator maintenance-scheduling problem (GMP) game. To obtain the equilibrium solution for the GMP game, the GMP problem is formulated as a dynamic non-cooperative game with complete information. In the proposed game, the players correspond to the profit-maximizing individual Gencos, and the payoff of each player is defined as the profits from the energy market. The optimal maintenance schedule is defined by subgame perfect equilibrium of the game. Numerical results for two-Genco system by both proposed method and conventional one are used to demonstrate that 1) the proposed framework can be successfully applied in analyzing the strategic behaviors of each Genco in changed markets and 2) both methods show considerably different results in terms of market stability or system reliability. The result indicates that generator maintenance scheduling strategy is one of the crucial strategic decision-makings whereby Gencos can maximize their profits in a competitive market environment.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.7
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• pp.352-357
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• 2005

In competitive electricity markets, the System Operator (SO) coordinates the overall maintenance schedules when the collective maintenance schedule reported to 50 by Gencos not satisfy the specified operating criteria, such as system reliability or supply adequacy. This paper presented a method that divides generator maintenance scheduling of the 50 into a master-problem and a 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. And, the 50 should use the open information only, because the information such as cost function of a generator and bidding Price is highly crucial for the strategies of profit maximization.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.216-217
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• 2006

This paper presents development of program for generator maintenance scheduling. The maintenance scheduling of generating units is a dynamic discrete combinatorial optimization problem with constraints to determine the optimal maintenance periods of each generating units for a given planning periods. The developed program is designed so as to provide the maintenance schedule satisfying the operating reserve margin levelization and the procurement of proper reliability. In order to verify the effectiveness of the developed program, the numerical study has been performed with the practical data in 2005.