A Reliability-Centered Approach to an Optimal Maintenance Strategy in Transmission Systems Using a Genetic Algorithm

Heo, Jae-Hyeok; Kim, Mun-Kyeom; Park, Geun-Pyo; Yoon, Yong Tae; Park, Jong Keun; Lee, Sang-Seung; Kim, Dong‐Hyeon

doi:10.1109/tpwrd.2011.2162752

Cited by 80 publications

(34 citation statements)

References 12 publications

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“…The main conclusion of this investigation was that maintenance at fixed intervals is the most frequently used approach, and strategies based on reliability-centered maintenance (RCM) are increasingly considered for application. This can be observed recently in some applications of RCM in transmission systems [5], distribution systems [6], and wind turbines [7], just to mention a few examples. Also, other studies have proposed probabilistic maintenance models based on state diagrams.…”

mentioning

confidence: 86%

A model for optimizing maintenance policy for power equipment

Melchor-Hernández

Rivas-Davalos

Maximov

et al. 2015

International Journal of Electrical Power & Energy Systems

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mentioning

confidence: 86%

A model for optimizing maintenance policy for power equipment

Melchor-Hernández

Rivas-Davalos

Maximov

et al. 2015

International Journal of Electrical Power & Energy Systems

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“…A multi-objective optimization problem can be transformed into a single objective optimization problem by converting an objective into a constraint [4], [5], [9] or by using a weighted sum method [10], [11]. The single objective optimization problem transformed is then solved by a single objective optimization algorithm.…”

Section: Nomenclaturementioning

confidence: 99%

Multi-objective optimization of generation maintenance scheduling

Chen

Zhan

Guo

2014

2014 IEEE PES General Meeting | Conference &Amp; Exposition

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For the generation maintenance scheduling (GMS) problem, a producer hopes to maximize its profit while ISO is to guarantee the system reliability. Thus, the GMS is a multi-objective optimization problem. In the GMS, there are large numbers of both continuous and integer variables, which complicates the resolving of the GMS. This paper proposes a new GMS model, which is suitable to be solved by the nondominated sorting genetic algorithm-II (NSGA-II). In the GMS model, the maintenance status of a generator is encoded into an integer variable and both the online status and the start-up status are represented by the generation variables. The GMS model on the IEEE reliability test system is solved by NSGA-II with a set of Pareto-optimal solutions obtained. The simulation results show that the GMS can be efficiently solved by NSGA-II. The simulation results also show that one producer's profit conflicts with another one's, and that the reliability objective is independent of the other objectives.

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“…The use of high voltage direct current (HVDC) transmission systems allows for power transfer over longer distances with lower losses and improved power system controllability, and such systems are expected to become an essential technology in integrating renewable energy sources as transmission system backups [2]. In particular, multi-terminal HVDC (MTDC) systems can simultaneously manage both active power and reactive power, and they provides a cost-effective solution for power system operation at each terminal independent of the direct current (DC) power transmission.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Scheduling Optimization Based on a Modified Non-Dominated Sorting Genetic Algorithm-II in Voltage Source Converter−Multi-Terminal High Voltage DC Grid-Connected Offshore Wind Farms with Battery Energy Storage Systems

Kim

2017

Energies

Self Cite

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Improving the performance of power systems has become a challenging task for system operators in an open access environment. This paper presents an optimization approach for solving the multi-objective scheduling problem using a modified non-dominated sorting genetic algorithm in a hybrid network of meshed alternating current (AC)/wind farm grids. This approach considers voltage and power control modes based on multi-terminal voltage source converter high-voltage direct current (MTDC) and battery energy storage systems (BESS). To enhance the hybrid network station performance, we implement an optimal process based on the battery energy storage system operational strategy for multi-objective scheduling over a 24 h demand profile. Furthermore, the proposed approach is formulated as a master problem and a set of sub-problems associated with the hybrid network station to improve the overall computational efficiency using Benders' decomposition. Based on the results of the simulations conducted on modified institute of electrical and electronics engineers (IEEE-14) bus and IEEE-118 bus test systems, we demonstrate and confirm the applicability, effectiveness and validity of the proposed approach.

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A Reliability-Centered Approach to an Optimal Maintenance Strategy in Transmission Systems Using a Genetic Algorithm

Cited by 80 publications

References 12 publications

A model for optimizing maintenance policy for power equipment

A model for optimizing maintenance policy for power equipment

Multi-objective optimization of generation maintenance scheduling

Multi-Objective Scheduling Optimization Based on a Modified Non-Dominated Sorting Genetic Algorithm-II in Voltage Source Converter−Multi-Terminal High Voltage DC Grid-Connected Offshore Wind Farms with Battery Energy Storage Systems

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