Promoting the optimal maintenance schedule of generating facilities in open systems

Tabari, N.M.; Ranjbar, A.M.; Sadati, N.

doi:10.1109/icpst.2002.1053621

Cited by 7 publications

(5 citation statements)

References 7 publications

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“…[44] proposed Mixed Integer Programming (MIP), and [45] proposed Mixed Integer Linear Programming (MILP). [46] proposed Dynamic Programming (DP), [47] proposed Dynamic Programming and Successive Approximations (DPSA) method. [48] proposed Branch and Bound (B&B) method.…”

Section: Related Workmentioning

confidence: 99%

Single Objective Optimization Methods in Electrical Power Systems: A Review

Al-kharaz¹,

A.Wahhab²,

Ibrahim³

et al. 2023

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Although the scheduling of maintenance tasks for generators is not a new issue, it has recently attracted new attention due to the significant rise in demand for expanding power system size in modern power systems. Generator Maintenance Scheduling (GMS) is a nonlinear optimization problem, highly dimensional and constrained, and determines when power-producing units must undertake well-planned preventative maintenance. The objective function includes binary variables to indicate whether a generator is undergoing maintenance at a given time and is subject to several restrictions described in this paper. However, the biggest concern of GMS is to produce a precise timetable for preventive maintenance of generating units with low cost and high reliability. Despite that, regrettably, a large volume of research works has accomplished solutions towards a model of GMS with the consideration of either maximizing system reliability or minimizing operation costs as an objective of their research work. This is called Single-Objective Problem (SOP), which involves one objective function that needs to be optimized. SOP is solved by Single-Objective Optimization Method (SOOM). The primary purpose of the research is to present a review of SOOM methods used in solving GMS problems.

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Section: Related Workmentioning

confidence: 99%

Single Objective Optimization Methods in Electrical Power Systems: A Review

Al-kharaz¹,

A.Wahhab²,

Ibrahim³

et al. 2023

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“…The optimal periods of maintenances are determined based on seasonal, operative, and reliability constraints. Similarly, [4] uses a dynamic programming approach that maximizes the profits of the GENCOs considering forecasted electricity prices and constraints related to the operation and reliability of the system and the availability of maintenance resources. A new formulation for solving the GMS problem is proposed in [5], considering electricity prices and demand forecasts, generation capacity, and maintenance resources constraints.…”

Section: A Literature Reviewmentioning

confidence: 99%

Hybrid NSGA III/dual simplex approach to generation and transmission maintenance scheduling

Martin

Yang

Liu

2022

International Journal of Electrical Power & Energy Systems

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“…The goal of maintenance scheduling for each GENCO is to maximize its own profits. Different unit owners make their own units maintenance plan independently and do not consider other GENCOs' maintenance plans [31]. But few existing mathematical models associated with maintenance scheduling for generators units take into account this new change.…”

Section: B Maintenance Schedulingmentioning

confidence: 99%

“…Kim et al [34], [35] and Torre et al [36] proposed to model the GENCOs in competitive electricity markets using Nash equilibrium theory. References [31] and [37] discussed the maintenance scheduling of generating units in the deregulated and open power system.…”

Section: B Maintenance Schedulingmentioning

confidence: 99%

Advanced Maintenance Strategy for Power Plants &#8212;Introducing Intelligent Maintenance System

Chu

Mao

2006

2006 6th World Congress on Intelligent Control and Automation

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Maintenance activities play a key role in keeping performance, reliability and safety levels of generating facilities in power plants. Scheduled maintenance and imperfect conditionbased maintenance often augmented by additional breakdown maintenance are the usual maintenance strategies employed by generating companies now in China. Recently, a new maintenance philosophy called as intelligent maintenance system was proposed. This paper describes the new advantages and characteristics of intelligent maintenance system, and shows the possible challenges to develop the intelligent maintenance system for generating equipment. The technologies of fault prognosis, maintenance scheduling and sensors etc. as the key elements of intelligent maintenance system in power plants are depicted in detail, and their future research directions are addressed respectively. Index Terms-Intelligent maintenance system. Power plants. Fault prognosis. Maintenance modeling and optimization. Sensors.

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Promoting the optimal maintenance schedule of generating facilities in open systems

Cited by 7 publications

References 7 publications

Single Objective Optimization Methods in Electrical Power Systems: A Review

Single Objective Optimization Methods in Electrical Power Systems: A Review

Hybrid NSGA III/dual simplex approach to generation and transmission maintenance scheduling

Advanced Maintenance Strategy for Power Plants &#8212;Introducing Intelligent Maintenance System

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Promoting the optimal maintenance schedule of generating facilities in open systems

Cited by 7 publications

References 7 publications

Single Objective Optimization Methods in Electrical Power Systems: A Review

Single Objective Optimization Methods in Electrical Power Systems: A Review

Hybrid NSGA III/dual simplex approach to generation and transmission maintenance scheduling

Advanced Maintenance Strategy for Power Plants &amp;#8212;Introducing Intelligent Maintenance System

Contact Info

Product

Resources

About

Advanced Maintenance Strategy for Power Plants —Introducing Intelligent Maintenance System