Condition-based maintenance effectiveness for series–parallel power generation system—A combined Markovian simulation model

Azadeh, A.; Asadzadeh, Seyed Mohammad; Salehi, Niloufar; Firoozi, M.

doi:10.1016/j.ress.2015.04.009

Cited by 67 publications

(22 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where ρ is the best observation given by the cardinality of the observer sets as presented in [39]. The last step of AQPSO is to verify the termination criterion using the total number of iterations It, and convergence tolerance value e. The process finishes if one of the conditions given in (25) is satisfied…”

Section: Optimisation Technique: Aqpsomentioning

confidence: 99%

“…The main contributions of this paper are: (i) a more realistic and accurate ageing reliability model, which considers the obsolescence state of the power generators; (ii) a novel AQPSObased algorithm for optimal long-term PM planning of power generators; (iii) a novel mathematical formulation that describes the relationship between generator's lifetime, virtual age, degradation and transition rates; and (iv) an advanced SM algorithm for optimal power system generation adequacy assessment. [19] not applied no two one discrete integer cuckoo search Basçiftci et al [20] λ: not specified no not specified one stochastic mixed-integer programming and sample average approximation μ: not specified Jo et al [21] λ: not specified no not specified one mixed-integer polynomial programming μ: not specified Eygelaar et al [22] λ: constant no two one reliability theory μ: constant Hosseini et al [23] λ: constant no not specified one greedy heuristic μ: constant local search algorithm Rodríguez et al [24] not applied no not applied one mixed-integer programming Azadeh et al [25] λ: Weibull variation yes two one Markovian discrete event and Monte Carlo μ: constant Yildirim et al [26] λ: Weibull yes two one mixed-integer μ: Weibull optimisation and Monte Carlo Mo and Sansavini [27] λ: Weibull variation yes two twenty linear programming and Monte Carlo μ: constant Hoseyni et al [28] λ: Weibull variation yes three thirty condition-based probabilistic safety assessment μ: not specified Selvi et al [29] λ: Weibull variation yes two ten genetic algorithm and Monte Carlo μ: not specified proposed approach in this paper λ: bathtub curve yes three fifty AQPSO and sequential Monte Carlo μ: half-arch shape IET Gener. Transm.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reliability‐based smart‐maintenance model for power system generators

Alvarez-Alvarado

Jayaweera

2020

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

Section: Optimisation Technique: Aqpsomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reliability‐based smart‐maintenance model for power system generators

Alvarez-Alvarado

Jayaweera

2020

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

“…In order to improve the reliability and efficiency of equipment, it is very important to apply the condition-based maintenance (CBM). A good maintenance activity has a close relationship with security and diminishes costs, making this issue even more attractive to researchers [8].…”

Section: Maintenance Systems and Their Application In Thermoelectric mentioning

confidence: 99%

Maintenance Management with Application of Computational Intelligence Generating a Decision Support System for the Load Dispatch in Power Plants

Fonseca

Sanches²,

Leite³

et al. 2020

Maintenance Management

View full text Add to dashboard Cite

The development of a computational tool to support the decision of load dispatch according to the operational conditions of motors and generators of power plants is proposed, which are classified in relation to the probabilities of faults by a fuzzy system developed in this text, from indicators obtained from the analysis of lubricating oil, vibration analysis, and thermography of power generation equipment. The basis for the study is based on the principle of operation and operational conditions of the equipment to be dispatched for generation in a power plant, in addition to its particularities as specific consumption and the polluting emission for each equipment. In this way, this work aims not only to provide the tools to monitor these equipment but also, based on the management reports of vibration, temperature, and oil analysis, take corrective actions to maintain the necessary reliability and achieve the quality of the service through a preclearance procedure that takes into account the operating conditions of the equipment, obtaining performance indicators of the plan.

show abstract

“…When this approach combines with PM method, the maintenance will be highly effective and efficient. The reason is that the priority of maintenance schedule performs based on the aging process, resources, and personal experiences [11].…”

Section: Condition-based Maintenancementioning

confidence: 99%

Evaluation of Various Maintenance Strategies for Reliability Assessment of Thermal Power Plants

Zarei¹,

Ghaedi-Kajuei²

2017

IJEECS

View full text Add to dashboard Cite

In recent years, the world has had a phenomenal economic growth due to the acquisition of innovative technologies and globalization. In the meantime, electrical power plants are regarded as a fundamental element in industrial and production, and any deficiency in supplying may lead to significant financial detriment. Regard to the deep dependency of modern lifestyle to electricity, providing a high-quality and reliable electricity for consumers has taken on paramount importance. The reliability of a power plant depends on the configuration of elements and the reliability of each utility. The reliability, continuous service, flexibility in operation, simplicity, maintenance, development availability, meeting required standards etc. constitute the decisive factors for selection of a utility. Hence, each component of a power system must maintain the adequate level of reliability. In general, the maintenance approaches are classified into two parts: 1- The maintenance which must be carried out within determined and specified time intervals; 2- The maintenance which must be performed when required or in emergencies. To evaluate the maintenance and its effect on reliability, two types of deterministic and probabilistic approaches are presented. In this paper, a comprehensive description of both models is issued, and a detailed comparison is drawn. The results obviously show that the probabilistic models have considerable priority to deterministic models regard to their abilities for maximization of reliability or minimization of costs.

show abstract

Condition-based maintenance effectiveness for series–parallel power generation system—A combined Markovian simulation model

Cited by 67 publications

References 38 publications

Reliability‐based smart‐maintenance model for power system generators

Reliability‐based smart‐maintenance model for power system generators

Maintenance Management with Application of Computational Intelligence Generating a Decision Support System for the Load Dispatch in Power Plants

Evaluation of Various Maintenance Strategies for Reliability Assessment of Thermal Power Plants

Contact Info

Product

Resources

About