Heuristic algorithm for the problem of vessel routing optimisation for offshore wind farms

Dawid, Rafael; McMillan, David; Revie, Matthew

doi:10.1049/joe.2017.0511

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…Por ejemplo ya se están desarrollando máquinas inteligentes que gracias al despliegue de sensores de medición permiten comunicar el fallo en tiempo real (Exner, 2018). Es por lo anterior que modelos complejos deben adaptarse a entornos complejos y los simples a casos de fácil aplicación, dejando en claro que el presente y futuro de las predicciones en todo entorno empresarial deben migrar a modelos heurísticos métodos que puedan generar simplicidad y flexibilidad en los algoritmos, manejando una gran cantidad de restricciones (Dawid et al, 2017).…”

Section: Discusionunclassified

Predicción de Fallos Mecánicos en Equipos de Envoltura

Rodas

Castrillón

2019

Inf. tecnol.

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El objetivo de este trabajo es el pronóstico de fallos mecánicos en equipos de envoltura partiendo de datos históricos para mejorar la programación de intervenciones preventivas y disminuir el número de correctivas. Para esto se debe recolectar y clasificar datos históricos de tiempos entre fallos, realizar modelos de correlación y a partir de estos resultados definir cuál modelo de pronóstico es mejor, validando los datos mediante pruebas de hipótesis que reduzcan al mínimo la elección de este. Por último, aplicarlo, llegar a resultados y determinar tiempos aptos de programación para mantenimientos preventivos. La metodología empleada condujo al planteamiento de una ecuación que se adapta a las variables que afectan de manera directa el pronóstico del fallo. Se concluyó el impacto positivo de los paros programados en una organización, reduciendo el intervalo de tiempo de intervenciones preventivas y proyectando los tiempos de intervención para el siguiente año.

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Section: Discusionunclassified

Predicción de Fallos Mecánicos en Equipos de Envoltura

Rodas

Castrillón

2019

Inf. tecnol.

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“…Besides merging of the optimal maintenance scheduling approaches, the vessel routing problem of maintenance activities has also attracted the attention of many researchers and practitioners in recent years. [27][28][29][30][31][32][33] Dai et al 34 firstly introduced routing and scheduling problems for maintenance vessel at offshore wind farms and proposed a mathematical model to minimize the service cost and production loss cost due to delayed maintenance. The results showed the feasibility of proposed model and its applicability in determining the optimal assignments of turbines and vessel.…”

Section: Introductionmentioning

confidence: 99%

Optimal maintenance planning with special emphasis on deterioration process and vessel routing for offshore wind systems

Chou

Pham

Nguyen

et al. 2022

Energy & Environment

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Maintenance cost contributes a large portion in total life-cycle cost of offshore wind systems and improves the efficiency of maintenance activities that has emerged as an effective solution in enhancing cost-effectiveness of offshore wind energy. This study proposes a mathematical model to determine the optimal maintenance schedules, by highlighting the deterioration process of offshore wind systems and accounting the optimal vessel routing of maintenance activities, maintenance cost therefore could be shifted to an optimal level. Firstly, reliability of each component is precisely analyzed with respect to the effect of previous maintenance activities. Then, an optimal individual maintenance schedule and a grouping maintenance schedule in daily manner are established based on reliability analysis and opportunity cost consideration. Finally, an optimal maintenance schedule approach accounting vessel routing is apparently presented to optimize the transportation cost of maintenance activities. Numerous influential factors such as system reliability, weather condition, maintenance resource, maintenance duration, production loss cost, and vessel related issues are deliberately examined to enhance the robustness and efficiency of the proposed approach. The experimental results investigating four different scenarios demonstrate that by applying the proposed approach, number of maintenance activity is lowered down, maintenance duration and vessel travelling distance are also significantly reduced in the range of 43.86% - 52.77%, and 52.90% - 58.35%, respectively. Therefore, the economic benefit on maintenance cost could be achieved in an interval of 15.15% - 23.25% by selecting the optimal maintenance schedule.

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