Routing and Scheduling of Maintenance Fleet for Offshore Wind Farms

Dai, Lijuan; Stålhane, Magnus; Utne, Ingrid Bouwer

doi:10.1260/0309-524x.39.1.15

Cited by 70 publications

(54 citation statements)

References 9 publications

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“…The maintenance routing and scheduling problem for an offshore wind farm was introduced by Dai, Stålhane, and Utne (2015) . The problem consists of finding one route and schedule for each vessel to perform maintenance on a set of wind turbines over a planning period of several days.…”

Section: Maintenance Routing and Scheduling For Offshore Wind Farmsmentioning

confidence: 99%

“…The model also considers the capacity of vessels in transporting technicians and spare parts. Stålhane, Hvattum, and Skaar (2015) study the problem proposed by Dai et al (2015) , but consider only one period. They propose an arc-flow model of the problem, and reformulate it as a path-flow model by using DantzigWolfe decomposition ( Dantzig and Wolfe, 1960 ).…”

Section: Maintenance Routing and Scheduling For Offshore Wind Farmsmentioning

confidence: 99%

See 1 more Smart Citation

Optimisation of maintenance routing and scheduling for offshore wind farms

Irawan

Ouelhadj

Jones

et al. 2017

European Journal of Operational Research

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167

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a b s t r a c tAn optimisation model and a solution method for maintenance routing and scheduling at offshore wind farms are proposed. The model finds the optimal schedule for maintaining the turbines and the optimal routes for the crew transfer vessels to service the turbines along with the number of technicians required for each vessel. The model takes into account multiple vessels, multiple periods (days), multiple Operation & Maintenance (O&M) bases, and multiple wind farms. We develop an algorithm based on the Dantzig-Wolfe decomposition method, where a mixed integer linear program is solved for each subset of turbines to generate all feasible routes and maintenance schedules for the vessels for each period. The routes have to consider several constraints such as weather conditions, the availability of vessels, and the number of technicians available at the O&M base. An integer linear program model is then proposed to find the optimal route configuration along with the maintenance schedules that minimise maintenance costs, including travel, technician and penalty costs. The computational experiments show that the proposed optimisation model and solution method find optimal solutions to the problem in reasonable computing times.

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Section: Maintenance Routing and Scheduling For Offshore Wind Farmsmentioning

confidence: 99%

Section: Maintenance Routing and Scheduling For Offshore Wind Farmsmentioning

confidence: 99%

Optimisation of maintenance routing and scheduling for offshore wind farms

Irawan

Ouelhadj

Jones

et al. 2017

European Journal of Operational Research

Self Cite

167

View full text Add to dashboard Cite

show abstract

“…Various sources and expert opinions have been consulted to obtain realistic parameters for the instances, mainly based on a reference case created for verification of O&M simulation models for offshore wind farms by Dinwoodie et al [35]. Additional sources have been used for data on the wave height limits of the different vessels [36,37], transportation costs [23] and daily cost rates [38], maintenance task categories and failure rates [39], and weather conditions [40]. Details on the data used to create the test instances are provided in the supplemental material.…”

Section: Computational Studymentioning

confidence: 99%

“…Dai et al [23] present an optimization model for the routing and scheduling problem of a given vessel fleet for O&M in an offshore wind farm. The model minimizes costs related to travelling to the respective turbines and delaying tasks.…”

Section: Introductionmentioning

confidence: 99%

Scheduling of Maintenance Tasks and Routing of a Joint Vessel Fleet for Multiple Offshore Wind Farms

Raknes

Ødeskaug

Stålhane

et al. 2017

JMSE

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Abstract:Maintenance costs related to offshore wind farms are severely limiting their potential for being profitable. This paper proposes a new mathematical model that considers how maintenance tasks should be scheduled and performed by technicians transported using a fleet of dedicated vessels. The model is novel in its combination of modelling several work shifts and including vessels that can stay offshore for several shifts, while handling large maintenance tasks and accurate calculation of downtime costs. Simulation is used to evaluate the performance of the model in its pure form, as well as when solved heuristically using a rolling horizon heuristic. The results indicate that the end-of-horizon effects of the mathematical formulation are handled effectively. Computational experiments also illustrate how the mathematical model coupled with simulation can be used to evaluate strategic decisions regarding the composition of a vessel fleet used to execute maintenance tasks.

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“…This approach, although computationally effective, lacks the flexibility to incorporate the possibility of repairs taking longer than expected. Furthermore, in the last five years, the problem of vessel routing for offshore wind farms was tackled by Dai et al [5], who used a branch and bound method, Zhang [6], who used Ant Colony Optimisation, and Stålhane et al [7], who used a path-flow model. To date, no model for vessel routing optimisation in the offshore wind domain attempted to take into account uncertainties on the expected maintenance action time and wave height, which are a consideration when planning vessel routing in real life.…”

Section: Introductionmentioning

confidence: 99%

Decision Support Tool for Offshore Wind Farm Vessel Routing under Uncertainty

2018

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This paper for the first time captures the impact of uncertain maintenance action times on vessel routing for realistic offshore wind farm problems. A novel methodology is presented to incorporate uncertainties, e.g., on the expected maintenance duration, into the decision-making process. Users specify the extent to which these unknown elements impact the suggested vessel routing strategy. If uncertainties are present, the tool outputs multiple vessel routing policies with varying likelihoods of success. To demonstrate the tool's capabilities, two case studies were presented. Firstly, simulations based on synthetic data illustrate that in a scenario with uncertainties, the cost-optimal solution is not necessarily the best choice for operators. Including uncertainties when calculating the vessel routing policy led to a 14% increase in the number of wind turbines maintained at the end of the day. Secondly, the tool was applied to a real-life scenario based on an offshore wind farm in collaboration with a United Kingdom (UK) operator. The results showed that the assignment of vessels to turbines generated by the tool matched the policy chosen by wind farm operators. By producing a range of policies for consideration, this tool provided operators with a structured and transparent method to assess trade-offs and justify decisions.

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Routing and Scheduling of Maintenance Fleet for Offshore Wind Farms

Cited by 70 publications

References 9 publications

Optimisation of maintenance routing and scheduling for offshore wind farms

Optimisation of maintenance routing and scheduling for offshore wind farms

Scheduling of Maintenance Tasks and Routing of a Joint Vessel Fleet for Multiple Offshore Wind Farms

Decision Support Tool for Offshore Wind Farm Vessel Routing under Uncertainty

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