Vessel Fleet Optimization for Maintenance Operations at Offshore Wind Farms Under Uncertainty

Stålhane, Magnus; Vefsnmo, Hanne; Halvorsen-Weare, Elin Espeland; Hvattum, Lars Magnus; Nonås, Lars Magne

doi:10.1016/j.egypro.2016.09.195

Cited by 36 publications

(27 citation statements)

References 8 publications

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“…The environmental conditions that usually hinder the majority of the offshore operations concern stochastic variables such as wind speed, wave height and wave period. The wind and wave influence on the uncertainty of the operational window (i.e., the period in which offshore works can be executed) is a well-known problem and has been extensively studied for installation and maintenance activities of offshore wind farms (Stålhane, Vefsnmo, Halvorsen-Weare, Hvattum, & Nonås, 2016;Kikuchi et al, 2009;Martin, Lazakis, Barbouchi, & Johanning, 2015;Leontaris, Morales-Nápoles, & Wolfert, 2016). Probabilistic models have been developed to cope with uncertainties of the duration of the operational windows and its effect on offshore infrastructural assets planning (time and costs).…”

Section: Introductionmentioning

confidence: 99%

Offshore infrastructure planning using a vine copula approach for environmental conditions: an application for replacement maintenance of tidal energy infrastructure

Nie

Leontaris

Hoogendoorn

et al. 2019

Structure and Infrastructure Engineering

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Installation and maintenance operations of offshore assets are impacted by local environmental conditions such as wave height and period, wind speed and current velocity. These parameters are substantially of influence for the asset planning (time and costs) given the uncertainty of operational windows. In this article, a method is proposed to construct realistic time series of the aforementioned dependent conditions using a vine copulas approach. This method makes it possible to obtain a large number of realizations of these conditions at a certain location. It is shown that the operational windows remain persistent with the original limited dataset. Moreover, this method enables the incorporation of environmental uncertainties in the operational planning processes. To illustrate the value of this method, an application regarding replacement maintenance of a tidal energy infrastructure is examined. For this purpose, the maintenance activities are represented as a semi-Markov decision process. For every synthetic environmental time series, the algorithm finds the optimal set of decisions and the corresponding maintenance plans, including replacement costs and revenue losses. It is shown that the proposed method is effective in replacement maintenance decision making, while taking into account the environmental uncertainties.

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Section: Introductionmentioning

confidence: 99%

Offshore infrastructure planning using a vine copula approach for environmental conditions: an application for replacement maintenance of tidal energy infrastructure

Nie

Leontaris

Hoogendoorn

et al. 2019

Structure and Infrastructure Engineering

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“…A numerical example is illustrated to validate the model. Stalhane et al (2016) determine the optimal fleet size and mix of vessels to support maintenance activities at offshore wind farms. A two-stage stochastic programming model is proposed where uncertainty in demand and weather conditions are considered.…”

Section: Introductionmentioning

confidence: 99%

Integrated Maintenance Decision Making Platform for Offshore Wind Farm with Optimal Vessel Fleet Size Support System

Szpytko¹,

Salgado²

2019

TransNav

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The paper presents a model to coordinate the predictive-preventive maintenance process of Offshore Wind Farm (OWF) with optimal Vessel Fleet (VF) size support system. The model is presented as a bilevel problem. On the first level, the model coordinates the predictive-preventive maintenance of the OWF and the distributed Power System minimizing the risk of Expected Energy not Supply (EENS). The risk is estimated with a sequential Markov Chain Monte Carlo (MCMC) simulation model. On the second level the model determining the optimal fleet size of vessels to support maintenance activities at OWF.

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“…Constraint (22) forces f ms to one if task m is completed within shift s and Constraint (23) forces f ms to zero if task m is not completed within shift s. Constraint (24) prohibits that a task m is performed during shifts after the task is completed.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…A majority of these models use simulation tools to analyze O&M related costs, and the use of optimization models for analyzing O&M costs are limited. Halvorsen-Weare et al [20], Gundegjerde et al [21] and Stålhane et al [22] use optimization models to investigate vessel fleets and determine the optimal fleet size and mix for an offshore wind farm. These models can be used as support when deciding when and how many vessels to purchase or rent, addressing decisions on a strategic level for O&M in offshore wind farms.…”

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

Self Cite

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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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Vessel Fleet Optimization for Maintenance Operations at Offshore Wind Farms Under Uncertainty

Cited by 36 publications

References 8 publications

Offshore infrastructure planning using a vine copula approach for environmental conditions: an application for replacement maintenance of tidal energy infrastructure

Offshore infrastructure planning using a vine copula approach for environmental conditions: an application for replacement maintenance of tidal energy infrastructure

Integrated Maintenance Decision Making Platform for Offshore Wind Farm with Optimal Vessel Fleet Size Support System

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

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