A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

With a typical investment of in excess of £100 million for each project, the installation phase of offshore wind farms is an area where substantial cost-reductions can be achieved; however, to-date there have been relatively few studies exploring this. In this paper, we develop a mixed-method framework which exploits the complementary strengths of two decision-support methods: discrete-event simulation and robust optimisation. The simulation component allows developers to estimate the impact of user-defined asset selections on the likely cost and duration of the full or partial completion of the installation process. The optimisation component provides developers with an installation schedule that is robust to changes in operation durations due to weather uncertainties. The combined framework provides a decision-support tool which enhances the individual capability of both models by feedback channels between the two, and provides a mechanism to address current OWF installation projects. The combined tool, verified and validated by external experts, was applied to an installation case study to illustrate the application of the combined approach. An installation schedule was identified which accounted for seasonal uncertainties and optimised the ordering of activities.
LanguageEnglish
Pages894-906
Number of pages13
JournalEuropean Journal of Operational Research
Volume264
Issue number3
Early online date26 May 2017
DOIs
Publication statusPublished - 1 Feb 2018

Fingerprint

Offshore wind farms
Mixed Methods
Simulation Framework
Decision Support
Schedule
Uncertainty
Simulation Optimization
Robust Optimization
Optimization
Costs
Discrete Event Simulation
Weather
Excess
Completion
Likely
Partial
Estimate
Simulation
Discrete event simulation
Cost reduction

Keywords

  • OR in Energy
  • mixed methods
  • action research
  • offshore wind farm
  • installation logistics

Cite this

@article{3ab6bcda78784268ac71988ff87fb32d,
title = "A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations",
abstract = "With a typical investment of in excess of £100 million for each project, the installation phase of offshore wind farms is an area where substantial cost-reductions can be achieved; however, to-date there have been relatively few studies exploring this. In this paper, we develop a mixed-method framework which exploits the complementary strengths of two decision-support methods: discrete-event simulation and robust optimisation. The simulation component allows developers to estimate the impact of user-defined asset selections on the likely cost and duration of the full or partial completion of the installation process. The optimisation component provides developers with an installation schedule that is robust to changes in operation durations due to weather uncertainties. The combined framework provides a decision-support tool which enhances the individual capability of both models by feedback channels between the two, and provides a mechanism to address current OWF installation projects. The combined tool, verified and validated by external experts, was applied to an installation case study to illustrate the application of the combined approach. An installation schedule was identified which accounted for seasonal uncertainties and optimised the ordering of activities.",
keywords = "OR in Energy, mixed methods, action research, offshore wind farm, installation logistics",
author = "Euan Barlow and {Tezcaner {\"O}zt{\"u}rk}, Diclehan and Matthew Revie and Kerem Akartunali and Day, {Alexander H.} and Evangelos Boulougouris",
year = "2018",
month = "2",
day = "1",
doi = "10.1016/j.ejor.2017.05.043",
language = "English",
volume = "264",
pages = "894--906",
journal = "European Journal of Operational Research",
issn = "0377-2217",
number = "3",

}

TY - JOUR

T1 - A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations

AU - Barlow, Euan

AU - Tezcaner Öztürk, Diclehan

AU - Revie, Matthew

AU - Akartunali, Kerem

AU - Day, Alexander H.

AU - Boulougouris, Evangelos

PY - 2018/2/1

Y1 - 2018/2/1

N2 - With a typical investment of in excess of £100 million for each project, the installation phase of offshore wind farms is an area where substantial cost-reductions can be achieved; however, to-date there have been relatively few studies exploring this. In this paper, we develop a mixed-method framework which exploits the complementary strengths of two decision-support methods: discrete-event simulation and robust optimisation. The simulation component allows developers to estimate the impact of user-defined asset selections on the likely cost and duration of the full or partial completion of the installation process. The optimisation component provides developers with an installation schedule that is robust to changes in operation durations due to weather uncertainties. The combined framework provides a decision-support tool which enhances the individual capability of both models by feedback channels between the two, and provides a mechanism to address current OWF installation projects. The combined tool, verified and validated by external experts, was applied to an installation case study to illustrate the application of the combined approach. An installation schedule was identified which accounted for seasonal uncertainties and optimised the ordering of activities.

AB - With a typical investment of in excess of £100 million for each project, the installation phase of offshore wind farms is an area where substantial cost-reductions can be achieved; however, to-date there have been relatively few studies exploring this. In this paper, we develop a mixed-method framework which exploits the complementary strengths of two decision-support methods: discrete-event simulation and robust optimisation. The simulation component allows developers to estimate the impact of user-defined asset selections on the likely cost and duration of the full or partial completion of the installation process. The optimisation component provides developers with an installation schedule that is robust to changes in operation durations due to weather uncertainties. The combined framework provides a decision-support tool which enhances the individual capability of both models by feedback channels between the two, and provides a mechanism to address current OWF installation projects. The combined tool, verified and validated by external experts, was applied to an installation case study to illustrate the application of the combined approach. An installation schedule was identified which accounted for seasonal uncertainties and optimised the ordering of activities.

KW - OR in Energy

KW - mixed methods

KW - action research

KW - offshore wind farm

KW - installation logistics

UR - https://www.sciencedirect.com/journal/european-journal-of-operational-research

U2 - 10.1016/j.ejor.2017.05.043

DO - 10.1016/j.ejor.2017.05.043

M3 - Article

VL - 264

SP - 894

EP - 906

JO - European Journal of Operational Research

T2 - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 3

ER -