A Bayesian network based approach for integration of condition-based maintenance in strategic offshore wind farm O&M simulation models

Jannie Sønderkær Nielsen, John Dalsgaard Sørensen, Iver Bakken Sperstad, Thomas Welte

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

In the overall decision problem regarding optimization of operation and maintenance (O&M) for offshore wind farms, there are many approaches for solving parts of the overall decision problem. Simulation-based strategy models accurately capture system effects related to logistics, but model condition-based maintenance (CBM) in a simplified manner. The influence of the CBM strategy on the failure rate can be directly consid-ered using a risk-based approach, but here logistics is modelled in a simplified manner. This paper presents an efficient approach for accurate integration of CBM in simulation-based strategy models. Using Bayesian net-works, the probability distribution for the time of failure and the conditional probability distribution for the time of CBM given the time of failure is estimated accounting for the CBM strategy, and are used by the sim-ulation-based strategy model to generate failures and CBM tasks. An example considering CBM for wind turbine blades demonstrates the feasibility of the approach.
Original languageEnglish
Title of host publicationLife-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision : Proceedings of the Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE 2018)
EditorsRobby Caspeele, Luc Taerwe, Dan M. Frangopol
PublisherCRC Press
Publication date2019
Pages2153-2160
ChapterSS10:Value of structural health monitoring information for the life-cycle management of civil structures
ISBN (Print)978-1-138-62633-1
ISBN (Electronic)978-1-315-22891-4
Publication statusPublished - 2019
EventThe Sixth International Symposium on Life-Cycle Civil Engineering - Ghent, Belgium
Duration: 28 Oct 201831 Oct 2018
Conference number: 6
http://www.ialcce2018.org/#/home

Conference

ConferenceThe Sixth International Symposium on Life-Cycle Civil Engineering
Number6
CountryBelgium
CityGhent
Period28/10/201831/10/2018
Internet address

Fingerprint

Offshore wind farms
Bayesian networks
Probability distributions
Logistics
Wind turbines
Turbomachine blades

Cite this

Nielsen, J. S., Sørensen, J. D., Sperstad, I. B., & Welte, T. (2019). A Bayesian network based approach for integration of condition-based maintenance in strategic offshore wind farm O&M simulation models. In R. Caspeele, L. Taerwe, & D. M. Frangopol (Eds.), Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision: Proceedings of the Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE 2018) (pp. 2153-2160). CRC Press.
Nielsen, Jannie Sønderkær ; Sørensen, John Dalsgaard ; Sperstad, Iver Bakken ; Welte, Thomas. / A Bayesian network based approach for integration of condition-based maintenance in strategic offshore wind farm O&M simulation models. Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision: Proceedings of the Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE 2018). editor / Robby Caspeele ; Luc Taerwe ; Dan M. Frangopol. CRC Press, 2019. pp. 2153-2160
@inproceedings{90195ec2ea9e4ed9aeb25b93b13f89fe,
title = "A Bayesian network based approach for integration of condition-based maintenance in strategic offshore wind farm O&M simulation models",
abstract = "In the overall decision problem regarding optimization of operation and maintenance (O&M) for offshore wind farms, there are many approaches for solving parts of the overall decision problem. Simulation-based strategy models accurately capture system effects related to logistics, but model condition-based maintenance (CBM) in a simplified manner. The influence of the CBM strategy on the failure rate can be directly consid-ered using a risk-based approach, but here logistics is modelled in a simplified manner. This paper presents an efficient approach for accurate integration of CBM in simulation-based strategy models. Using Bayesian net-works, the probability distribution for the time of failure and the conditional probability distribution for the time of CBM given the time of failure is estimated accounting for the CBM strategy, and are used by the sim-ulation-based strategy model to generate failures and CBM tasks. An example considering CBM for wind turbine blades demonstrates the feasibility of the approach.",
author = "Nielsen, {Jannie S{\o}nderk{\ae}r} and S{\o}rensen, {John Dalsgaard} and Sperstad, {Iver Bakken} and Thomas Welte",
year = "2019",
language = "English",
isbn = "978-1-138-62633-1",
pages = "2153--2160",
editor = "Robby Caspeele and Luc Taerwe and Frangopol, {Dan M.}",
booktitle = "Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision",
publisher = "CRC Press",

}

Nielsen, JS, Sørensen, JD, Sperstad, IB & Welte, T 2019, A Bayesian network based approach for integration of condition-based maintenance in strategic offshore wind farm O&M simulation models. in R Caspeele, L Taerwe & DM Frangopol (eds), Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision: Proceedings of the Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE 2018). CRC Press, pp. 2153-2160, The Sixth International Symposium on Life-Cycle Civil Engineering, Ghent, Belgium, 28/10/2018.

A Bayesian network based approach for integration of condition-based maintenance in strategic offshore wind farm O&M simulation models. / Nielsen, Jannie Sønderkær; Sørensen, John Dalsgaard; Sperstad, Iver Bakken; Welte, Thomas.

Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision: Proceedings of the Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE 2018). ed. / Robby Caspeele; Luc Taerwe; Dan M. Frangopol. CRC Press, 2019. p. 2153-2160.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

TY - GEN

T1 - A Bayesian network based approach for integration of condition-based maintenance in strategic offshore wind farm O&M simulation models

AU - Nielsen, Jannie Sønderkær

AU - Sørensen, John Dalsgaard

AU - Sperstad, Iver Bakken

AU - Welte, Thomas

PY - 2019

Y1 - 2019

N2 - In the overall decision problem regarding optimization of operation and maintenance (O&M) for offshore wind farms, there are many approaches for solving parts of the overall decision problem. Simulation-based strategy models accurately capture system effects related to logistics, but model condition-based maintenance (CBM) in a simplified manner. The influence of the CBM strategy on the failure rate can be directly consid-ered using a risk-based approach, but here logistics is modelled in a simplified manner. This paper presents an efficient approach for accurate integration of CBM in simulation-based strategy models. Using Bayesian net-works, the probability distribution for the time of failure and the conditional probability distribution for the time of CBM given the time of failure is estimated accounting for the CBM strategy, and are used by the sim-ulation-based strategy model to generate failures and CBM tasks. An example considering CBM for wind turbine blades demonstrates the feasibility of the approach.

AB - In the overall decision problem regarding optimization of operation and maintenance (O&M) for offshore wind farms, there are many approaches for solving parts of the overall decision problem. Simulation-based strategy models accurately capture system effects related to logistics, but model condition-based maintenance (CBM) in a simplified manner. The influence of the CBM strategy on the failure rate can be directly consid-ered using a risk-based approach, but here logistics is modelled in a simplified manner. This paper presents an efficient approach for accurate integration of CBM in simulation-based strategy models. Using Bayesian net-works, the probability distribution for the time of failure and the conditional probability distribution for the time of CBM given the time of failure is estimated accounting for the CBM strategy, and are used by the sim-ulation-based strategy model to generate failures and CBM tasks. An example considering CBM for wind turbine blades demonstrates the feasibility of the approach.

UR - https://doi.org/10.1201/9781315228914

M3 - Article in proceeding

SN - 978-1-138-62633-1

SP - 2153

EP - 2160

BT - Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision

A2 - Caspeele, Robby

A2 - Taerwe, Luc

A2 - Frangopol, Dan M.

PB - CRC Press

ER -

Nielsen JS, Sørensen JD, Sperstad IB, Welte T. A Bayesian network based approach for integration of condition-based maintenance in strategic offshore wind farm O&M simulation models. In Caspeele R, Taerwe L, Frangopol DM, editors, Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision: Proceedings of the Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE 2018). CRC Press. 2019. p. 2153-2160