A decision support system for strategic maintenance planning in offshore wind farms: decision supply system for offshore wind farms

Xiaodong Li; Djamila Ouelhadj; Xiang Song; Dylan Francis Jones; Graham Thomas Wall; Kerry E. Howell; Paul Igwe; Simon Martin; Dongping  Song; Emmanuel  Pertin

doi:10.1016/j.renene.2016.07.037

A decision support system for strategic maintenance planning in offshore wind farms: decision supply system for offshore wind farms

Xiaodong Li, Djamila Ouelhadj, Xiang Song, Dylan Francis Jones, Graham Thomas Wall, Kerry E. Howell, Paul Igwe, Simon Martin, Dongping Song, Emmanuel Pertin

Research output: Contribution to journal › Article › peer-review

593 Downloads (Pure)

Abstract

This paper presents a Decision Support System (DSS) for maintenance cost optimisation at an Offshore Wind Farm (OWF). The DSS is designed for use by multiple stakeholders in the OWF sector with the overall goal of informing maintenance strategy and hence reducing overall lifecycle maintenance costs at the OWF. Two optimisation models underpin the DSS. The first is a deterministic model that is intended for use by stakeholders with access to accurate failure rate data. The second is a stochastic model that is intended for use by stakeholders who have less certainty about failure rates. Solutions of both models are presented using a UK OWF that is in construction as an example. Conclusions as to the value of failure rate data are drawn by comparing the results of the two models. Sensitivity analysis is undertaken with respect to the turbine failure rate frequency and number of turbines at the site, with near linear trends observed for both factors. Finally, overall conclusions are drawn in the context of maintenance planning in the OWF sector.

Original language	English
Pages (from-to)	784-799
Number of pages	32
Journal	Renewable Energy
Volume	99
Early online date	31 Jul 2016
DOIs	https://doi.org/10.1016/j.renene.2016.07.037
Publication status	Published - Dec 2016

Keywords

offshore wind
renewable energy
operations and maintenance
decision support
stochastic optimisation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.renene.2016.07.037

A decision support system for strategic maintenance planning in offshore wind farmsAccepted author manuscript (Post-print), 1.35 MBLicence: CC BY-NC-ND

Offshore Operations Maintenance & Mutualisation
Jones, D., Song, X., Ouelhadj, D. & Wall, G.
1/09/12 → 31/08/15
Project: Research

Cite this

@article{1cb4112afcc04dcf9fb2ab5ba18e89aa,

title = "A decision support system for strategic maintenance planning in offshore wind farms: decision supply system for offshore wind farms",

abstract = "This paper presents a Decision Support System (DSS) for maintenance cost optimisation at an Offshore Wind Farm (OWF). The DSS is designed for use by multiple stakeholders in the OWF sector with the overall goal of informing maintenance strategy and hence reducing overall lifecycle maintenance costs at the OWF. Two optimisation models underpin the DSS. The first is a deterministic model that is intended for use by stakeholders with access to accurate failure rate data. The second is a stochastic model that is intended for use by stakeholders who have less certainty about failure rates. Solutions of both models are presented using a UK OWF that is in construction as an example. Conclusions as to the value of failure rate data are drawn by comparing the results of the two models. Sensitivity analysis is undertaken with respect to the turbine failure rate frequency and number of turbines at the site, with near linear trends observed for both factors. Finally, overall conclusions are drawn in the context of maintenance planning in the OWF sector. ",

keywords = "offshore wind, renewable energy, operations and maintenance, decision support, stochastic optimisation",

author = "Xiaodong Li and Djamila Ouelhadj and Xiang Song and Jones, {Dylan Francis} and Wall, {Graham Thomas} and Howell, {Kerry E.} and Paul Igwe and Simon Martin and Dongping Song and Emmanuel Pertin",

year = "2016",

month = dec,

doi = "10.1016/j.renene.2016.07.037",

language = "English",

volume = "99",

pages = "784--799",

journal = "Renewable Energy",

issn = "0960-1481",

publisher = "Elsevier BV",

}

TY - JOUR

T1 - A decision support system for strategic maintenance planning in offshore wind farms

T2 - decision supply system for offshore wind farms

AU - Li, Xiaodong

AU - Ouelhadj, Djamila

AU - Song, Xiang

AU - Jones, Dylan Francis

AU - Wall, Graham Thomas

AU - Howell, Kerry E.

AU - Igwe, Paul

AU - Martin, Simon

AU - Song, Dongping

AU - Pertin, Emmanuel

PY - 2016/12

Y1 - 2016/12

N2 - This paper presents a Decision Support System (DSS) for maintenance cost optimisation at an Offshore Wind Farm (OWF). The DSS is designed for use by multiple stakeholders in the OWF sector with the overall goal of informing maintenance strategy and hence reducing overall lifecycle maintenance costs at the OWF. Two optimisation models underpin the DSS. The first is a deterministic model that is intended for use by stakeholders with access to accurate failure rate data. The second is a stochastic model that is intended for use by stakeholders who have less certainty about failure rates. Solutions of both models are presented using a UK OWF that is in construction as an example. Conclusions as to the value of failure rate data are drawn by comparing the results of the two models. Sensitivity analysis is undertaken with respect to the turbine failure rate frequency and number of turbines at the site, with near linear trends observed for both factors. Finally, overall conclusions are drawn in the context of maintenance planning in the OWF sector.

AB - This paper presents a Decision Support System (DSS) for maintenance cost optimisation at an Offshore Wind Farm (OWF). The DSS is designed for use by multiple stakeholders in the OWF sector with the overall goal of informing maintenance strategy and hence reducing overall lifecycle maintenance costs at the OWF. Two optimisation models underpin the DSS. The first is a deterministic model that is intended for use by stakeholders with access to accurate failure rate data. The second is a stochastic model that is intended for use by stakeholders who have less certainty about failure rates. Solutions of both models are presented using a UK OWF that is in construction as an example. Conclusions as to the value of failure rate data are drawn by comparing the results of the two models. Sensitivity analysis is undertaken with respect to the turbine failure rate frequency and number of turbines at the site, with near linear trends observed for both factors. Finally, overall conclusions are drawn in the context of maintenance planning in the OWF sector.

KW - offshore wind

KW - renewable energy

KW - operations and maintenance

KW - decision support

KW - stochastic optimisation

U2 - 10.1016/j.renene.2016.07.037

DO - 10.1016/j.renene.2016.07.037

M3 - Article

SN - 0960-1481

VL - 99

SP - 784

EP - 799

JO - Renewable Energy

JF - Renewable Energy

ER -

A decision support system for strategic maintenance planning in offshore wind farms: decision supply system for offshore wind farms

Abstract

Keywords

UN SDGs

Access to Document

Fingerprint

Projects

Offshore Operations Maintenance & Mutualisation

Cite this