A robust model for scheduling power productions of multiple offshore wind farms using one‐to‐many maintenance services

Abstract This paper studies the power production optimization problem of multiple offshore wind farms (OWFs) considering different maintenance demands and requirements under the wind power uncertainty. A decentralized robust operation optimization model is developed, in which OWFs and a maintenance...

Full description

Bibliographic Details
Main Authors: Bingying Zhang, Zijun Zhang
Format: Article
Language:English
Published: Wiley 2021-10-01
Series:IET Renewable Power Generation
Online Access:https://doi.org/10.1049/rpg2.12235
id doaj-2f4bf036935b4793b4bbf7ae8de2812a
record_format Article
spelling doaj-2f4bf036935b4793b4bbf7ae8de2812a2021-09-01T10:25:26ZengWileyIET Renewable Power Generation1752-14161752-14242021-10-0115132997301310.1049/rpg2.12235A robust model for scheduling power productions of multiple offshore wind farms using one‐to‐many maintenance servicesBingying Zhang0Zijun Zhang1School of Data Science City University of Hong Kong 83 Tat Chee Avenue Hong Kong SAR ChinaSchool of Data Science City University of Hong Kong 83 Tat Chee Avenue Hong Kong SAR ChinaAbstract This paper studies the power production optimization problem of multiple offshore wind farms (OWFs) considering different maintenance demands and requirements under the wind power uncertainty. A decentralized robust operation optimization model is developed, in which OWFs and a maintenance service provider (MSP) are treated as individual stakeholders with different interests but coupled by maintenance resources. Based on the analytical target cascading (ATC) algorithm, the model is decoupled into independent models for MSP and each OWF. The operation and objectives of individual entities can be autonomously optimized only considering their own conditions. For each OWF, the power production planning coupled with maintenance scheduling is formulated as a two‐stage robust optimization model and solved by a column‐and‐constraint generation (C&CG) algorithm to tackle the wind power uncertainty. Numerical experiments demonstrate the effectiveness of the proposed model and the applicability of the integrated solution method to the studied problem. Results illustrate that the developed model shows a better guarantee for individual interests of OWFs, lower communication burden, and better information privacy than the centralized optimization model, especially in large‐scale systems. The integrated solution framework can guarantee a quick convergence and optimality. Moreover, it reduces impacts of uncertain factors on power productions and maintenance schemes.https://doi.org/10.1049/rpg2.12235
collection DOAJ
language English
format Article
sources DOAJ
author Bingying Zhang
Zijun Zhang
spellingShingle Bingying Zhang
Zijun Zhang
A robust model for scheduling power productions of multiple offshore wind farms using one‐to‐many maintenance services
IET Renewable Power Generation
author_facet Bingying Zhang
Zijun Zhang
author_sort Bingying Zhang
title A robust model for scheduling power productions of multiple offshore wind farms using one‐to‐many maintenance services
title_short A robust model for scheduling power productions of multiple offshore wind farms using one‐to‐many maintenance services
title_full A robust model for scheduling power productions of multiple offshore wind farms using one‐to‐many maintenance services
title_fullStr A robust model for scheduling power productions of multiple offshore wind farms using one‐to‐many maintenance services
title_full_unstemmed A robust model for scheduling power productions of multiple offshore wind farms using one‐to‐many maintenance services
title_sort robust model for scheduling power productions of multiple offshore wind farms using one‐to‐many maintenance services
publisher Wiley
series IET Renewable Power Generation
issn 1752-1416
1752-1424
publishDate 2021-10-01
description Abstract This paper studies the power production optimization problem of multiple offshore wind farms (OWFs) considering different maintenance demands and requirements under the wind power uncertainty. A decentralized robust operation optimization model is developed, in which OWFs and a maintenance service provider (MSP) are treated as individual stakeholders with different interests but coupled by maintenance resources. Based on the analytical target cascading (ATC) algorithm, the model is decoupled into independent models for MSP and each OWF. The operation and objectives of individual entities can be autonomously optimized only considering their own conditions. For each OWF, the power production planning coupled with maintenance scheduling is formulated as a two‐stage robust optimization model and solved by a column‐and‐constraint generation (C&CG) algorithm to tackle the wind power uncertainty. Numerical experiments demonstrate the effectiveness of the proposed model and the applicability of the integrated solution method to the studied problem. Results illustrate that the developed model shows a better guarantee for individual interests of OWFs, lower communication burden, and better information privacy than the centralized optimization model, especially in large‐scale systems. The integrated solution framework can guarantee a quick convergence and optimality. Moreover, it reduces impacts of uncertain factors on power productions and maintenance schemes.
url https://doi.org/10.1049/rpg2.12235
work_keys_str_mv AT bingyingzhang arobustmodelforschedulingpowerproductionsofmultipleoffshorewindfarmsusingonetomanymaintenanceservices
AT zijunzhang arobustmodelforschedulingpowerproductionsofmultipleoffshorewindfarmsusingonetomanymaintenanceservices
AT bingyingzhang robustmodelforschedulingpowerproductionsofmultipleoffshorewindfarmsusingonetomanymaintenanceservices
AT zijunzhang robustmodelforschedulingpowerproductionsofmultipleoffshorewindfarmsusingonetomanymaintenanceservices
_version_ 1721182834636357632