Condition based maintenance optimization for offshore wind turbine considering opportunities based on neural network approach

Lu, Yang; Sun, Liping; Zhang, Xinyue; Feng, Feng; Kang, Jichuan; Fu, Guoqiang

doi:10.1016/j.apor.2018.02.016

Cited by 65 publications

(21 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Research by Huang et al [11] showed that meaningful wave height is the main factor limiting landing system work and maintenance personnel landing, which determines the validity window of marine maintenance. Tian [12] developed a Condition based maintenance (CBM) strategy for WTs to optimize maintenance cost, and Lu et al [13] optimized OWTs by the CBM strategy, the results showed that the CBM strategy is more effective than the time-based maintenance policies. Wu et al [14] established a weather-based Markov maintenance model of an offshore wind system, estimated accessibility of offshore wind power maintenance and considered correlation between equipment maintenance, but the study object was not expanded to offshore wind farm, and maintenance imperfection in actual engineering was neglected.…”

Section: Introductionmentioning

confidence: 99%

Research on a Comprehensive Maintenance Optimization Strategy for an Offshore Wind Farm

Sun

Yang

2021

Energies

Self Cite

View full text Add to dashboard Cite

Offshore wind is considered a crucial part in the future energy supply. However, influenced by weather conditions, the maintenance of offshore wind turbine system (OWTs) equipment is challenged by poor accessibility and serious failure consequences. It is necessary to study the optimized strategy of comprehensive maintenance for offshore wind farms, with consideration of the influences of incomplete equipment maintenance, weather accessibility and economic relevance. In this paper, a Monte Carlo algorithm-improved factor is presented to simulate the imperfect preventive maintenance activity, and waiting windows were created to study the accessibility of weather conditions. Based on a rolling horizon approach, an opportunity group maintenance model of an offshore wind farm was proposed. The maintenance correlations between systems and between equipment as well as breakdown losses, maintenance uncertainty, and weather conditions were taken into account in the model, thus realizing coordination of maintenance activities of different systems and different equipment. The proposed model was applied to calculate the maintenance cost of the Dafengtian Offshore Wind Farm in China. Results proved that the proposed model could realize long-term dynamic optimization of offshore wind farm maintenance activities, increase the total availability of the wind power system and reduce total maintenance costs.

show abstract

Section: Introductionmentioning

confidence: 99%

Research on a Comprehensive Maintenance Optimization Strategy for an Offshore Wind Farm

Sun

Yang

2021

Energies

Self Cite

View full text Add to dashboard Cite

show abstract

“…Houda et al 16 presented a decision-making approach for preventive maintenance strategies by the use of real options. Lu et al 17 proposed an opportunistic condition-based maintenance (CBM) optimization approach for offshore WTs, in which economic dependence exists among the components that are subjected to condition monitoring. WT reliability studies will help to identify the most critical components of a WT, on the basis that identifying the most critical components will optimize the maintenance.…”

Section: Introductionmentioning

confidence: 99%

Analysis of long-term temperature monitoring of multiple wind turbines

Wang

Zhao

Yang

et al. 2021

Measurement and Control

View full text Add to dashboard Cite

The historical temperature data logged in the supervisory control and data acquisition (SCADA) system contains a wealth of information that can assist with the performance optimization of wind turbines (WTs). However, mining and using these long-term data is difficult and time-consuming due to their complexity, volume, etc. In this study, we tracked and analyzed the 5-year trends of major SCADA temperature rise variables in relation to the active power of four WTs in a real wind farm. To uncover useful information, an extended version of the bins method, which calculates the standard deviation (SD) as well as the average, is proposed and adopted. The implications of the analysis for engineering practice are discussed from multiple perspectives. The research results demonstrate a change in the patterns of the main temperature rise variables in a real wind farm, completeness of the monitoring of the WT internal temperature state, influence of wind turbine aging on temperature signals, a correlation between different measurement points, and a correlation between signals from different years. The knowledge gained from this research provides a reference for the development of more practical and comprehensive condition monitoring systems and methods, as well as better operation maintenance strategies.

show abstract

“…The opportunistic maintenance strategy was combined with condition-based model in Ref. [15][16][17]. A multi-objective opportunistic maintenance strategy was implemented to optimize the income of after-sales in Ref.…”

Section: Introductionmentioning

confidence: 99%

An improved opportunistic group replacement maintenance strategy for wind turbines

Wang

et al. 2020

Energy Science & Engineering

View full text Add to dashboard Cite

show abstract

Condition based maintenance optimization for offshore wind turbine considering opportunities based on neural network approach

Cited by 65 publications

References 23 publications

Research on a Comprehensive Maintenance Optimization Strategy for an Offshore Wind Farm

Research on a Comprehensive Maintenance Optimization Strategy for an Offshore Wind Farm

Analysis of long-term temperature monitoring of multiple wind turbines

An improved opportunistic group replacement maintenance strategy for wind turbines

Contact Info

Product

Resources

About