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研究生: Pham Xuan Loc
Pham Xuan Loc
論文名稱: 離岸風機系統維修排程與路徑優化之研究
Research on Maintenance Scheduling and Routing Optimization for Offshore Wind Systems
指導教授: 周碩彥
Shuo-Yan Chou
郭伯勳
Po-Hsun Kuo
口試委員: 游慧光
Tiffany Hui-KuangYu
學位類別: 碩士
Master
系所名稱: 管理學院 - 工業管理系
Department of Industrial Management
論文出版年: 2020
畢業學年度: 108
語文別: 英文
論文頁數: 85
中文關鍵詞: Offshore wind systemOperation and maintenanceMaintenance scheduleMaintenance routingOptimization maintenance
外文關鍵詞: Offshore wind system, Operation and maintenance, Maintenance schedule, Maintenance routing, Optimization maintenance
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Offshore wind energy has been considered as one of the best solutions among renewable energy sources for reducing dependence on conventional energy such as fossil fuels. However, the cost is still the major obstacle in expanding offshore wind energy comparing to other renewable energy sources. In order to address this obstacle and make offshore wind energy become more competitive in energy market, an effective solution is enhancing the efficiency of maintenance activity to reduce maintenance cost that contributes a large portion to total life cycle cost of offshore wind systems. In this study, an optimal approach for executing maintenance activities at offshore wind systems is proposed. Firstly, deterioration process of offshore wind system is analyzed through component’s reliability with respect to the effect of previous maintenance activity. After understanding the condition of wind system’s components, a maintenance scheduling and vessel routing approach is proposed with the aim of minimizing maintenance cost while ensuring the system’s reliability. Maintenance schedule in this study is formulated dynamically for single component, multiple components of a wind turbine, multiple wind turbines and multiple types of wind turbine under a variety of influential factors. To improve the robustness and accuracy of proposed approach, a numeral example with information from Taiwan is investigated. The experimental results show that by applying the proposed approach, maintenance duration can be reduced 24%-56%, vessel traveling distance also saves in a range of 52.50%-62.40%, which leads maintenance cost saving up to 15.15%-29.23%. Such that total maintenance cost is consequently obtained at optimal level.

ABSTRACT i ACKNOWLEDGEMENT iv LIST OF FIGURES vii LIST OF TABLES ix CHAPTER 1 1 INTRODUCTION 1 1.1 Research background and motivation 1 1.2 Research objectives and contributions 3 1.3 Organization of thesis 4 CHAPTER 2 5 LITERATURE REVIEW 5 2.1 Development of offshore wind energy 5 2.1.1 Development of offshore wind energy in the world 5 2.1.2 Development of offshore wind energy in Taiwan 8 2.2 Reliability of wind turbine 12 2.2.1 Generation of offshore wind turbine 12 2.2.2 Deterioration process of offshore wind turbine 15 2.3 Review on maintenance scheduling and routing 17 2.3.1 Review on maintenance strategies of offshore wind farm 17 2.3.2 Review on maintenance scheduling and routing of offshore wind farm 18 2.3.3 Review on maintenance vessels of offshore wind farm 21 2.3.4 Related works 25 CHAPTER 3 27 MODEL DEVELOPMENT 27 3.1 Overview of the proposed approach 27 3.2 Maintenance cost description 29 3.3 Maintenance scheduling 31 3.3.1 Individual maintenance scheduling 31 3.3.2 Tentative planning 32 3.3.3 Economic benefit analysis 33 3.3.4 Grouped maintenance scheduling 34 3.4 Optimal maintenance vessel routing approach 35 3.4.1 Mathematical programming model for maintenance vessel routing 36 3.4.2 Design of Simulated Annealing algorithm for maintenance vessel routing 38 CHAPTER 4 41 APPLICATIONS 41 4.1 Input data 41 4.2 Reliability of wind turbine components 43 4.3 Optimal maintenance scheduling and routing 45 4.3.1 Individual maintenance scheduling 45 4.3.2 Grouped maintenance scheduling 48 4.3.3 Optimal maintenance routing 50 4.3.4 Economic saving 53 4.4 Sensitive analysis 55 4.4.1 The effect of required technician numbers 55 4.4.2 The effect of distance to the shore 56 4.4.2 The effect of the number of maintenance vessels 58 CHAPTER 5 60 CONCLUSIONS 60 5.1 Conclusions 60 5.2 Limitations and Future works 62 REFERENCES 63 APPENDIX 70 Appendix 1 70 Appendix 2 72

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