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研究生: Nguyen Phuong Thao Nguyen
Nguyen Phuong Thao Nguyen
論文名稱: 家庭層級離網混合可再生能源系統的多目標容量設計最佳化
Multi-Objective Sizing Optimization of Off-grid Hybrid Renewable Energy System at Household Level
指導教授: 喻奉天
Vincent F. Yu
郭伯勳
Po-Hsun Kuo
口試委員: 喻奉天
Vincent F. Yu
郭伯勳
Po-Hsun Kuo
曾世賢
Shih-Hsien Tseng
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: 2023
畢業學年度: 112
語文別: 英文
論文頁數: 61
中文關鍵詞: 混合再生能源系統多目標優化優化微電網設計加權求和法經濟環境分析
外文關鍵詞: Hybrid renewable energy system, Multi-objective optimization, Optimal microgrid design, Weighted sum method, Economic-environmental analysis
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  • The increasing energy demand and the urgent need to reduce greenhouse gas emissions have made the design of optimal hybrid renewable energy systems (HRESs) more essential than ever. In this context, the system reliability, the intermittency of renewables, and the economic-environmental trade-offs are the main challenges that need to be addressed toward the transition to a more sustainable and reliable energy future. This study proposes a mixed integer non-linear programming for multi-objective optimal sizing of HRES including wind turbine, energy storage, and diesel generator. Two functions of the economic and environmental objectives are to minimize the total system cost and total carbon emissions released into the atmosphere, respectively; while ensuring a high degree of renewable fraction and system reliability. The weighted sum method combining a dynamic weight assignment strategy is used to find the set of optimal solutions and investigate the two conflicting objectives. The developed system is applied in different five geographic regions in Taiwan and investigated for two types of wind turbines. Case studies on household and micro-community levels are performed based on real load demand data from a three-story house and synthetic data from an island, respectively. Moreover, a sensitivity analysis is conducted to investigate how sensitive interest rate are to the proposed model. Results based on a single objective reveal significant differences between environmental and economic optimization, whereas multi-objective optimization has proven to be an effective method for exploring the trade-offs between these two conflicting objectives. The findings from this study contribute to accelerating the transition to cleaner and more resilient energy systems. The conclusion highlights additional areas for future research.

    TABLE OF CONTENTS ABSTRACT i ACKNOWLEDGEMENT ii TABLE OF CONTENTS iv LIST OF FIGURES vii LIST OF TABLES viii CHAPTER 1 INTRODUCTION 1 1.1 Research Background 1 1.2 Research Objectives and Contributions 3 1.3 Thesis Organization 4 CHAPTER 2 LITERATURE REVIEW 5 2.1 Hybrid Renewable Energy System 5 2.2 Environmental-Economic Multi-Objective Optimization 6 CHAPTER 3 MATHEMATICAL MODEL AND SOLUTION APPROACH 9 3.1 Problem Description 9 3.1.1 Wind Turbine 11 3.1.2 Energy Storage 11 3.1.3 Diesel Generator 12 3.1.4 Power Management Strategy 13 3.2 Problem Assumption 14 3.3 Mathematical Formulation 15 3.4 Objective Functions 19 3.4.1 Total Cost 19 3.4.2 Total Carbon Emission 20 3.5 Problem Constraints 21 3.5.1 Renewable Fraction 21 3.5.2 Reliability 22 3.5.3 Other Constraints 24 3.6 Optimization Methods 25 3.6.1 Compromise Solution 25 3.6.2 Dynamic Weighted Sum Method 26 CHAPTER 4 COMPUTATIONAL EXPERIMENTS 28 4.1 Experimental Setup 28 4.1.1 Input parameters 28 4.1.2 Load Demand 30 4.1.3 Wind Speed 32 4.2 Microgrid System at Household Level 33 4.2.1 Reliability 33 4.2.2 Multi-Objective Optimization 34 4.3 Microgrid System at Micro-Community Level 46 4.3.1 Reliability 46 4.3.2 Multi-Objective Optimization 48 4.4 Sensitivity analysis 50 CHAPTER 5 CONCLUSIONS AND FUTURE RESEARCH 52 5.1 Conclusions 52 5.2 Research Limitations 53 5.3 Future Research 54

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